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  • Analytics - Where do my drop offs go?

    - by BadCash
    I have a website set up with Google Analytics (through the Wordpress plugin "Google Analytics for WordPress" by Joos de Valk). When I check out the visitors flow in Google Analytics, it shows something like this: (home) - 43% drop-offs /page-2/ - 10% drop-offs ... etc ... I have also set up events for external links. My main "goal" of the website is to drive traffic to my Android app on Google Play, so I have a couple of different links to that that are all set up as events. Everything seems to be working, my events show up when I go to Content - Events in Google Analytics. However, it seems to me that some percentage of the users that are reported as "drop-offs" in fact have clicked on one of the external links. But there's no info about the reason of those drop-offs in the Visitors flow-chart. I can of course check out each specific event category, event action and set "other" to Content/Page, which (I guess) shows the number of visitors who triggered a specific event on a specific page. It just seems like such a complicated way of going about this! So, is there a way to get a more detailed picture, including events, in the Visitors flow chart? Something like: (home) - 43% drop-offs Event Action: "Google Play"=50%, "Youtube"=10%, (not set)=40%

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  • Classic vs universal and loss of historical data

    - by iss42
    I'm keen to use some of the new features in Google Universal Analytics. I have an old site though that I don't want to lose the historical data for. The comparisons with historical data are interesting for example. However Google doesn't appear to allow you to change a property from the classic code to the new code. Am I missing something? I'm surprised this isn't a bigger issue for many other users.

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  • Show Google Analytics dashboard on my site

    - by Steven
    I have an ASP.NET website set up, and I'm using Google Analytics for page tracking. The only thing I don't like is that I have to go away from my site (to the Google Analytics site) to see the report. Is there any way to show the Google Analytics data on my own site with all the AJAX that they have?

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  • iPhone Analytics

    - by ACBurk
    With the recent changes in the SDK agreement, I am kinda confused if I'm able to put any type of analytics into my app. I don't want to do anything nefarious, just want to see which functionality of my app is getting used the most. I was looking at Google Analytic's mobile sdk to track the different views, just like page views but I have a feeling it is not allowed anymore. Can someone clear up if Google Analytics are still allowed; if not, are any analytics allowed?

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  • Get more than 7 dimensions in google analytics

    - by Paritosh Singh
    I am fetching my data from google analytics core api. I came to know that we can fetch only 7 dimensions using api, But here I need to fetch more than 7 dimensions with correct metrics. Is there anyway (other than using paid google analytics) to fetch more than 7 dmensions with correct metrics from google analytics. If not, then is there any mathematical formula through which we can find intersection of dimensions fetched using 2 different dimensions having one dimension in common. Thanks

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  • Custom Page tagging in Google Analytics

    - by Jason
    I want to have custom page tags, which are different from URLs I have, in my Google Analytics report page. For instance, Actual URL - /news/today_news.php page tag on Google Analytics - /news/today_news.php/Category.News/TodayNews How can I make the custom page tag with Google Analytics API?

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  • Oracle Data Mining a Star Schema: Telco Churn Case Study

    - by charlie.berger
    There is a complete and detailed Telco Churn case study "How to" Blog Series just posted by Ari Mozes, ODM Dev. Manager.  In it, Ari provides detailed guidance in how to leverage various strengths of Oracle Data Mining including the ability to: mine Star Schemas and join tables and views together to obtain a complete 360 degree view of a customer combine transactional data e.g. call record detail (CDR) data, etc. define complex data transformation, model build and model deploy analytical methodologies inside the Database  His blog is posted in a multi-part series.  Below are some opening excerpts for the first 3 blog entries.  This is an excellent resource for any novice to skilled data miner who wants to gain competitive advantage by mining their data inside the Oracle Database.  Many thanks Ari! Mining a Star Schema: Telco Churn Case Study (1 of 3) One of the strengths of Oracle Data Mining is the ability to mine star schemas with minimal effort.  Star schemas are commonly used in relational databases, and they often contain rich data with interesting patterns.  While dimension tables may contain interesting demographics, fact tables will often contain user behavior, such as phone usage or purchase patterns.  Both of these aspects - demographics and usage patterns - can provide insight into behavior.Churn is a critical problem in the telecommunications industry, and companies go to great lengths to reduce the churn of their customer base.  One case study1 describes a telecommunications scenario involving understanding, and identification of, churn, where the underlying data is present in a star schema.  That case study is a good example for demonstrating just how natural it is for Oracle Data Mining to analyze a star schema, so it will be used as the basis for this series of posts...... Mining a Star Schema: Telco Churn Case Study (2 of 3) This post will follow the transformation steps as described in the case study, but will use Oracle SQL as the means for preparing data.  Please see the previous post for background material, including links to the case study and to scripts that can be used to replicate the stages in these posts.1) Handling missing values for call data recordsThe CDR_T table records the number of phone minutes used by a customer per month and per call type (tariff).  For example, the table may contain one record corresponding to the number of peak (call type) minutes in January for a specific customer, and another record associated with international calls in March for the same customer.  This table is likely to be fairly dense (most type-month combinations for a given customer will be present) due to the coarse level of aggregation, but there may be some missing values.  Missing entries may occur for a number of reasons: the customer made no calls of a particular type in a particular month, the customer switched providers during the timeframe, or perhaps there is a data entry problem.  In the first situation, the correct interpretation of a missing entry would be to assume that the number of minutes for the type-month combination is zero.  In the other situations, it is not appropriate to assume zero, but rather derive some representative value to replace the missing entries.  The referenced case study takes the latter approach.  The data is segmented by customer and call type, and within a given customer-call type combination, an average number of minutes is computed and used as a replacement value.In SQL, we need to generate additional rows for the missing entries and populate those rows with appropriate values.  To generate the missing rows, Oracle's partition outer join feature is a perfect fit.  select cust_id, cdre.tariff, cdre.month, minsfrom cdr_t cdr partition by (cust_id) right outer join     (select distinct tariff, month from cdr_t) cdre     on (cdr.month = cdre.month and cdr.tariff = cdre.tariff);   ....... Mining a Star Schema: Telco Churn Case Study (3 of 3) Now that the "difficult" work is complete - preparing the data - we can move to building a predictive model to help identify and understand churn.The case study suggests that separate models be built for different customer segments (high, medium, low, and very low value customer groups).  To reduce the data to a single segment, a filter can be applied: create or replace view churn_data_high asselect * from churn_prep where value_band = 'HIGH'; It is simple to take a quick look at the predictive aspects of the data on a univariate basis.  While this does not capture the more complex multi-variate effects as would occur with the full-blown data mining algorithms, it can give a quick feel as to the predictive aspects of the data as well as validate the data preparation steps.  Oracle Data Mining includes a predictive analytics package which enables quick analysis. begin  dbms_predictive_analytics.explain(   'churn_data_high','churn_m6','expl_churn_tab'); end; /select * from expl_churn_tab where rank <= 5 order by rank; ATTRIBUTE_NAME       ATTRIBUTE_SUBNAME EXPLANATORY_VALUE RANK-------------------- ----------------- ----------------- ----------LOS_BAND                                      .069167052          1MINS_PER_TARIFF_MON  PEAK-5                   .034881648          2REV_PER_MON          REV-5                    .034527798          3DROPPED_CALLS                                 .028110322          4MINS_PER_TARIFF_MON  PEAK-4                   .024698149          5From the above results, it is clear that some predictors do contain information to help identify churn (explanatory value > 0).  The strongest uni-variate predictor of churn appears to be the customer's (binned) length of service.  The second strongest churn indicator appears to be the number of peak minutes used in the most recent month.  The subname column contains the interior piece of the DM_NESTED_NUMERICALS column described in the previous post.  By using the object relational approach, many related predictors are included within a single top-level column. .....   NOTE:  These are just EXCERPTS.  Click here to start reading the Oracle Data Mining a Star Schema: Telco Churn Case Study from the beginning.    

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  • ClickThrough on Google Webmaster Tool and Traffic Source in Google Analytics

    - by Svetlana
    I'm new to SEO and website management, but eager to learn. I manage a newly revamped site and I'm tracking it on Google Analytics and in Google Webmaster tools. The Webmaster tools show that I get about 3200 impressions and 180 click through's a week. Google Analytics show that no traffic comes from search engins, all of the traffic is direct. On average, I get about 60-80 visitors a day, shouldn't Google Analytics show at least a few of those visitors as having come from the search engines?. What does that discrepancy mean? I can't seem to wrap my mind around it... Thank you in advance, Svetlana

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  • Google Analytics on Static Site Hosted by GAE

    - by Cody Hess
    I finagled hosting a static site on Google App Engine at http://corbyhaas.com The HTML when visiting the URL shows some meta information and a frame to the site's actual address: http://cody-static-sites.appspot.com/corbyhaas which has the content. This is done automagically by Google App Engine. I've set up Google Analytics by including their script in my index.html, but the report shows 100% of visits coming from referring site "corbyhaas.com", which is useless information. Has anyone set up Google Analytics for a static GAE site? Is there a setting in my Analytics dashboard I can tweak, or is this a hazard of using Google App Engine for static content? Also, while it's not relevant here (but could be for future sites), does GAE's method of showing only meta information with frames for static data affect SEO?

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  • Google analytics and Adwords showing very different figures

    - by Dave Rook
    In AdWords I have 1 advert running only. The landing page includes a querystring so I can track it. EG, www.mydomain.com/products?source=CPC I also use Google Analytics. For February I have approx 1450 clicks in AdWords. This means, 1450 went to my website. In Google Analytics, according to my landing page, there were only ~850 visits. In Google Analytics, in the Acquisition - All traffic page, it suggests that Google CPC brought 517 visits... I know tracking tools are not 100% reliable but this figure seems to be showing something is very wrong. How can I tell which of the figures is accurate or is this just a limitation of reporting tools?

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  • In-page Google Analytics giving no page views recorded

    - by Nicolo77
    I am trying to use Google In-Page Analytics. The rest of Google Analytics seems to work correctly on my site, but when I go to the new In-page analytics, I get no click appearing. I just get an error saying "There are no pageviews recorded for this page. Try adjusting the date range or select an alternate page." To the left in the content details it tells the number of page views. Do I need to setup something special for In-Page anayltics to work?

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  • Google analytics tracking example.com and www.example.com

    - by danferth
    Our website is set up to direct all traffic for www.example.com to example.com with a line in the htaccess file. With google analytics new in page analytics feature we are thinking of removing the line and allowing people to visit www.example.com as well to play with the new features. My question is this. How will this change affect our analytics data. -will nothing change and we can start using the new feature with our existing data -Are the two domains tracked separately and we will have to start over with www.example .com Any help would be great, as I can find nothing on googles help site covering this. Let me know if you need further explanation.

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  • Rewrite Generic URLs into real URLs on Google Analytics

    - by valdroni
    I have an iPhone app for a forum which also has a limited Google Analytics reporting. This app reports the page views in following generic form: /forum/67 /thread/29036 etc... The numbers above represent forum and thread ID's I am trying to set an Advanced filter, which will rewrite/report the page views in Google Analytics in following form: http://www.mysite.com/forum-67.html http://www.mysite.com/thread-29036.html Can someone please assist me in creating an Advanced Google Analytics filter which will enable me to see URL's so they can be live and send to correct page. Is there another method to achieve what I'm looking for ? Obviously there will be a need for some RegExp matches, but I cannot get around it.

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  • Tack anchor link with Google Analytics

    - by Fredrik
    I have searched for how to track anchor links in analytics, but couldn't get it working. I have this code in the header: <script> (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,'script','//www.google-analytics.com/analytics.js','ga'); ga('_setAllowAnchor', true); ga('create', 'UA-*******-1', '****.com'); ga('send', 'pageview'); </script> And my links looks like this: <a href='#/contact'><span>Contact</span></a> I also tried to use this links: <a href='#/contact' onClick="_gaq.push(['_trackPageview', location.pathname+location.search+location.hash]);"><span>Contact</span></a> Is there any tips on what I can do?

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  • Google Analytics - TOS section pertaining to privacy

    - by Eike Pierstorff
    The Google Analytics terms of service does do not allow to track "data that personally identifies an individual (such as a name, email address or billing information), or other data which can be reasonably linked to such information by Google". Does anybody have first-hand knowledge if this includes user ids which cannot be resolved by Google but can be linked to actual persons via an Analytics Users CRM system (e.g. a CRM linked to Analytics via API access) ? I used to think so, but if that where the case many ecommerce implementations would be illegal (since they store transactions id which can be linked to client's purchases). If anybody has insights about the intended meaning of the paragraph (preferably with a reliable source) it would be great if he/she could share :-)

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  • Why does Google Analytics show false referrals?

    - by Peter Merrill
    Ever since Google revamped their Analytics interface I've been noticing a weird "bug" while viewing the "Real-Time" overview area. From this area I can obviously see live stats of visitors to my website but when I visit my website by opening a new tab (Chrome) and manually visit website the real time stats sometimes look like the image linked below. http://i.stack.imgur.com/mfniY.png Is there any reason why Google is saying that I was referred by Stack Overflow when I'm visiting my website from a new tab? Could this be something do to with how I installed the analytics on my site or could this be an issue with browser cookies? Have anyone else noticed this? I am mainly concerned about this because in the standard reporting area of my Analytics panel my referral stats are getting thrown off every time I visit my own website.

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  • Tracking Search Filter Parameters Using Google Analytics

    - by Petra Barus
    I'm just wondering if there is a way to do this using Google Analytics. Let's say I have a search filter like the one used in Trulia.com There is a text search for the location with other drop-downs for filtering by bedroom, land size, property type (apartments, house) etc. Is there a way to track the filter and obtain a report for some questions like below using Google Analytics What is the most popular property types (house, apartments) for search in New York area? What is the most common maximum price of users who are looking for apartments in San Francisco? (or actually Google Analytics is not suitable for this kind of thing?)

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  • Google analytics shows wrong number of page views, asp.net website

    - by f_karlsson
    Sometimes it can be for example 4500 requests, after a few hours it shows a few thousand less. What is wrong? It looks like analytics corrects itself. I changed from classic to Universal a few months ago, do not know if it has anything to do with this. In masterpage: <script> (function (i, s, o, g, r, a, m) { i['GoogleAnalyticsObject'] = r; i[r] = i[r] || function () { (i[r].q = i[r].q || []).push(arguments) }, i[r].l = 1 * new Date(); a = s.createElement(o), m = s.getElementsByTagName(o)[0]; a.async = 1; a.src = g; m.parentNode.insertBefore(a, m) })(window, document, 'script', '//www.google-analytics.com/analytics.js', 'ga'); ga('create', 'UA-xxxxxxxx-1', 'xxxxx.se'); ga('send', 'pageview'); </script>

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  • When reversing a Google Analytics e-commerce transaction is the per-unit price positive or negative?

    - by Michael Glenn
    Google's own instructions for reversing an e-commerce transaction seem to contradict themselves regarding the unit price. In the instructions it states The item field has a positive per-unit price and a negative quantity. yet, the code sample has a negative per-unit price and negative quantity. _gaq.push(['_addItem', '1234', // order ID - necessary to associate item with transaction 'DD44', // SKU/code - required 'T-Shirt', // product name 'Olive Medium', // category or variation '-11.99', // unit price - required '-1' // quantity - required ]); Which is correct?

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  • Big Data – Buzz Words: What is MapReduce – Day 7 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. 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 – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting 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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  • SQL Rally Pre-Con: Data Warehouse Modeling – Making the Right Choices

    - by Davide Mauri
    As you may have already learned from my old post or Adam’s or Kalen’s posts, there will be two SQL Rally in North Europe. In the Stockholm SQL Rally, with my friend Thomas Kejser, I’ll be delivering a pre-con on Data Warehouse Modeling: Data warehouses play a central role in any BI solution. It's the back end upon which everything in years to come will be created. For this reason, it must be rock solid and yet flexible at the same time. To develop such a data warehouse, you must have a clear idea of its architecture, a thorough understanding of the concepts of Measures and Dimensions, and a proven engineered way to build it so that quality and stability can go hand-in-hand with cost reduction and scalability. In this workshop, Thomas Kejser and Davide Mauri will share all the information they learned since they started working with data warehouses, giving you the guidance and tips you need to start your BI project in the best way possible?avoiding errors, making implementation effective and efficient, paving the way for a winning Agile approach, and helping you define how your team should work so that your BI solution will stand the test of time. You'll learn: Data warehouse architecture and justification Agile methodology Dimensional modeling, including Kimball vs. Inmon, SCD1/SCD2/SCD3, Junk and Degenerate Dimensions, and Huge Dimensions Best practices, naming conventions, and lessons learned Loading the data warehouse, including loading Dimensions, loading Facts (Full Load, Incremental Load, Partitioned Load) Data warehouses and Big Data (Hadoop) Unit testing Tracking historical changes and managing large sizes With all the Self-Service BI hype, Data Warehouse is become more and more central every day, since if everyone will be able to analyze data using self-service tools, it’s better for him/her to rely on correct, uniform and coherent data. Already 50 people registered from the workshop and seats are limited so don’t miss this unique opportunity to attend to this workshop that is really a unique combination of years and years of experience! http://www.sqlpass.org/sqlrally/2013/nordic/Agenda/PreconferenceSeminars.aspx See you there!

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  • Is Google Analytics Part Of Google's Search Engine Algorithm

    - by ub3rst4r
    I was wondering if anyone knows if Google uses the data it receives from Google Analytics to help determine a websites SERP (Search Engine Rank Position). For example, if my website is getting 1000 users visiting my website from Canada and only 100 users visiting my website from the USA, does that mean my website will be ranked higher on Google.ca and lower on Google.com? And, if a website is using Google Analytics will it be ranked higher for the organic search engine keywords?

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  • Google Analytics and jQuery, happy together

    - by webbes
    Google Analytics is great out of the box already, but you can do much more than just registering your page loads. Especially with all these “Web 2.0” sites it can be convenient to not register page loads, but events! In this blog post I’ll show you how you can use jQuery in combination with Google Analytics to get a great insight on what actually happens on your website while you’re not looking!...(read more)

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  • Big Oh notation does not mention constant value

    - by user883561
    I am a programmer and have just started reading Algorithms. I am not completely convinced with the notations namely Bog Oh, Big Omega and Big Theta. The reason is by definition of Big Oh, it states that there should be a function g(x) such that it is always greater than or equal to f(x). Or f(x) <= c.n for all values of n n0. My doubt is the why dont we mention the constant value in the definition? For example. lets say a function 6n+4, we denote it as O(n). but its not true that the definition holds good for all constant value. this holds good only when c = 10 and n = 1. For lesser values of c than 6, the value of n0 increases. So why we do not mention the constant value as a part of the definition.

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