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  • Data Quality and Master Data Management Resources

    - by Dejan Sarka
    Many companies or organizations do regular data cleansing. When you cleanse the data, the data quality goes up to some higher level. The data quality level is determined by the amount of work invested in the cleansing. As time passes, the data quality deteriorates, and you need to repeat the cleansing process. If you spend an equal amount of effort as you did with the previous cleansing, you can expect the same level of data quality as you had after the previous cleansing. And then the data quality deteriorates over time again, and the cleansing process starts over and over again. The idea of Data Quality Services is to mitigate the cleansing process. While the amount of time you need to spend on cleansing decreases, you will achieve higher and higher levels of data quality. While cleansing, you learn what types of errors to expect, discover error patterns, find domains of correct values, etc. You don’t throw away this knowledge. You store it and use it to find and correct the same issues automatically during your next cleansing process. The following figure shows this graphically. The idea of master data management, which you can perform with Master Data Services (MDS), is to prevent data quality from deteriorating. Once you reach a particular quality level, the MDS application—together with the defined policies, people, and master data management processes—allow you to maintain this level permanently. This idea is shown in the following picture. OK, now you know what DQS and MDS are about. You can imagine the importance on maintaining the data quality. Here are some resources that help you preparing and executing the data quality (DQ) and master data management (MDM) activities. Books Dejan Sarka and Davide Mauri: Data Quality and Master Data Management with Microsoft SQL Server 2008 R2 – a general introduction to MDM, MDS, and data profiling. Matching explained in depth. Dejan Sarka, Matija Lah and Grega Jerkic: MCTS Self-Paced Training Kit (Exam 70-463): Building Data Warehouses with Microsoft SQL Server 2012 – I wrote quite a few chapters about DQ and MDM, and introduced also SQL Server 2012 DQS. Thomas Redman: Data Quality: The Field Guide – you should start with this book. Thomas Redman is the father of DQ and MDM. Tyler Graham: Microsoft SQL Server 2012 Master Data Services – MDS in depth from a product team mate. Arkady Maydanchik: Data Quality Assessment – data profiling in depth. Tamraparni Dasu, Theodore Johnson: Exploratory Data Mining and Data Cleaning – advanced data profiling with data mining. Forthcoming presentations I am presenting a DQS and MDM seminar at PASS SQL Rally Amsterdam 2013: Wednesday, November 6th, 2013: Enterprise Information Management with SQL Server 2012 – a good kick start to your first DQ and / or MDM project. Courses Data Quality and Master Data Management with SQL Server 2012 – I wrote a 2-day course for SolidQ. If you are interested in this course, which I could also deliver in a shorter seminar way, you can contact your closes SolidQ subsidiary, or, of course, me directly on addresses [email protected] or [email protected]. This course could also complement the existing courseware portfolio of training providers, which are welcome to contact me as well. Start improving the quality of your data now!

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  • Encouraging software engineers to track time

    - by M. Dudley
    How can I encourage my coworkers to track the time they spend resolving issues and implementing features? We have software to do this, but they just don't enter the numbers. I want the team to get better at providing project estimates by comparing our past estimates to actual time spent. I suspect that my coworkers don't see the personal benefit, since they're not often involved in project scheduling.

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  • Big Data – Learning Basics of Big Data in 21 Days – Bookmark

    - by Pinal Dave
    Earlier this month I had a great time to write Bascis of Big Data series. This series received great response and lots of good comments I have received, I am going to follow up this basics series with further in-depth series in near future. Here is the consolidated blog post where you can find all the 21 days blog posts together. Bookmark this page for future reference. Big Data – Beginning Big Data – Day 1 of 21 Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21 Big Data – Evolution of Big Data – Day 3 of 21 Big Data – Basics of Big Data Architecture – Day 4 of 21 Big Data – Buzz Words: What is NoSQL – Day 5 of 21 Big Data – Buzz Words: What is Hadoop – Day 6 of 21 Big Data – Buzz Words: What is MapReduce – Day 7 of 21 Big Data – Buzz Words: What is HDFS – Day 8 of 21 Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21 Big Data – Buzz Words: What is NewSQL – Day 10 of 21 Big Data – Role of Cloud Computing in Big Data – Day 11 of 21 Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21 Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21 Big Data – Operational Databases Supporting Big Data – Columnar, Graph and Spatial Database – Day 14 of 21 Big DataData Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21 Big Data – Interacting with Hadoop – What is PIG? – What is PIG Latin? – Day 16 of 21 Big Data – Interacting with Hadoop – What is Sqoop? – What is Zookeeper? – Day 17 of 21 Big Data – Basics of Big Data Analytics – Day 18 of 21 Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21 Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21 Big Data – Final Wrap and What Next – Day 21 of 21 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Accelerate your SOA with Data Integration - Live Webinar Tuesday!

    - by dain.hansen
    Need to put wind in your SOA sails? Organizations are turning more and more to Real-time data integration to complement their Service Oriented Architecture. The benefit? Lowering costs through consolidating legacy systems, reducing risk of bad data polluting their applications, and shortening the time to deliver new service offerings. Join us on Tuesday April 13th, 11AM PST for our live webinar on the value of combining SOA and Data Integration together. In this webcast you'll learn how to innovate across your applications swiftly and at a lower cost using Oracle Data Integration technologies: Oracle Data Integrator Enterprise Edition, Oracle GoldenGate, and Oracle Data Quality. You'll also hear: Best practices for building re-usable data services that are high performing and scalable across the enterprise How real-time data integration can maximize SOA returns while providing continuous availability for your mission critical applications Architectural approaches to speed service implementation and delivery times, with pre-integrations to CRM, ERP, BI, and other packaged applications Register now for this live webinar!

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  • 14+ Real Estate WordPress Themes

    - by Aditi
    If you are looking for a great WordPress real estate theme. Below is a list of some of the best wordpress real estate themes, so you can find one, which is the best suited for you and be at par with increasing industry demands in real estates business.We have covered only the best themes available. The Themes are flexible & can be used by anybody in real estate business. If you are realtor, agent, appraiser or realty these can be modified as per your use. Estate It is an immensely powerful and simple to manage business theme. It offers advanced SEO control, clean code and styling modification features. It has new “Properties” management facility when installed – proving it’s far more than just a WordPress theme. It offers flexible page templates, an advanced search facility that allows you to drill down into properties based on very specific criteria, Google Maps integration and smart property images management. It is a complete web solution. It also has IDX functionality due to dsIDXpress plugin integration, which allows multi-listing services. Price: $200 View Demo Download ElegantEstate It makes your WordPress blog into a full-feature real estate website. The theme makes browsing your listings easy, and adds special integration features for property info, photos, Google Maps and more. Help increase sales by establishing an elegant and professional online presence today. It has opera compatibility, Netscape compatibility, Safari compatibility, WordPress 3.0 compatibility. It comes with five color schemes, threaded comments, optional blog-style structure, Gravatar ready, firefox compatible, IE8 + IE7 + IE6 compatible, advertisement ready, widget ready sidebars, theme options page, custom thumbnail images, PSD files, valid XHTML + CSS, smooth table less design, ePanel theme options, page templates, complete localization and many more features. Price: $39 (Package includes more than 55 themes) View Demo Download Open House Open House is fully compatible with WordPress 3.0+ and a highly customizable Real Estate WordPress theme. It has Google Maps Integration with Street View. It has a professional look for Agents and Realtors both. It is best suited for all markets and countries with theme localization, translation and internationalization. It provides for English, Spanish and Portuguese language files in the Developer Package. It has custom scripts, which makes it easy to add/delete/modify listings. It also includes photo gallery with a lightbox effect, gorgeous photo fade animations and automatic Google Maps integration. The theme can be used as a single or multi-agent website with individual Agent-Realtor pages with listings and biography information, Agent photo uploader, financing calculator.There is Multi Category search for potential customers to locate the house they want. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Residence Real Estate It is a WordPress 3.0+ compatible stunning real estate theme. It has a dynamic real estate framework management module for easy edit-delete-add more features options, which makes this theme super easy to customize to the market needs. It allows you to add your own labels and values in your own language and switch the theme to your own language with English and Spanish files included with the ability to add your own language. It offers Multi-Category search with breadcrumb filtered results, easy photo gallery management with drag-drop sorting of images. It allows you to build your own multi-category search section menu with custom labels-choices and unlimited dropdown menus. They have been presented in a professional module with search results in breadcrumb navigation. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Smooth Smooth is a WordPress Real Estate theme. It is a complete theme, which comes with Multi Category Search, Google Maps Integration, Agent Photo and Logo uploader that offers a professional and extremely affordable solution for Realtors and Agents to showcase their properties with ease. You can add your listings with the extremely easy and flexible Dynamic Real Estate Framework, edit-add-modify-delete all features, labels and values within the WordPress administration and upload unlimited photos to your galleries with latest WordPress 3.0+ features. It is a complete solution for real estate sites. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Homeowners It is another WordPress Real Estate theme, which is a fast loading optimized theme with Google Maps Integration, fully compatible with WordPress 3.0 features and all Real Estate markets. It has a professional clean look and it is full of features extremely easy to modify. It also provides for 12 new styles provided. English, Spanish and Portuguese language files are provided in the Developer Package. Homeowners WordPress Real Estate features custom scripts that make add/delete/modify listings an easy task with an included photo gallery with a lightbox effect and automatic Google Map integration with street view (New) Agents will have access only to their own listings and add the listing management for their account making this theme an ideal affordable solution for Realtors and Real Estate agencies. The theme can be used as a single or multi-agent website with individual Agent-Realtor pages with listings and biography information, Agent photo uploader, financing calculator. Multi category search has also been provided. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Real Agent Real Estate This theme is a WordPress 3.0+ compatible clean grid based real estate theme. It has a dynamic real estate framework management module for easy edit-delete-add more features options. It is easy to customize according to market. It allows you to add your own labels and values in your own language switch the theme to your own language with English and Spanish files included with the ability to add your own language. Multi-Category search with breadcrumb filtered results, easy photo gallery management with drag-drop sorting of images. You can upload property photos in bulk with the native WordPress uploader and the new image editing and resizing options in WordPress 3.0+. The theme features 5 different color styles, blue, black, red, green and purple with professional layouts, logo and agent photo uploaders. This theme is best suited for individual or multiple agents both. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Agent Press The AgentPress theme is an ideal solution for real estate agents. It offers multiple page templates that can be used to create a complete real estate website. You can create from single property templates to a custom homepage easily with it. It is compatible to WordPress 3.0 and 3.1. It has custom background/header, property template, 6 layout options, fixed width, threaded comments and many more features. Price: $99.95 View Demo Download Real Estate It is one of the best Real Estate themes. It offers single click auto install of the site, Allow user to pay & submit properties on your site, Multi-agent site with profiles, Strategically built real estate site with professional design, User dashboard to edit/renew their submissions, Auto generated Google Maps and Image Slideshows and many more unique features. Once the users search property as per their criteria, the properties are listed with all the necessary parameters that let them select the property of their choice. Users can also add the property to favorite so they can check the property later from their member area dashboard. Admin may display different sidebar on this page and add widgets of their choice. This theme is full of custom, dynamic widgets such as top agents, finance calculator, user login; advertise blocks, testimonials and so on. There is a property details page where users can see the actual property. The agent details is displayed with the full contact details and appropriate links so the visitor can get all info about the property being sold, seller and may contact them by filling out a simple form. The email will be sent directly to the person who listed the property. Price: $89.95 Single | $159.95 Developer View Demo Download Broker Real Estate It is also a WordPress 3.0+ compatible real estate theme. It has a featured property slideshow, dynamic real estate framework management module for easy edit-delete-add more features. You can add your own labels and values in your own language. It offers multi-category search with breadcrumb-filtered results, easy photo gallery management with drag-drop sorting of images. You can also build your own multi-category search section menu with custom labels-choices and unlimited dropdown menus. Price: $39.95 essential | $69.95 standard | $99.95 premium View Demo Download Decasa It has custom search panel that lets your user easily browse your properties by keyword search or category select drop downs. It offers the property exposé, which is a user-friendly overview over the most important details of each real estate object. You can easily add this data through a post settings meta box on the post edit screen. You can easily create a real estate image gallery. Its theme options panel makes it easy to make the basic theme settings. It supports the new WordPress post thumbnail feature. When uploading an image file the theme will automatically create all the necessary image size. You can also create your own custom menu easily and fast with drag and drop without touching any code. Price: 39 € View Demo Download RealtorPress A real estate premium WordPress theme from PremiumPress. Versatile WordPress Theme that can be used by individual agents or real estate companies. The theme allows you to easily add property listings via the custom backend admin area or import CSV spreadsheets. It features customisable search options, Google maps integration, real estate data custom field creator, image management tools and more. Price: $79 | Premium Collection: $259 (all PremiumPress themes) View Demo Download Related posts:21+ WordPress Photo Blog & Portfolio Themes 14+ WordPress Portfolio Themes Professional WordPress Business Themes

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  • How to Achieve Real-Time Data Protection and Availabilty....For Real

    - by JoeMeeks
    There is a class of business and mission critical applications where downtime or data loss have substantial negative impact on revenue, customer service, reputation, cost, etc. Because the Oracle Database is used extensively to provide reliable performance and availability for this class of application, it also provides an integrated set of capabilities for real-time data protection and availability. Active Data Guard, depicted in the figure below, is the cornerstone for accomplishing these objectives because it provides the absolute best real-time data protection and availability for the Oracle Database. This is a bold statement, but it is supported by the facts. It isn’t so much that alternative solutions are bad, it’s just that their architectures prevent them from achieving the same levels of data protection, availability, simplicity, and asset utilization provided by Active Data Guard. Let’s explore further. Backups are the most popular method used to protect data and are an essential best practice for every database. Not surprisingly, Oracle Recovery Manager (RMAN) is one of the most commonly used features of the Oracle Database. But comparing Active Data Guard to backups is like comparing apples to motorcycles. Active Data Guard uses a hot (open read-only), synchronized copy of the production database to provide real-time data protection and HA. In contrast, a restore from backup takes time and often has many moving parts - people, processes, software and systems – that can create a level of uncertainty during an outage that critical applications can’t afford. This is why backups play a secondary role for your most critical databases by complementing real-time solutions that can provide both data protection and availability. Before Data Guard, enterprises used storage remote-mirroring for real-time data protection and availability. Remote-mirroring is a sophisticated storage technology promoted as a generic infrastructure solution that makes a simple promise – whatever is written to a primary volume will also be written to the mirrored volume at a remote site. Keeping this promise is also what causes data loss and downtime when the data written to primary volumes is corrupt – the same corruption is faithfully mirrored to the remote volume making both copies unusable. This happens because remote-mirroring is a generic process. It has no  intrinsic knowledge of Oracle data structures to enable advanced protection, nor can it perform independent Oracle validation BEFORE changes are applied to the remote copy. There is also nothing to prevent human error (e.g. a storage admin accidentally deleting critical files) from also impacting the remote mirrored copy. Remote-mirroring tricks users by creating a false impression that there are two separate copies of the Oracle Database. In truth; while remote-mirroring maintains two copies of the data on different volumes, both are part of a single closely coupled system. Not only will remote-mirroring propagate corruptions and administrative errors, but the changes applied to the mirrored volume are a result of the same Oracle code path that applied the change to the source volume. There is no isolation, either from a storage mirroring perspective or from an Oracle software perspective.  Bottom line, storage remote-mirroring lacks both the smarts and isolation level necessary to provide true data protection. Active Data Guard offers much more than storage remote-mirroring when your objective is protecting your enterprise from downtime and data loss. Like remote-mirroring, an Active Data Guard replica is an exact block for block copy of the primary. Unlike remote-mirroring, an Active Data Guard replica is NOT a tightly coupled copy of the source volumes - it is a completely independent Oracle Database. Active Data Guard’s inherent knowledge of Oracle data block and redo structures enables a separate Oracle Database using a different Oracle code path than the primary to use the full complement of Oracle data validation methods before changes are applied to the synchronized copy. These include: physical check sum, logical intra-block checking, lost write validation, and automatic block repair. The figure below illustrates the stark difference between the knowledge that remote-mirroring can discern from an Oracle data block and what Active Data Guard can discern. An Active Data Guard standby also provides a range of additional services enabled by the fact that it is a running Oracle Database - not just a mirrored copy of data files. An Active Data Guard standby database can be open read-only while it is synchronizing with the primary. This enables read-only workloads to be offloaded from the primary system and run on the active standby - boosting performance by utilizing all assets. An Active Data Guard standby can also be used to implement many types of system and database maintenance in rolling fashion. Maintenance and upgrades are first implemented on the standby while production runs unaffected at the primary. After the primary and standby are synchronized and all changes have been validated, the production workload is quickly switched to the standby. The only downtime is the time required for user connections to transfer from one system to the next. These capabilities further expand the expectations of availability offered by a data protection solution beyond what is possible to do using storage remote-mirroring. So don’t be fooled by appearances.  Storage remote-mirroring and Active Data Guard replication may look similar on the surface - but the devil is in the details. Only Active Data Guard has the smarts, the isolation, and the simplicity, to provide the best data protection and availability for the Oracle Database. Stay tuned for future blog posts that dive into the many differences between storage remote-mirroring and Active Data Guard along the dimensions of data protection, data availability, cost, asset utilization and return on investment. For additional information on Active Data Guard, see: Active Data Guard Technical White Paper Active Data Guard vs Storage Remote-Mirroring Active Data Guard Home Page on the Oracle Technology Network

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  • Data Quality Through Data Governance

    Data Quality Governance Data quality is very important to every organization, bad data cost an organization time, money, and resources that could be prevented if the proper governance was put in to place.  Data Governance Program Criteria: Support from Executive Management and all Business Units Data Stewardship Program  Cross Functional Team of Data Stewards Data Governance Committee Quality Structured Data It should go without saying but any successful project in today’s business world must get buy in from executive management and all stakeholders involved with the project. If management does not fully support a project because they see it is in there and the company’s best interest then they will remove/eliminate funding, resources and allocated time to work on the project. In essence they can render a project dead until it is official killed by the business. In addition, buy in from stake holders is also very important because they can cause delays increased spending in time, money and resources because they do not support a project. Data Stewardship programs are administered by a data steward manager who primary focus is to support, train and manage a cross functional data stewards team. A cross functional team of data stewards are pulled from various departments act to ensure that all systems work to ensure that an organization’s goals are achieved. Typically, data stewards are subject matter experts that act as mediators between their respective departments and IT. Data Quality Procedures Data Governance Committees are composed of data stewards, Upper management, IT Leadership and various subject matter experts depending on a company. The primary goal of this committee is to define strategic goals, coordinate activities, set data standards and offer data guidelines for the business. Data Quality Policies In 1997, Claudia Imhoff defined a Data Stewardship’s responsibility as to approve business naming standards, develop consistent data definitions, determine data aliases, develop standard calculations and derivations, document the business rules of the corporation, monitor the quality of the data in the data warehouse, define security requirements, and so forth. She further explains data stewards responsible for creating and enforcing polices on the following but not limited to issues. Resolving Data Integration Issues Determining Data Security Documenting Data Definitions, Calculations, Summarizations, etc. Maintaining/Updating Business Rules Analyzing and Improving Data Quality

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  • SQL SERVER – Advanced Data Quality Services with Melissa Data – Azure Data Market

    - by pinaldave
    There has been much fanfare over the new SQL Server 2012, and especially around its new companion product Data Quality Services (DQS). Among the many new features is the addition of this integrated knowledge-driven product that enables data stewards everywhere to profile, match, and cleanse data. In addition to the homegrown rules that data stewards can design and implement, there are also connectors to third party providers that are hosted in the Azure Datamarket marketplace.  In this review, I leverage SQL Server 2012 Data Quality Services, and proceed to subscribe to a third party data cleansing product through the Datamarket to showcase this unique capability. Crucial Questions For the purposes of the review, I used a database I had in an Excel spreadsheet with name and address information. Upon a cursory inspection, there are miscellaneous problems with these records; some addresses are missing ZIP codes, others missing a city, and some records are slightly misspelled or have unparsed suites. With DQS, I can easily add a knowledge base to help standardize my values, such as for state abbreviations. But how do I know that my address is correct? And if my address is not correct, what should it be corrected to? The answer lies in a third party knowledge base by the acknowledged USPS certified address accuracy experts at Melissa Data. Reference Data Services Within DQS there is a handy feature to actually add reference data from many different third-party Reference Data Services (RDS) vendors. DQS simplifies the processes of cleansing, standardizing, and enriching data through custom rules and through service providers from the Azure Datamarket. A quick jump over to the Datamarket site shows me that there are a handful of providers that offer data directly through Data Quality Services. Upon subscribing to these services, one can attach a DQS domain or composite domain (fields in a record) to a reference data service provider, and begin using it to cleanse, standardize, and enrich that data. Besides what I am looking for (address correction and enrichment), it is possible to subscribe to a host of other services including geocoding, IP address reference, phone checking and enrichment, as well as name parsing, standardization, and genderization.  These capabilities extend the data quality that DQS has natively by quite a bit. For my current address correction review, I needed to first sign up to a reference data provider on the Azure Data Market site. For this example, I used Melissa Data’s Address Check Service. They offer free one-month trials, so if you wish to follow along, or need to add address quality to your own data, I encourage you to sign up with them. Once I subscribed to the desired Reference Data Provider, I navigated my browser to the Account Keys within My Account to view the generated account key, which I then inserted into the DQS Client – Configuration under the Administration area. Step by Step to Guide That was all it took to hook in the subscribed provider -Melissa Data- directly to my DQS Client. The next step was for me to attach and map in my Reference Data from the newly acquired reference data provider, to a domain in my knowledge base. On the DQS Client home screen, I selected “New Knowledge Base” under Knowledge Base Management on the left-hand side of the home screen. Under New Knowledge Base, I typed a Name and description of my new knowledge base, then proceeded to the Domain Management screen. Here I established a series of domains (fields) and then linked them all together as a composite domain (record set). Using the Create Domain button, I created the following domains according to the fields in my incoming data: Name Address Suite City State Zip I added a Suite column in my domain because Melissa Data has the ability to return missing Suites based on last name or company. And that’s a great benefit of using these third party providers, as they have data that the data steward would not normally have access to. The bottom line is, with these third party data providers, I can actually improve my data. Next, I created a composite domain (fulladdress) and added the (field) domains into the composite domain. This essentially groups our address fields together in a record to facilitate the full address cleansing they perform. I then selected my newly created composite domain and under the Reference Data tab, added my third party reference data provider –Melissa Data’s Address Check- and mapped in each domain that I had to the provider’s Schema. Now that my composite domain has been married to the Reference Data service, I can take the newly published knowledge base and create a project to cleanse and enrich my data. My next task was to create a new Data Quality project, mapping in my data source and matching it to the appropriate domain column, and then kick off the verification process. It took just a few minutes with some progress indicators indicating that it was working. When the process concluded, there was a helpful set of tabs that place the response records into categories: suggested; new; invalid; corrected (automatically); and correct. Accepting the suggestions provided by  Melissa Data allowed me to clean up all the records and flag the invalid ones. It is very apparent that DQS makes address data quality simplistic for any IT professional. Final Note As I have shown, DQS makes data quality very easy. Within minutes I was able to set up a data cleansing and enrichment routine within my data quality project, and ensure that my address data was clean, verified, and standardized against real reference data. As reviewed here, it’s easy to see how both SQL Server 2012 and DQS work to take what used to require a highly skilled developer, and empower an average business or database person to consume external services and clean data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology Tagged: DQS

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  • jQuery Time Entry with Time Navigation Keys

    - by Rick Strahl
    So, how do you display time values in your Web applications? Displaying date AND time values in applications is lot less standardized than date display only. While date input has become fairly universal with various date picker controls available, time entry continues to be a bit of a non-standardized. In my own applications I tend to use the jQuery UI DatePicker control for date entries and it works well for that. Here's an example: The date entry portion is well defined and it makes perfect sense to have a calendar pop up so you can pick a date from a rich UI when necessary. However, time values are much less obvious when it comes to displaying a UI or even just making time entries more useful. There are a slew of time picker controls available but other than adding some visual glitz, they are not really making time entry any easier. Part of the reason for this is that time entry is usually pretty simple. Clicking on a dropdown of any sort and selecting a value from a long scrolling list tends to take more user interaction than just typing 5 characters (7 if am/pm is used). Keystrokes can make Time Entry easier Time entry maybe pretty simple, but I find that adding a few hotkeys to handle date navigation can make it much easier. Specifically it'd be nice to have keys to: Jump to the current time (Now) Increase/decrease minutes Increase/decrease hours The timeKeys jQuery PlugIn Some time ago I created a small plugin to handle this scenario. It's non-visual other than tooltip that pops up when you press ? to display the hotkeys that are available: Try it Online The keys loosely follow the ancient Quicken convention of using the first and last letters of what you're increasing decreasing (ie. H to decrease, R to increase hours and + and - for the base unit or minutes here). All navigation happens via the keystrokes shown above, so it's all non-visual, which I think is the most efficient way to deal with dates. To hook up the plug-in, start with the textbox:<input type="text" id="txtTime" name="txtTime" value="12:05 pm" title="press ? for time options" /> Note the title which might be useful to alert people using the field that additional functionality is available. To hook up the plugin code is as simple as:$("#txtTime").timeKeys(); You essentially tie the plugin to any text box control. OptionsThe syntax for timeKeys allows for an options map parameter:$(selector).timeKeys(options); Options are passed as a parameter map object which can have the following properties: timeFormatYou can pass in a format string that allows you to format the date. The default is "hh:mm t" which is US time format that shows a 12 hour clock with am/pm. Alternately you can pass in "HH:mm" which uses 24 hour time. HH, hh, mm and t are translated in the format string - you can arrange the format as you see fit. callbackYou can also specify a callback function that is called when the date value has been set. This allows you to either re-format the date or perform post processing (such as displaying highlight if it's after a certain hour for example). Here's another example that uses both options:$("#txtTime").timeKeys({ timeFormat: "HH:mm", callback: function (time) { showStatus("new time is: " + time.toString() + " " + $(this).val() ); } }); The plugin code itself is fairly simple. It hooks the keydown event and checks for the various keys that affect time navigation which is straight forward. The bulk of the code however deals with parsing the time value and formatting the output using a Time class that implements parsing, formatting and time navigation methods. Here's the code for the timeKeys jQuery plug-in:/// <reference path="jquery.js" /> /// <reference path="ww.jquery.js" /> (function ($) { $.fn.timeKeys = function (options) { /// <summary> /// Attaches a set of hotkeys to time fields /// + Add minute - subtract minute /// H Subtract Hour R Add houR /// ? Show keys /// </summary> /// <param name="options" type="object"> /// Options: /// timeFormat: "hh:mm t" by default HH:mm alternate /// callback: callback handler after time assignment /// </param> /// <example> /// var proxy = new ServiceProxy("JsonStockService.svc/"); /// proxy.invoke("GetStockQuote",{symbol:"msft"},function(quote) { alert(result.LastPrice); },onPageError); ///</example> if (this.length < 1) return this; var opt = { timeFormat: "hh:mm t", callback: null } $.extend(opt, options); return this.keydown(function (e) { var $el = $(this); var time = new Time($el.val()); //alert($(this).val() + " " + time.toString() + " " + time.date.toString()); switch (e.keyCode) { case 78: // [N]ow time = new Time(new Date()); break; case 109: case 189: // - time.addMinutes(-1); break; case 107: case 187: // + time.addMinutes(1); break; case 72: //H time.addHours(-1); break; case 82: //R time.addHours(1); break; case 191: // ? if (e.shiftKey) $(this).tooltip("<b>N</b> Now<br/><b>+</b> add minute<br /><b>-</b> subtract minute<br /><b>H</b> Subtract Hour<br /><b>R</b> add hour", 4000, { isHtml: true }); return false; default: return true; } $el.val(time.toString(opt.timeFormat)); if (opt.callback) { // call async and set context in this element setTimeout(function () { opt.callback.call($el.get(0), time) }, 1); } return false; }); } Time = function (time, format) { /// <summary> /// Time object that can parse and format /// a time values. /// </summary> /// <param name="time" type="object"> /// A time value as a string (12:15pm or 23:01), a Date object /// or time value. /// /// </param> /// <param name="format" type="string"> /// Time format string: /// HH:mm (23:01) /// hh:mm t (11:01 pm) /// </param> /// <example> /// var time = new Time( new Date()); /// time.addHours(5); /// time.addMinutes(10); /// var s = time.toString(); /// /// var time2 = new Time(s); // parse with constructor /// var t = time2.parse("10:15 pm"); // parse with .parse() method /// alert( t.hours + " " + t.mins + " " + t.ampm + " " + t.hours25) ///</example> var _I = this; this.date = new Date(); this.timeFormat = "hh:mm t"; if (format) this.timeFormat = format; this.parse = function (time) { /// <summary> /// Parses time value from a Date object, or string in format of: /// 12:12pm or 23:01 /// </summary> /// <param name="time" type="any"> /// A time value as a string (12:15pm or 23:01), a Date object /// or time value. /// /// </param> if (!time) return null; // Date if (time.getDate) { var t = {}; var d = time; t.hours24 = d.getHours(); t.mins = d.getMinutes(); t.ampm = "am"; if (t.hours24 > 11) { t.ampm = "pm"; if (t.hours24 > 12) t.hours = t.hours24 - 12; } time = t; } if (typeof (time) == "string") { var parts = time.split(":"); if (parts < 2) return null; var time = {}; time.hours = parts[0] * 1; time.hours24 = time.hours; time.mins = parts[1].toLowerCase(); if (time.mins.indexOf("am") > -1) { time.ampm = "am"; time.mins = time.mins.replace("am", ""); if (time.hours == 12) time.hours24 = 0; } else if (time.mins.indexOf("pm") > -1) { time.ampm = "pm"; time.mins = time.mins.replace("pm", ""); if (time.hours < 12) time.hours24 = time.hours + 12; } time.mins = time.mins * 1; } _I.date.setMinutes(time.mins); _I.date.setHours(time.hours24); return time; }; this.addMinutes = function (mins) { /// <summary> /// adds minutes to the internally stored time value. /// </summary> /// <param name="mins" type="number"> /// number of minutes to add to the date /// </param> _I.date.setMinutes(_I.date.getMinutes() + mins); } this.addHours = function (hours) { /// <summary> /// adds hours the internally stored time value. /// </summary> /// <param name="hours" type="number"> /// number of hours to add to the date /// </param> _I.date.setHours(_I.date.getHours() + hours); } this.getTime = function () { /// <summary> /// returns a time structure from the currently /// stored time value. /// Properties: hours, hours24, mins, ampm /// </summary> return new Time(new Date()); h } this.toString = function (format) { /// <summary> /// returns a short time string for the internal date /// formats: 12:12 pm or 23:12 /// </summary> /// <param name="format" type="string"> /// optional format string for date /// HH:mm, hh:mm t /// </param> if (!format) format = _I.timeFormat; var hours = _I.date.getHours(); if (format.indexOf("t") > -1) { if (hours > 11) format = format.replace("t", "pm") else format = format.replace("t", "am") } if (format.indexOf("HH") > -1) format = format.replace("HH", hours.toString().padL(2, "0")); if (format.indexOf("hh") > -1) { if (hours > 12) hours -= 12; if (hours == 0) hours = 12; format = format.replace("hh", hours.toString().padL(2, "0")); } if (format.indexOf("mm") > -1) format = format.replace("mm", _I.date.getMinutes().toString().padL(2, "0")); return format; } // construction if (time) this.time = this.parse(time); } String.prototype.padL = function (width, pad) { if (!width || width < 1) return this; if (!pad) pad = " "; var length = width - this.length if (length < 1) return this.substr(0, width); return (String.repeat(pad, length) + this).substr(0, width); } String.repeat = function (chr, count) { var str = ""; for (var x = 0; x < count; x++) { str += chr }; return str; } })(jQuery); The plugin consists of the actual plugin and the Time class which handles parsing and formatting of the time value via the .parse() and .toString() methods. Code like this always ends up taking up more effort than the actual logic unfortunately. There are libraries out there that can handle this like datejs or even ww.jquery.js (which is what I use) but to keep the code self contained for this post the plugin doesn't rely on external code. There's one optional exception: The code as is has one dependency on ww.jquery.js  for the tooltip plugin that provides the small popup for all the hotkeys available. You can replace that code with some other mechanism to display hotkeys or simply remove it since that behavior is optional. While we're at it: A jQuery dateKeys plugIn Although date entry tends to be much better served with drop down calendars to pick dates from, often it's also easier to pick dates using a few simple hotkeys. Navigation that uses + - for days and M and H for MontH navigation, Y and R for YeaR navigation are a quick way to enter dates without having to resort to using a mouse and clicking around to what you want to find. Note that this plugin does have a dependency on ww.jquery.js for the date formatting functionality.$.fn.dateKeys = function (options) { /// <summary> /// Attaches a set of hotkeys to date 'fields' /// + Add day - subtract day /// M Subtract Month H Add montH /// Y Subtract Year R Add yeaR /// ? Show keys /// </summary> /// <param name="options" type="object"> /// Options: /// dateFormat: "MM/dd/yyyy" by default "MMM dd, yyyy /// callback: callback handler after date assignment /// </param> /// <example> /// var proxy = new ServiceProxy("JsonStockService.svc/"); /// proxy.invoke("GetStockQuote",{symbol:"msft"},function(quote) { alert(result.LastPrice); },onPageError); ///</example> if (this.length < 1) return this; var opt = { dateFormat: "MM/dd/yyyy", callback: null }; $.extend(opt, options); return this.keydown(function (e) { var $el = $(this); var d = new Date($el.val()); if (!d) d = new Date(1900, 0, 1, 1, 1); var month = d.getMonth(); var year = d.getFullYear(); var day = d.getDate(); switch (e.keyCode) { case 84: // [T]oday d = new Date(); break; case 109: case 189: d = new Date(year, month, day - 1); break; case 107: case 187: d = new Date(year, month, day + 1); break; case 77: //M d = new Date(year, month - 1, day); break; case 72: //H d = new Date(year, month + 1, day); break; case 191: // ? if (e.shiftKey) $el.tooltip("<b>T</b> Today<br/><b>+</b> add day<br /><b>-</b> subtract day<br /><b>M</b> subtract Month<br /><b>H</b> add montH<br/><b>Y</b> subtract Year<br/><b>R</b> add yeaR", 5000, { isHtml: true }); return false; default: return true; } $el.val(d.formatDate(opt.dateFormat)); if (opt.callback) // call async setTimeout(function () { opt.callback.call($el.get(0),d); }, 10); return false; }); } The logic for this plugin is similar to the timeKeys plugin, but it's a little simpler as it tries to directly parse the date value from a string via new Date(inputString). As mentioned it also uses a helper function from ww.jquery.js to format dates which removes the logic to perform date formatting manually which again reduces the size of the code. And the Key is… I've been using both of these plugins in combination with the jQuery UI datepicker for datetime values and I've found that I rarely actually pop up the date picker any more. It's just so much more efficient to use the hotkeys to navigate dates. It's still nice to have the picker around though - it provides the expected behavior for date entry. For time values however I can't justify the UI overhead of a picker that doesn't make it any easier to pick a time. Most people know how to type in a time value and if they want shortcuts keystrokes easily beat out any pop up UI. Hopefully you'll find this as useful as I have found it for my code. Resources Online Sample Download Sample Project © Rick Strahl, West Wind Technologies, 2005-2011Posted in jQuery  HTML   Tweet (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Big Data – Basics of Big Data Architecture – Day 4 of 21

    - by Pinal Dave
    In yesterday’s blog post we understood how Big Data evolution happened. Today we will understand basics of the Big Data Architecture. Big Data Cycle Just like every other database related applications, bit data project have its development cycle. Though three Vs (link) for sure plays an important role in deciding the architecture of the Big Data projects. Just like every other project Big Data project also goes to similar phases of the data capturing, transforming, integrating, analyzing and building actionable reporting on the top of  the data. While the process looks almost same but due to the nature of the data the architecture is often totally different. Here are few of the question which everyone should ask before going ahead with Big Data architecture. Questions to Ask How big is your total database? What is your requirement of the reporting in terms of timereal time, semi real time or at frequent interval? How important is the data availability and what is the plan for disaster recovery? What are the plans for network and physical security of the data? What platform will be the driving force behind data and what are different service level agreements for the infrastructure? This are just basic questions but based on your application and business need you should come up with the custom list of the question to ask. As I mentioned earlier this question may look quite simple but the answer will not be simple. When we are talking about Big Data implementation there are many other important aspects which we have to consider when we decide to go for the architecture. Building Blocks of Big Data Architecture It is absolutely impossible to discuss and nail down the most optimal architecture for any Big Data Solution in a single blog post, however, we can discuss the basic building blocks of big data architecture. Here is the image which I have built to explain how the building blocks of the Big Data architecture works. Above image gives good overview of how in Big Data Architecture various components are associated with each other. In Big Data various different data sources are part of the architecture hence extract, transform and integration are one of the most essential layers of the architecture. Most of the data is stored in relational as well as non relational data marts and data warehousing solutions. As per the business need various data are processed as well converted to proper reports and visualizations for end users. Just like software the hardware is almost the most important part of the Big Data Architecture. In the big data architecture hardware infrastructure is extremely important and failure over instances as well as redundant physical infrastructure is usually implemented. NoSQL in Data Management NoSQL is a very famous buzz word and it really means Not Relational SQL or Not Only SQL. This is because in Big Data Architecture the data is in any format. It can be unstructured, relational or in any other format or from any other data source. To bring all the data together relational technology is not enough, hence new tools, architecture and other algorithms are invented which takes care of all the kind of data. This is collectively called NoSQL. Tomorrow Next four days we will answer the Buzz Words – Hadoop. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Big Data – Evolution of Big Data – Day 3 of 21

    - by Pinal Dave
    In yesterday’s blog post we answered what is the Big Data. Today we will understand why and how the evolution of Big Data has happened. Though the answer is very simple, I would like to tell it in the form of a history lesson. Data in Flat File In earlier days data was stored in the flat file and there was no structure in the flat file.  If any data has to be retrieved from the flat file it was a project by itself. There was no possibility of retrieving the data efficiently and data integrity has been just a term discussed without any modeling or structure around. Database residing in the flat file had more issues than we would like to discuss in today’s world. It was more like a nightmare when there was any data processing involved in the application. Though, applications developed at that time were also not that advanced the need of the data was always there and there was always need of proper data management. Edgar F Codd and 12 Rules Edgar Frank Codd was a British computer scientist who, while working for IBM, invented the relational model for database management, the theoretical basis for relational databases. He presented 12 rules for the Relational Database and suddenly the chaotic world of the database seems to see discipline in the rules. Relational Database was a promising land for all the unstructured database users. Relational Database brought into the relationship between data as well improved the performance of the data retrieval. Database world had immediately seen a major transformation and every single vendors and database users suddenly started to adopt the relational database models. Relational Database Management Systems Since Edgar F Codd proposed 12 rules for the RBDMS there were many different vendors who started them to build applications and tools to support the relationship between database. This was indeed a learning curve for many of the developer who had never worked before with the modeling of the database. However, as time passed by pretty much everybody accepted the relationship of the database and started to evolve product which performs its best with the boundaries of the RDBMS concepts. This was the best era for the databases and it gave the world extreme experts as well as some of the best products. The Entity Relationship model was also evolved at the same time. In software engineering, an Entity–relationship model (ER model) is a data model for describing a database in an abstract way. Enormous Data Growth Well, everything was going fine with the RDBMS in the database world. As there were no major challenges the adoption of the RDBMS applications and tools was pretty much universal. There was a race at times to make the developer’s life much easier with the RDBMS management tools. Due to the extreme popularity and easy to use system pretty much every data was stored in the RDBMS system. New age applications were built and social media took the world by the storm. Every organizations was feeling pressure to provide the best experience for their users based the data they had with them. While this was all going on at the same time data was growing pretty much every organization and application. Data Warehousing The enormous data growth now presented a big challenge for the organizations who wanted to build intelligent systems based on the data and provide near real time superior user experience to their customers. Various organizations immediately start building data warehousing solutions where the data was stored and processed. The trend of the business intelligence becomes the need of everyday. Data was received from the transaction system and overnight was processed to build intelligent reports from it. Though this is a great solution it has its own set of challenges. The relational database model and data warehousing concepts are all built with keeping traditional relational database modeling in the mind and it still has many challenges when unstructured data was present. Interesting Challenge Every organization had expertise to manage structured data but the world had already changed to unstructured data. There was intelligence in the videos, photos, SMS, text, social media messages and various other data sources. All of these needed to now bring to a single platform and build a uniform system which does what businesses need. The way we do business has also been changed. There was a time when user only got the features what technology supported, however, now users ask for the feature and technology is built to support the same. The need of the real time intelligence from the fast paced data flow is now becoming a necessity. Large amount (Volume) of difference (Variety) of high speed data (Velocity) is the properties of the data. The traditional database system has limits to resolve the challenges this new kind of the data presents. Hence the need of the Big Data Science. We need innovation in how we handle and manage data. We need creative ways to capture data and present to users. Big Data is Reality! Tomorrow In tomorrow’s blog post we will try to answer discuss Basics of Big Data Architecture. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Working with Temporal Data in SQL Server

    - by Dejan Sarka
    My third Pluralsight course, Working with Temporal Data in SQL Server, is published. I am really proud on the second part of the course, where I discuss optimization of temporal queries. This was a nearly impossible task for decades. First solutions appeared only lately. I present all together six solutions (and one more that is not a solution), and I invented four of them. http://pluralsight.com/training/Courses/TableOfContents/working-with-temporal-data-sql-server

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  • New Communications Industry Data Model with "Factory Installed" Predictive Analytics using Oracle Da

    - by charlie.berger
    Oracle Introduces Oracle Communications Data Model to Provide Actionable Insight for Communications Service Providers   We've integrated pre-installed analytical methodologies with the new Oracle Communications Data Model to deliver automated, simple, yet powerful predictive analytics solutions for customers.  Churn, sentiment analysis, identifying customer segments - all things that can be anticipated and hence, preconcieved and implemented inside an applications.  Read on for more information! TM Forum Management World, Nice, France - 18 May 2010 News Facts To help communications service providers (CSPs) manage and analyze rapidly growing data volumes cost effectively, Oracle today introduced the Oracle Communications Data Model. With the Oracle Communications Data Model, CSPs can achieve rapid time to value by quickly implementing a standards-based enterprise data warehouse that features communications industry-specific reporting, analytics and data mining. The combination of the Oracle Communications Data Model, Oracle Exadata and the Oracle Business Intelligence (BI) Foundation represents the most comprehensive data warehouse and BI solution for the communications industry. Also announced today, Hong Kong Broadband Network enhanced their data warehouse system, going live on Oracle Communications Data Model in three months. The leading provider increased its subscriber base by 37 percent in six months and reduced customer churn to less than one percent. Product Details Oracle Communications Data Model provides industry-specific schema and embedded analytics that address key areas such as customer management, marketing segmentation, product development and network health. CSPs can efficiently capture and monitor critical data and transform it into actionable information to support development and delivery of next-generation services using: More than 1,300 industry-specific measurements and key performance indicators (KPIs) such as network reliability statistics, provisioning metrics and customer churn propensity. Embedded OLAP cubes for extremely fast dimensional analysis of business information. Embedded data mining models for sophisticated trending and predictive analysis. Support for multiple lines of business, such as cable, mobile, wireline and Internet, which can be easily extended to support future requirements. With Oracle Communications Data Model, CSPs can jump start the implementation of a communications data warehouse in line with communications-industry standards including the TM Forum Information Framework (SID), formerly known as the Shared Information Model. Oracle Communications Data Model is optimized for any Oracle Database 11g platform, including Oracle Exadata, which can improve call data record query performance by 10x or more. Supporting Quotes "Oracle Communications Data Model covers a wide range of business areas that are relevant to modern communications service providers and is a comprehensive solution - with its data model and pre-packaged templates including BI dashboards, KPIs, OLAP cubes and mining models. It helps us save a great deal of time in building and implementing a customized data warehouse and enables us to leverage the advanced analytics quickly and more effectively," said Yasuki Hayashi, executive manager, NTT Comware Corporation. "Data volumes will only continue to grow as communications service providers expand next-generation networks, deploy new services and adopt new business models. They will increasingly need efficient, reliable data warehouses to capture key insights on data such as customer value, network value and churn probability. With the Oracle Communications Data Model, Oracle has demonstrated its commitment to meeting these needs by delivering data warehouse tools designed to fill communications industry-specific needs," said Elisabeth Rainge, program director, Network Software, IDC. "The TM Forum Conformance Mark provides reassurance to customers seeking standards-based, and therefore, cost-effective and flexible solutions. TM Forum is extremely pleased to work with Oracle to certify its Oracle Communications Data Model solution. Upon successful completion, this certification will represent the broadest and most complete implementation of the TM Forum Information Framework to date, with more than 130 aggregate business entities," said Keith Willetts, chairman and chief executive officer, TM Forum. Supporting Resources Oracle Communications Oracle Communications Data Model Data Sheet Oracle Communications Data Model Podcast Oracle Data Warehousing Oracle Communications on YouTube Oracle Communications on Delicious Oracle Communications on Facebook Oracle Communications on Twitter Oracle Communications on LinkedIn Oracle Database on Twitter The Data Warehouse Insider Blog

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  • How to change system time or force a time sync

    - by cpury
    My laptop is probably running out of CMOS battery, I know I have to fix it soon, but until then, this very annoying issue keeps me from using it. Scenario: My system clock is reset to 15/12/08 11:00 AM every time I turn on my computer. This has all sorts of side-effects, one of the more annoying being that I can't log into my gmail. At first I just waited for a time sync to happen, as I have that activated and all. It never happened. I googled and didn't find any way of enforcing a time sync, which I found very strange. Is there really none? Setting the time and date by hand is also a problem. For my 12.10 installation, the time & date settings are bugged. I remember it being for my last, older installation as well, though. Of course the easiest way should be to just manually edit the date and time fields by entering a new date. This is possible in theory, but the changes are reverted as soon as the text boxes loose focus. The other way to do it is to click the +-buttons for a long, long time. The first time I did that, the changes weren't stored either. I found out that afterwards I have to switch from manual to internet-sync mode and wait ~5 seconds until the in the top left corner of my system the new time is shown, or otherwise it won't have effect. So a nice solution would be one of the following: Setting the time/date by hand, maybe via terminal, so I can just enter the right values. Or, a command that would enforce an immediate time sync, that I can run after booting. I know I have to change the batteries soon, but this is seriously keeping me from working...

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  • Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the analytics in Big Data Story. In this article we will understand how to become a Data Scientist for Big Data Story. Data Scientist is a new buzz word, everyone seems to be wanting to become Data Scientist. Let us go over a few key topics related to Data Scientist in this blog post. First of all we will understand what is a Data Scientist. In the new world of Big Data, I see pretty much everyone wants to become Data Scientist and there are lots of people I have already met who claims that they are Data Scientist. When I ask what is their role, I have got a wide variety of answers. What is Data Scientist? Data scientists are the experts who understand various aspects of the business and know how to strategies data to achieve the business goals. They should have a solid foundation of various data algorithms, modeling and statistics methodology. What do Data Scientists do? Data scientists understand the data very well. They just go beyond the regular data algorithms and builds interesting trends from available data. They innovate and resurrect the entire new meaning from the existing data. They are artists in disguise of computer analyst. They look at the data traditionally as well as explore various new ways to look at the data. Data Scientists do not wait to build their solutions from existing data. They think creatively, they think before the data has entered into the system. Data Scientists are visionary experts who understands the business needs and plan ahead of the time, this tremendously help to build solutions at rapid speed. Besides being data expert, the major quality of Data Scientists is “curiosity”. They always wonder about what more they can get from their existing data and how to get maximum out of future incoming data. Data Scientists do wonders with the data, which goes beyond the job descriptions of Data Analysist or Business Analysist. Skills Required for Data Scientists Here are few of the skills a Data Scientist must have. Expert level skills with statistical tools like SAS, Excel, R etc. Understanding Mathematical Models Hands-on with Visualization Tools like Tableau, PowerPivots, D3. j’s etc. Analytical skills to understand business needs Communication skills On the technology front any Data Scientists should know underlying technologies like (Hadoop, Cloudera) as well as their entire ecosystem (programming language, analysis and visualization tools etc.) . Remember that for becoming a successful Data Scientist one require have par excellent skills, just having a degree in a relevant education field will not suffice. Final Note Data Scientists is indeed very exciting job profile. As per research there are not enough Data Scientists in the world to handle the current data explosion. In near future Data is going to expand exponentially, and the need of the Data Scientists will increase along with it. It is indeed the job one should focus if you like data and science of statistics. Courtesy: emc Tomorrow In tomorrow’s blog post we will discuss about various Big Data Learning resources. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • How is time calculation performed by a computer?

    - by Jorge Mendoza
    I need to add a certain feature to a module in a given project regarding time calculation. For this specific case I'm using Java and reading through the documentation of the Date class I found out the time is calculated in milliseconds starting from January 1, 1970, 00:00:00 GMT. I think it's safe to assume there is a similar "starting date" in other languages so I guess the specific implementation in Java doesn't matter. How is the time calculation performed by the computer? How does it know exactly how many milliseconds have passed from that given "starting date and time" to the current date and time?

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  • Unstructured Data - The future of Data Administration

    Some have claimed that there is a problem with the way data is currently managed using the relational paradigm do to the rise of unstructured data in modern business. PCMag.com defines unstructured data as data that does not reside in a fixed location. They further explain that unstructured data refers to data in a free text form that is not bound to any specific structure. With the rise of unstructured data in the form of emails, spread sheets, images and documents the critics have a right to argue that the relational paradigm is not as effective as the object oriented data paradigm in managing this type of data. The relational paradigm relies heavily on structure and relationships in and between items of data. This type of paradigm works best in a relation database management system like Microsoft SQL, MySQL, and Oracle because data is forced to conform to a structure in the form of tables and relations can be derived from the existence of one or more tables. These critics also claim that database administrators have not kept up with reality because their primary focus in regards to data administration deals with structured data and the relational paradigm. The relational paradigm was developed in the 1970’s as a way to improve data management when compared to standard flat files. Little has changed since then, and modern database administrators need to know more than just how to handle structured data. That is why critics claim that today’s data professionals do not have the proper skills in order to store and maintain data for modern systems when compared to the skills of system designers, programmers , software engineers, and data designers  due to the industry trend of object oriented design and development. I think that they are wrong. I do not disagree that the industry is moving toward an object oriented approach to development with the potential to use more of an object oriented approach to data.   However, I think that it is business itself that is limiting database administrators from changing how data is stored because of the potential costs, and impact that might occur by altering any part of stored data. Furthermore, database administrators like all technology workers constantly are trying to improve their technical skills in order to excel in their job, so I think that accusing data professional is not just when the root cause of the lack of innovation is controlled by business, and it is business that will suffer for their inability to keep up with technology. One way for database professionals to better prepare for the future of database management is start working with data in the form of objects and so that they can extract data from the objects so that the stored information within objects can be used in relation to the data stored in a using the relational paradigm. Furthermore, I think the use of pattern matching will increase with the increased use of unstructured data because object can be selected, filtered and altered based on the existence of a pattern found within an object.

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  • Real Time BI in the Real World

    - by tobin.gilman(at)oracle.com
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";} One of my favorite BI offerings from Oracle is a solution called Oracle Real Time Decisions.  Whenever I mention this product in customer meetings, eyes light up.  There are some fascinating examples of customers using it to up-sell, cross-sell, increase customer retention, and reduce risk in real time, with off the charts return on investment. I plan to share some of those stories in a future blog.  In this post however, I want to share some far more common real time analytics use case scenarios that are being addressed with widely deployed Oracle BI and data integration technologies Not all real time BI applications require continuous learning, predictive modeling, and data mining.  Many simply require the ability to integrate, aggregate, and access information that is current (typically within in few minutes or a few seconds).  The use cases are infinite.  A few I've seen: ·         Purchasing agents need to match demand against available inventory ·         Manufacturing planners need to monitor current parts and material against scheduled build plans ·         Airline agents need to match ticket demand against flight schedules, ·         Human resources managers need to track the status of global hiring requisitions against current headcount authorizations...you get the idea. One way of doing this is to run reports or federated queries directly against transactional systems.  That approach can be viable if you only need to access simple data sets on rare occasions.  High volume and complex queries can quickly bog down performance of mission critical transactional systems.  There is an architecturally simple way of solving the problem, and it's being applied by real companies around the world to solve real needs in real time.    Cbeyond is an Atlanta, GA based  provider of voice, data and mobile business applications delivers.  They deliver real time information to its call center agents  as they are interacting with their customers. The data they need resides in production CRM and other transactional systems, but  instead or reporting directly off the those systems, data is first moved to an operational data store (ODS).  Rather than running data intensive, time consuming, and performance degrading batch ETL routines to populate the ODS, Cbeyond uses Oracle Golden Gate software to incrementally capture and move only the changed records from log files of the transactional systems every few minutes.  There is no impact on transactional system performance, and the information needed by call center representatives is up to date.  Oracle Business Intelligence software presents the information to services reps in a rich, visual, and highly interactive format. Avea is similar to Cbeyond.  They are a telecommunications company who integrates billing and customer information in an ODS that is accessed by their call center agents in real time using Oracle Golden Gate and Oracle Business Intelligence.  They've taken it a step further by using the ODS to feed a data warehouse.  The operational data store provides the current information needed by call center agents during "in flight" customer interactions.  The data warehouse is used for more sophisticated analysis of historical data.  For maximum performance, both the ODS and data warehouse run on the Oracle Exadata Database Machine. These are practical illustrations of companies addressing real time reporting and analysis needs using established business intelligence/data warehousing methodologies and tools common to many IT departments.  If real time BI could benefit your organization, you may be already be closer than you thought to having the pieces in place to solving the problem.    Give us a shout if you are interested in learning more or if you have an interesting use or approach to real-time BI.

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  • Developing an analytics's system processing large amounts of data - where to start

    - by Ryan
    Imagine you're writing some sort of Web Analytics system - you're recording raw page hits along with some extra things like tagging cookies etc and then producing stats such as Which pages got most traffic over a time period Which referers sent most traffic Goals completed (goal being a view of a particular page) And more advanced things like which referers sent the most number of vistors who later hit a goal. The naieve way of approaching this would be to throw it in a relational database and run queries over it - but that won't scale. You could pre-calculate everything (have a queue of incoming 'hits' and use to update report tables) - but what if you later change a goal - how could you efficiently re-calculate just the data that would be effected. Obviously this has been done before ;) so any tips on where to start, methods & examples, architecture, technologies etc.

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  • Is there a constant for "end of time"?

    - by Nick Rosencrantz
    For some systems, the time value 9999-12-31 is used as the "end of time" as the end of the time that the computer can calculate. But what if it changes? Wouldn't it be better to define this time as a builtin variable? In C and other programming languages there usually is a variable such as MAX_INT or similar to get the largest value an integer could have. Why is there not a similar function for MAX_TIME i.e. set the variable to the "end of time" which for many systems usually is 9999-12-31. To avoid the problem of hardcoding to a wrong year (9999) could these systems introduce a variable for the "end of time"?

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  • Big Data – Beginning Big Data – Day 1 of 21

    - by Pinal Dave
    What is Big Data? I want to learn Big Data. I have no clue where and how to start learning about it. Does Big Data really means data is big? What are the tools and software I need to know to learn Big Data? I often receive questions which I mentioned above. They are good questions and honestly when we search online, it is hard to find authoritative and authentic answers. I have been working with Big Data and NoSQL for a while and I have decided that I will attempt to discuss this subject over here in the blog. In the next 21 days we will understand what is so big about Big Data. Big Data – Big Thing! Big Data is becoming one of the most talked about technology trends nowadays. The real challenge with the big organization is to get maximum out of the data already available and predict what kind of data to collect in the future. How to take the existing data and make it meaningful that it provides us accurate insight in the past data is one of the key discussion points in many of the executive meetings in organizations. With the explosion of the data the challenge has gone to the next level and now a Big Data is becoming the reality in many organizations. Big Data – A Rubik’s Cube I like to compare big data with the Rubik’s cube. I believe they have many similarities. Just like a Rubik’s cube it has many different solutions. Let us visualize a Rubik’s cube solving challenge where there are many experts participating. If you take five Rubik’s cube and mix up the same way and give it to five different expert to solve it. It is quite possible that all the five people will solve the Rubik’s cube in fractions of the seconds but if you pay attention to the same closely, you will notice that even though the final outcome is the same, the route taken to solve the Rubik’s cube is not the same. Every expert will start at a different place and will try to resolve it with different methods. Some will solve one color first and others will solve another color first. Even though they follow the same kind of algorithm to solve the puzzle they will start and end at a different place and their moves will be different at many occasions. It is  nearly impossible to have a exact same route taken by two experts. Big Market and Multiple Solutions Big Data is exactly like a Rubik’s cube – even though the goal of every organization and expert is same to get maximum out of the data, the route and the starting point are different for each organization and expert. As organizations are evaluating and architecting big data solutions they are also learning the ways and opportunities which are related to Big Data. There is not a single solution to big data as well there is not a single vendor which can claim to know all about Big Data. Honestly, Big Data is too big a concept and there are many players – different architectures, different vendors and different technology. What is Next? In this 31 days series we will be exploring many essential topics related to big data. I do not claim that you will be master of the subject after 31 days but I claim that I will be covering following topics in easy to understand language. Architecture of Big Data Big Data a Management and Implementation Different Technologies – Hadoop, Mapreduce Real World Conversations Best Practices Tomorrow In tomorrow’s blog post we will try to answer one of the very essential questions – What is Big Data? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Reading data from an Entity Framework data model through a WCF Data Service

    - by nikolaosk
    This is going to be the fourth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . Microsoft with .Net 3.0 Framework, introduced WCF. WCF is Microsoft's...(read more)

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  • Big Data&rsquo;s Killer App&hellip;

    - by jean-pierre.dijcks
    Recently Keith spent  some time talking about the cloud on this blog and I will spare you my thoughts on the whole thing. What I do want to write down is something about the Big Data movement and what I think is the killer app for Big Data... Where is this coming from, ok, I confess... I spent 3 days in cloud land at the Cloud Connect conference in Santa Clara and it was quite a lot of fun. One of the nice things at Cloud Connect was that there was a track dedicated to Big Data, which prompted me to some extend to write this post. What is Big Data anyways? The most valuable point made in the Big Data track was that Big Data in itself is not very cool. Doing something with Big Data is what makes all of this cool and interesting to a business user! The other good insight I got was that a lot of people think Big Data means a single gigantic monolithic system holding gazillions of bytes or documents or log files. Well turns out that most people in the Big Data track are talking about a lot of collections of smaller data sets. So rather than thinking "big = monolithic" you should be thinking "big = many data sets". This is more than just theoretical, it is actually relevant when thinking about big data and how to process it. It is important because it means that the platform that stores data will most likely consist out of multiple solutions. You may be storing logs on something like HDFS, you may store your customer information in Oracle and you may store distilled clickstream information in some distilled form in MySQL. The big question you will need to solve is not what lives where, but how to get it all together and get some value out of all that data. NoSQL and MapReduce Nope, sorry, this is not the killer app... and no I'm not saying this because my business card says Oracle and I'm therefore biased. I think language is important, but as with storage I think pragmatic is better. In other words, some questions can be answered with SQL very efficiently, others can be answered with PERL or TCL others with MR. History should teach us that anyone trying to solve a problem will use any and all tools around. For example, most data warehouses (Big Data 1.0?) get a lot of data in flat files. Everyone then runs a bunch of shell scripts to massage or verify those files and then shoves those files into the database. We've even built shell script support into external tables to allow for this. I think the Big Data projects will do the same. Some people will use MapReduce, although I would argue that things like Cascading are more interesting, some people will use Java. Some data is stored on HDFS making Cascading the way to go, some data is stored in Oracle and SQL does do a good job there. As with storage and with history, be pragmatic and use what fits and neither NoSQL nor MR will be the one and only. Also, a language, while important, does in itself not deliver business value. So while cool it is not a killer app... Vertical Behavioral Analytics This is the killer app! And you are now thinking: "what does that mean?" Let's decompose that heading. First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after collecting large volumes of specific data. That all important data is about behavior. What do my customers do? More importantly why do they behave like that? If you can figure that out, you can tailor web sites, stores, products etc. to that behavior and figure out how to be successful. Today's behavior that is somewhat easily tracked is web site clicks, search patterns and all of those things that a web site or web server tracks. that is where the Big Data lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about prediction churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who calls whom. I call you a lot, you switch provider, and I might/will switch too. And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical. The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example). But the gist of it all is that analytics that can predict customer behavior for a specific focused group of people in a specific industry is what makes Big Data interesting. Building a Vertical Behavioral Analysis System Well, that is going to be interesting. I have not seen much going on in that space and if I had to have some criticism on the cloud connect conference it would be the lack of concrete user cases on big data. The telco example, while a step into the vertical behavioral part is not really on big data. It used a sample of data from the customers' data warehouse. One thing I do think, and this is where I think parts of the NoSQL stuff come from, is that we will be doing this analysis where the data is. Over the past 10 years we at Oracle have called this in-database analytics. I guess we were (too) early? Now the entire market is going there including companies like SAS. In-place btw does not mean "no data movement at all", what it means that you will do this on data's permanent home. For SAS that is kind of the current problem. Most of the inputs live in a data warehouse. So why move it into SAS and back? That all worked with 1 TB data warehouses, but when we are looking at 100TB to 500 TB of distilled data... Comments? As it is still early days with these systems, I'm very interested in seeing reactions and thoughts to some of these thoughts...

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