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  • Deploying Data Mining Models using Model Export and Import, Part 2

    - by [email protected]
    In my last post, Deploying Data Mining Models using Model Export and Import, we explored using DBMS_DATA_MINING.EXPORT_MODEL and DBMS_DATA_MINING.IMPORT_MODEL to enable moving a model from one system to another. In this post, we'll look at two distributed scenarios that make use of this capability and a tip for easily moving models from one machine to another using only Oracle Database, not an external file transport mechanism, such as FTP. The first scenario, consider a company with geographically distributed business units, each collecting and managing their data locally for the products they sell. Each business unit has in-house data analysts that build models to predict which products to recommend to customers in their space. A central telemarketing business unit also uses these models to score new customers locally using data collected over the phone. Since the models recommend different products, each customer is scored using each model. This is depicted in Figure 1.Figure 1: Target instance importing multiple remote models for local scoring In the second scenario, consider multiple hospitals that collect data on patients with certain types of cancer. The data collection is standardized, so each hospital collects the same patient demographic and other health / tumor data, along with the clinical diagnosis. Instead of each hospital building it's own models, the data is pooled at a central data analysis lab where a predictive model is built. Once completed, the model is distributed to hospitals, clinics, and doctor offices who can score patient data locally.Figure 2: Multiple target instances importing the same model from a source instance for local scoring Since this blog focuses on model export and import, we'll only discuss what is necessary to move a model from one database to another. Here, we use the package DBMS_FILE_TRANSFER, which can move files between Oracle databases. The script is fairly straightforward, but requires setting up a database link and directory objects. We saw how to create directory objects in the previous post. To create a database link to the source database from the target, we can use, for example: create database link SOURCE1_LINK connect to <schema> identified by <password> using 'SOURCE1'; Note that 'SOURCE1' refers to the service name of the remote database entry in your tnsnames.ora file. From SQL*Plus, first connect to the remote database and export the model. Note that the model_file_name does not include the .dmp extension. This is because export_model appends "01" to this name.  Next, connect to the local database and invoke DBMS_FILE_TRANSFER.GET_FILE and import the model. Note that "01" is eliminated in the target system file name.  connect <source_schema>/<password>@SOURCE1_LINK; BEGIN  DBMS_DATA_MINING.EXPORT_MODEL ('EXPORT_FILE_NAME' || '.dmp',                                 'MY_SOURCE_DIR_OBJECT',                                 'name =''MY_MINING_MODEL'''); END; connect <target_schema>/<password>; BEGIN  DBMS_FILE_TRANSFER.GET_FILE ('MY_SOURCE_DIR_OBJECT',                               'EXPORT_FILE_NAME' || '01.dmp',                               'SOURCE1_LINK',                               'MY_TARGET_DIR_OBJECT',                               'EXPORT_FILE_NAME' || '.dmp' );  DBMS_DATA_MINING.IMPORT_MODEL ('EXPORT_FILE_NAME' || '.dmp',                                 'MY_TARGET_DIR_OBJECT'); END; To clean up afterward, you may want to drop the exported .dmp file at the source and the transferred file at the target. For example, utl_file.fremove('&directory_name', '&model_file_name' || '.dmp');

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  • Deploying Data Mining Models using Model Export and Import

    - by [email protected]
    In this post, we'll take a look at how Oracle Data Mining facilitates model deployment. After building and testing models, a next step is often putting your data mining model into a production system -- referred to as model deployment. The ability to move data mining model(s) easily into a production system can greatly speed model deployment, and reduce the overall cost. Since Oracle Data Mining provides models as first class database objects, models can be manipulated using familiar database techniques and technology. For example, one or more models can be exported to a flat file, similar to a database table dump file (.dmp). This file can be moved to a different instance of Oracle Database EE, and then imported. All methods for exporting and importing models are based on Oracle Data Pump technology and found in the DBMS_DATA_MINING package. Before performing the actual export or import, a directory object must be created. A directory object is a logical name in the database for a physical directory on the host computer. Read/write access to a directory object is necessary to access the host computer file system from within Oracle Database. For our example, we'll work in the DMUSER schema. First, DMUSER requires the privilege to create any directory. This is often granted through the sysdba account. grant create any directory to dmuser; Now, DMUSER can create the directory object specifying the path where the exported model file (.dmp) should be placed. In this case, on a linux machine, we have the directory /scratch/oracle. CREATE OR REPLACE DIRECTORY dmdir AS '/scratch/oracle'; If you aren't sure of the exact name of the model or models to export, you can find the list of models using the following query: select model_name from user_mining_models; There are several options when exporting models. We can export a single model, multiple models, or all models in a schema using the following procedure calls: BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('MY_MODEL.dmp','dmdir','name =''MY_DT_MODEL'''); END; BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('MY_MODELS.dmp','dmdir',              'name IN (''MY_DT_MODEL'',''MY_KM_MODEL'')'); END; BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('ALL_DMUSER_MODELS.dmp','dmdir'); END; A .dmp file can be imported into another schema or database using the following procedure call, for example: BEGIN   DBMS_DATA_MINING.IMPORT_MODEL('MY_MODELS.dmp', 'dmdir'); END; As with models from any data mining tool, when moving a model from one environment to another, care needs to be taken to ensure the transformations that prepare the data for model building are matched (with appropriate parameters and statistics) in the system where the model is deployed. Oracle Data Mining provides automatic data preparation (ADP) and embedded data preparation (EDP) to reduce, or possibly eliminate, the need to explicitly transport transformations with the model. In the case of ADP, ODM automatically prepares the data and includes the necessary transformations in the model itself. In the case of EDP, users can associate their own transformations with attributes of a model. These transformations are automatically applied when applying the model to data, i.e., scoring. Exporting and importing a model with ADP or EDP results in these transformations being immediately available with the model in the production system.

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  • PHP: Aggregate Model Classes or Uber Model Classes?

    - by sunwukung
    In many of the discussions regarding the M in MVC, (sidestepping ORM controversies for a moment), I commonly see Model classes described as object representations of table data (be that an Active Record, Table Gateway, Row Gateway or Domain Model/Mapper). Martin Fowler warns against the development of an anemic domain model, i.e. a class that is nothing more than a wrapper for CRUD functionality. I've been working on an MVC application for a couple of months now. The DBAL in the application I'm working on started out simple (on account of my understanding - oh the benefits of hindsight), and is organised so that Controllers invoke Business Logic classes, that in turn access the database via DAO/Transaction Scripts pertinent to the task at hand. There are a few "Entity" classes that aggregate these DAO objects to provide a convenient CRUD wrapper, but also embody some of the "behaviour" of that Domain concept (for example, a user - since it's easy to isolate). Taking a look at some of the code, and thinking along refactoring some of the code into a Rich Domain Model, it occurred to me that were I to try and wrap the CRUD routines and behaviour of say, a Company into a single "Model" class, that would be a sizeable class. So, my question is this: do Models represent domain objects, business logic, service layers, all of the above combined? How do you go about defining the responsibilities for these components?

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  • Data Modeling Resources

    - by Dejan Sarka
    You can find many different data modeling resources. It is impossible to list all of them. I selected only the most valuable ones for me, and, of course, the ones I contributed to. Books Chris J. Date: An Introduction to Database Systems – IMO a “must” to understand the relational model correctly. Terry Halpin, Tony Morgan: Information Modeling and Relational Databases – meet the object-role modeling leaders. Chris J. Date, Nikos Lorentzos and Hugh Darwen: Time and Relational Theory, Second Edition: Temporal Databases in the Relational Model and SQL – all theory needed to manage temporal data. Louis Davidson, Jessica M. Moss: Pro SQL Server 2012 Relational Database Design and Implementation – the best SQL Server focused data modeling book I know by two of my friends. Dejan Sarka, et al.: MCITP Self-Paced Training Kit (Exam 70-441): Designing Database Solutions by Using Microsoft® SQL Server™ 2005 – SQL Server 2005 data modeling training kit. Most of the text is still valid for SQL Server 2008, 2008 R2, 2012 and 2014. Itzik Ben-Gan, Lubor Kollar, Dejan Sarka, Steve Kass: Inside Microsoft SQL Server 2008 T-SQL Querying – Steve wrote a chapter with mathematical background, and I added a chapter with theoretical introduction to the relational model. Itzik Ben-Gan, Dejan Sarka, Roger Wolter, Greg Low, Ed Katibah, Isaac Kunen: Inside Microsoft SQL Server 2008 T-SQL Programming – I added three chapters with theoretical introduction and practical solutions for the user-defined data types, dynamic schema and temporal data. Dejan Sarka, Matija Lah, Grega Jerkic: Training Kit (Exam 70-463): Implementing a Data Warehouse with Microsoft SQL Server 2012 – my first two chapters are about data warehouse design and implementation. Courses Data Modeling Essentials – I wrote a 3-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. Logical and Physical Modeling for Analytical Applications – online course I wrote for Pluralsight. Working with Temporal data in SQL Server – my latest Pluralsight course, where besides theory and implementation I introduce many original ways how to optimize temporal queries. Forthcoming presentations SQL Bits 12, July 17th – 19th, Telford, UK – I have a full-day pre-conference seminar Advanced Data Modeling Topics there.

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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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  • Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is HDFS. In this article we will take a quick look at the importance of the Relational Database in Big Data world. A Big Question? Here are a few questions I often received since the beginning of the Big Data Series - Does the relational database have no space in the story of the Big Data? Does relational database is no longer relevant as Big Data is evolving? Is relational database not capable to handle Big Data? Is it true that one no longer has to learn about relational data if Big Data is the final destination? Well, every single time when I hear that one person wants to learn about Big Data and is no longer interested in learning about relational database, I find it as a bit far stretched. I am not here to give ambiguous answers of It Depends. I am personally very clear that one who is aspiring to become Big Data Scientist or Big Data Expert they should learn about relational database. NoSQL Movement The reason for the NoSQL Movement in recent time was because of the two important advantages of the NoSQL databases. Performance Flexible Schema In personal experience I have found that when I use NoSQL I have found both of the above listed advantages when I use NoSQL database. There are instances when I found relational database too much restrictive when my data is unstructured as well as they have in the datatype which my Relational Database does not support. It is the same case when I have found that NoSQL solution performing much better than relational databases. I must say that I am a big fan of NoSQL solutions in the recent times but I have also seen occasions and situations where relational database is still perfect fit even though the database is growing increasingly as well have all the symptoms of the big data. Situations in Relational Database Outperforms Adhoc reporting is the one of the most common scenarios where NoSQL is does not have optimal solution. For example reporting queries often needs to aggregate based on the columns which are not indexed as well are built while the report is running, in this kind of scenario NoSQL databases (document database stores, distributed key value stores) database often does not perform well. In the case of the ad-hoc reporting I have often found it is much easier to work with relational databases. SQL is the most popular computer language of all the time. I have been using it for almost over 10 years and I feel that I will be using it for a long time in future. There are plenty of the tools, connectors and awareness of the SQL language in the industry. Pretty much every programming language has a written drivers for the SQL language and most of the developers have learned this language during their school/college time. In many cases, writing query based on SQL is much easier than writing queries in NoSQL supported languages. I believe this is the current situation but in the future this situation can reverse when No SQL query languages are equally popular. ACID (Atomicity Consistency Isolation Durability) – Not all the NoSQL solutions offers ACID compliant language. There are always situations (for example banking transactions, eCommerce shopping carts etc.) where if there is no ACID the operations can be invalid as well database integrity can be at risk. Even though the data volume indeed qualify as a Big Data there are always operations in the application which absolutely needs ACID compliance matured language. The Mixed Bag I have often heard argument that all the big social media sites now a days have moved away from Relational Database. Actually this is not entirely true. While researching about Big Data and Relational Database, I have found that many of the popular social media sites uses Big Data solutions along with Relational Database. Many are using relational databases to deliver the results to end user on the run time and many still uses a relational database as their major backbone. Here are a few examples: Facebook uses MySQL to display the timeline. (Reference Link) Twitter uses MySQL. (Reference Link) Tumblr uses Sharded MySQL (Reference Link) Wikipedia uses MySQL for data storage. (Reference Link) There are many for prominent organizations which are running large scale applications uses relational database along with various Big Data frameworks to satisfy their various business needs. Summary I believe that RDBMS is like a vanilla ice cream. Everybody loves it and everybody has it. NoSQL and other solutions are like chocolate ice cream or custom ice cream – there is a huge base which loves them and wants them but not every ice cream maker can make it just right  for everyone’s taste. No matter how fancy an ice cream store is there is always plain vanilla ice cream available there. Just like the same, there are always cases and situations in the Big Data’s story where traditional relational database is the part of the whole story. In the real world scenarios there will be always the case when there will be need of the relational database concepts and its ideology. It is extremely important to accept relational database as one of the key components of the Big Data instead of treating it as a substandard technology. Ray of Hope – NewSQL In this module we discussed that there are places where we need ACID compliance from our Big Data application and NoSQL will not support that out of box. There is a new termed coined for the application/tool which supports most of the properties of the traditional RDBMS and supports Big Data infrastructure – NewSQL. Tomorrow In tomorrow’s blog post we will discuss about NewSQL. 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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  • Rails model belongs to model that belongs to model but i want to use another name

    - by Micke
    Hello. This may be a stupid question but im just starting to learn Rail thats why i am asking thsi question. I have one model called "User" which handles all the users in my community. Now i want to add a guestbook to every user. So i created a model called "user_guestbook" and inserted this into the new model: belongs_to :user and this into the user model: has_one :user_guestbook, :as => :guestbook The next thing i did was to add a new model to handle the posts inside the guestbook. I named it "guestbook_posts" and added this code into the new model: belongs_to :user_guestbook And this into the user_guestbook model: has_many :guestbook_posts, :as => :posts What i wanted to achive was to be able to fetch all the posts to a certain user by: @user = User.find(1) puts @user.guestbook.posts But it doesnt work for me. I dont know what i am doing wrong and if there is any easier way to do this please tell me so. Just to note, i have created some migrations for it to as follows: create_user_guestbook: t.integer :user_id create_guestbook_posts: t.integer :guestbook_id t.integer :from_user t.string :post Thanks in advance!

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  • Oracle BI Server Modeling, Part 1- Designing a Query Factory

    - by bob.ertl(at)oracle.com
      Welcome to Oracle BI Development's BI Foundation blog, focused on helping you get the most value from your Oracle Business Intelligence Enterprise Edition (BI EE) platform deployments.  In my first series of posts, I plan to show developers the concepts and best practices for modeling in the Common Enterprise Information Model (CEIM), the semantic layer of Oracle BI EE.  In this segment, I will lay the groundwork for the modeling concepts.  First, I will cover the big picture of how the BI Server fits into the system, and how the CEIM controls the query processing. Oracle BI EE Query Cycle The purpose of the Oracle BI Server is to bridge the gap between the presentation services and the data sources.  There are typically a variety of data sources in a variety of technologies: relational, normalized transaction systems; relational star-schema data warehouses and marts; multidimensional analytic cubes and financial applications; flat files, Excel files, XML files, and so on. Business datasets can reside in a single type of source, or, most of the time, are spread across various types of sources. Presentation services users are generally business people who need to be able to query that set of sources without any knowledge of technologies, schemas, or how sources are organized in their company. They think of business analysis in terms of measures with specific calculations, hierarchical dimensions for breaking those measures down, and detailed reports of the business transactions themselves.  Most of them create queries without knowing it, by picking a dashboard page and some filters.  Others create their own analysis by selecting metrics and dimensional attributes, and possibly creating additional calculations. The BI Server bridges that gap from simple business terms to technical physical queries by exposing just the business focused measures and dimensional attributes that business people can use in their analyses and dashboards.   After they make their selections and start the analysis, the BI Server plans the best way to query the data sources, writes the optimized sequence of physical queries to those sources, post-processes the results, and presents them to the client as a single result set suitable for tables, pivots and charts. The CEIM is a model that controls the processing of the BI Server.  It provides the subject areas that presentation services exposes for business users to select simplified metrics and dimensional attributes for their analysis.  It models the mappings to the physical data access, the calculations and logical transformations, and the data access security rules.  The CEIM consists of metadata stored in the repository, authored by developers using the Administration Tool client.     Presentation services and other query clients create their queries in BI EE's SQL-92 language, called Logical SQL or LSQL.  The API simply uses ODBC or JDBC to pass the query to the BI Server.  Presentation services writes the LSQL query in terms of the simplified objects presented to the users.  The BI Server creates a query plan, and rewrites the LSQL into fully-detailed SQL or other languages suitable for querying the physical sources.  For example, the LSQL on the left below was rewritten into the physical SQL for an Oracle 11g database on the right. Logical SQL   Physical SQL SELECT "D0 Time"."T02 Per Name Month" saw_0, "D4 Product"."P01  Product" saw_1, "F2 Units"."2-01  Billed Qty  (Sum All)" saw_2 FROM "Sample Sales" ORDER BY saw_0, saw_1       WITH SAWITH0 AS ( select T986.Per_Name_Month as c1, T879.Prod_Dsc as c2,      sum(T835.Units) as c3, T879.Prod_Key as c4 from      Product T879 /* A05 Product */ ,      Time_Mth T986 /* A08 Time Mth */ ,      FactsRev T835 /* A11 Revenue (Billed Time Join) */ where ( T835.Prod_Key = T879.Prod_Key and T835.Bill_Mth = T986.Row_Wid) group by T879.Prod_Dsc, T879.Prod_Key, T986.Per_Name_Month ) select SAWITH0.c1 as c1, SAWITH0.c2 as c2, SAWITH0.c3 as c3 from SAWITH0 order by c1, c2   Probably everybody reading this blog can write SQL or MDX.  However, the trick in designing the CEIM is that you are modeling a query-generation factory.  Rather than hand-crafting individual queries, you model behavior and relationships, thus configuring the BI Server machinery to manufacture millions of different queries in response to random user requests.  This mass production requires a different mindset and approach than when you are designing individual SQL statements in tools such as Oracle SQL Developer, Oracle Hyperion Interactive Reporting (formerly Brio), or Oracle BI Publisher.   The Structure of the Common Enterprise Information Model (CEIM) The CEIM has a unique structure specifically for modeling the relationships and behaviors that fill the gap from logical user requests to physical data source queries and back to the result.  The model divides the functionality into three specialized layers, called Presentation, Business Model and Mapping, and Physical, as shown below. Presentation services clients can generally only see the presentation layer, and the objects in the presentation layer are normally the only ones used in the LSQL request.  When a request comes into the BI Server from presentation services or another client, the relationships and objects in the model allow the BI Server to select the appropriate data sources, create a query plan, and generate the physical queries.  That's the left to right flow in the diagram below.  When the results come back from the data source queries, the right to left relationships in the model show how to transform the results and perform any final calculations and functions that could not be pushed down to the databases.   Business Model Think of the business model as the heart of the CEIM you are designing.  This is where you define the analytic behavior seen by the users, and the superset library of metric and dimension objects available to the user community as a whole.  It also provides the baseline business-friendly names and user-readable dictionary.  For these reasons, it is often called the "logical" model--it is a virtual database schema that persists no data, but can be queried as if it is a database. The business model always has a dimensional shape (more on this in future posts), and its simple shape and terminology hides the complexity of the source data models. Besides hiding complexity and normalizing terminology, this layer adds most of the analytic value, as well.  This is where you define the rich, dimensional behavior of the metrics and complex business calculations, as well as the conformed dimensions and hierarchies.  It contributes to the ease of use for business users, since the dimensional metric definitions apply in any context of filters and drill-downs, and the conformed dimensions enable dashboard-wide filters and guided analysis links that bring context along from one page to the next.  The conformed dimensions also provide a key to hiding the complexity of many sources, including federation of different databases, behind the simple business model. Note that the expression language in this layer is LSQL, so that any expression can be rewritten into any data source's query language at run time.  This is important for federation, where a given logical object can map to several different physical objects in different databases.  It is also important to portability of the CEIM to different database brands, which is a key requirement for Oracle's BI Applications products. Your requirements process with your user community will mostly affect the business model.  This is where you will define most of the things they specifically ask for, such as metric definitions.  For this reason, many of the best-practice methodologies of our consulting partners start with the high-level definition of this layer. Physical Model The physical model connects the business model that meets your users' requirements to the reality of the data sources you have available. In the query factory analogy, think of the physical layer as the bill of materials for generating physical queries.  Every schema, table, column, join, cube, hierarchy, etc., that will appear in any physical query manufactured at run time must be modeled here at design time. Each physical data source will have its own physical model, or "database" object in the CEIM.  The shape of each physical model matches the shape of its physical source.  In other words, if the source is normalized relational, the physical model will mimic that normalized shape.  If it is a hypercube, the physical model will have a hypercube shape.  If it is a flat file, it will have a denormalized tabular shape. To aid in query optimization, the physical layer also tracks the specifics of the database brand and release.  This allows the BI Server to make the most of each physical source's distinct capabilities, writing queries in its syntax, and using its specific functions. This allows the BI Server to push processing work as deep as possible into the physical source, which minimizes data movement and takes full advantage of the database's own optimizer.  For most data sources, native APIs are used to further optimize performance and functionality. The value of having a distinct separation between the logical (business) and physical models is encapsulation of the physical characteristics.  This encapsulation is another enabler of packaged BI applications and federation.  It is also key to hiding the complex shapes and relationships in the physical sources from the end users.  Consider a routine drill-down in the business model: physically, it can require a drill-through where the first query is MDX to a multidimensional cube, followed by the drill-down query in SQL to a normalized relational database.  The only difference from the user's point of view is that the 2nd query added a more detailed dimension level column - everything else was the same. Mappings Within the Business Model and Mapping Layer, the mappings provide the binding from each logical column and join in the dimensional business model, to each of the objects that can provide its data in the physical layer.  When there is more than one option for a physical source, rules in the mappings are applied to the query context to determine which of the data sources should be hit, and how to combine their results if more than one is used.  These rules specify aggregate navigation, vertical partitioning (fragmentation), and horizontal partitioning, any of which can be federated across multiple, heterogeneous sources.  These mappings are usually the most sophisticated part of the CEIM. Presentation You might think of the presentation layer as a set of very simple relational-like views into the business model.  Over ODBC/JDBC, they present a relational catalog consisting of databases, tables and columns.  For business users, presentation services interprets these as subject areas, folders and columns, respectively.  (Note that in 10g, subject areas were called presentation catalogs in the CEIM.  In this blog, I will stick to 11g terminology.)  Generally speaking, presentation services and other clients can query only these objects (there are exceptions for certain clients such as BI Publisher and Essbase Studio). The purpose of the presentation layer is to specialize the business model for different categories of users.  Based on a user's role, they will be restricted to specific subject areas, tables and columns for security.  The breakdown of the model into multiple subject areas organizes the content for users, and subjects superfluous to a particular business role can be hidden from that set of users.  Customized names and descriptions can be used to override the business model names for a specific audience.  Variables in the object names can be used for localization. For these reasons, you are better off thinking of the tables in the presentation layer as folders than as strict relational tables.  The real semantics of tables and how they function is in the business model, and any grouping of columns can be included in any table in the presentation layer.  In 11g, an LSQL query can also span multiple presentation subject areas, as long as they map to the same business model. Other Model Objects There are some objects that apply to multiple layers.  These include security-related objects, such as application roles, users, data filters, and query limits (governors).  There are also variables you can use in parameters and expressions, and initialization blocks for loading their initial values on a static or user session basis.  Finally, there are Multi-User Development (MUD) projects for developers to check out units of work, and objects for the marketing feature used by our packaged customer relationship management (CRM) software.   The Query Factory At this point, you should have a grasp on the query factory concept.  When developing the CEIM model, you are configuring the BI Server to automatically manufacture millions of queries in response to random user requests. You do this by defining the analytic behavior in the business model, mapping that to the physical data sources, and exposing it through the presentation layer's role-based subject areas. While configuring mass production requires a different mindset than when you hand-craft individual SQL or MDX statements, it builds on the modeling and query concepts you already understand. The following posts in this series will walk through the CEIM modeling concepts and best practices in detail.  We will initially review dimensional concepts so you can understand the business model, and then present a pattern-based approach to learning the mappings from a variety of physical schema shapes and deployments to the dimensional model.  Along the way, we will also present the dimensional calculation template, and learn how to configure the many additivity patterns.

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  • Why model => model.Reason_ID turns to model =>Convert(model.Reason_ID)

    - by er-v
    I have my own html helper extension, wich I use this way <%=Html.LocalizableLabelFor(model => model.Reason_ID, Register.PurchaseReason) %> which declared like this. public static MvcHtmlString LocalizableLabelFor<T>(this HtmlHelper<T> helper, Expression<Func<T, object>> expr, string captionValue) where T : class { return helper.LocalizableLabelFor(ExpressionHelper.GetExpressionText(expr), captionValue); } but when I open it in debugger expr.Body.ToString() will show me Convert(model.Reason_ID). But should model.Reason_ID. That's a big problem, becouse ExpressionHelper.GetExpressionText(expr) returns empty string. What a strange magic is that? How can I get rid of it?

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  • Is it easy to switch from relational to non-relational databases with Rails?

    - by Tam
    Good day, I have been using Rails/Mysql for the past while but I have been hearing about Cassandra, MongoDB, CouchDB and other document-store DB/Non-relational databases. I'm planning to explore them later as they might be better alternative for scalability. I'm planning to start an application soon. Will it make a different with Rails design if I move from relational to non-relational database? I know Rails migrations are database-agnostic but wasn't sure if moving to non-relational will make difference with design or not.

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  • SQL SERVER – Log File Growing for Model Database – model Database Log File Grew Too Big

    - by pinaldave
    After reading my earlier article SQL SERVER – master Database Log File Grew Too Big, I received an email recently from another reader asking why does the log file of model database grow every day when he is not carrying out any operation in the model database. As per the email, he is absolutely sure that he is doing nothing on his model database; he had used policy management to catch any T-SQL operation in the model database and there were none. This was indeed surprising to me. I sent a request to access to his server, which he happily agreed for and within a min, we figured out the issue. He was taking the backup of the model database every day taking the database backup every night. When I explained the same to him, he did not believe it; so I quickly wrote down the following script. The results before and after the usage of the script were very clear. What is a model database? The model database is used as the template for all databases created on an instance of SQL Server. Any object you create in the model database will be automatically created in subsequent user database created on the server. NOTE: Do not run this in production environment. During the demo, the model database was in full recovery mode and only full backup operation was performed (no log backup). Before Backup Script Backup Script in loop DECLARE @FLAG INT SET @FLAG = 1 WHILE(@FLAG < 1000) BEGIN BACKUP DATABASE [model] TO  DISK = N'D:\model.bak' SET @FLAG = @FLAG + 1 END GO After Backup Script Why did this happen? The model database was in full recovery mode and taking full backup is logged operation. As there was no log backup and only full backup was performed on the model database, the size of the log file kept growing. Resolution: Change the backup mode of model database from “Full Recovery” to “Simple Recovery.”. Take full backup of the model database “only” when you change something in the model database. Let me know if you have encountered a situation like this? If so, how did you resolve it? It will be interesting to know about your experience. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • How to use the client object model with SharePoint2010

    - by ybbest
    In SharePoint2010, you can use client object model to communicate with SharePoint server. Today, I’d like to show you how to achieve this by using the c# console application. You can download the solution here. 1. Create a Console application in visual studio and add the following references to the project. 2. Insert your code as below ClientContext context = new ClientContext("http://demo2010a"); Web currentWeb = context.Web; context.Load(currentWeb, web =&gt; web.Title); context.ExecuteQuery(); Console.WriteLine(currentWeb.Title); Console.ReadLine(); 3. Run your code then you will get the web title displayed as shown below Note: If you got the following errors, you need to change your target framework from .Net Framework 4 client profile to .Net Framework 4 as shown below: Change from TO

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  • Creating an Entity Data Model using the Model First approach

    - by nikolaosk
    This is going to be the second post of a series of posts regarding Entity Framework and how we can use Entity Framework version 4.0 new features. You can read the first post here . In order to follow along you must have some knowledge of C# and know what an ORM system is and what kind of problems Entity Framework addresses.It will be handy to know how to work inside the Visual Studio 2010 IDE . I have a post regarding ASP.Net and EntityDataSource . You can read it here .I have 3 more posts on Profiling...(read more)

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  • Given the presentation model pattern, is the view, presentation model, or model responsible for adding child views to an existing view at runtime?

    - by Ryan Taylor
    I am building a Flex 4 based application using the presentation model design pattern. This application will have several different components to it as shown in the image below. The MainView and DashboardView will always be visible and they each have corresponding presentation models and models as necessary. These views are easily created by declaring their MXML in the application root. <s:HGroup width="100%" height="100%"> <MainView width="75% height="100%"/> <DashboardView width="25%" height="100%"/> </s:HGroup> There will also be many WidgetViewN views that can be added to the DashboardView by the user at runtime through a simple drop down list. This will need to be accomplished via ActionScript. The drop down list should always show what WidgetViewN has already been added to the DashboardView. Therefore some state about which WidgetViewN's have been created needs to be stored. Since the list of available WidgetViewN and which ones are added to the DashboardView also need to be accessible from other components in the system I think this needs to be stored in a Model object. My understanding of the presentation model design pattern is that the view is very lean. It contains as close to zero logic as is practical. The view communicates/binds to the presentation model which contains all the necessary view logic. The presentation model is effectively an abstract representation of the view which supports low coupling and eases testability. The presentation model may have one or more models injected in in order to display the necessary information. The models themselves contain no view logic whatsoever. So I have a several questions around this design. Who should be responsible for creating the WidgetViewN components and adding these to the DashboardView? Is this the responsibility of the DashboardView, DashboardPresentationModel, DashboardModel or something else entirely? It seems like the DashboardPresentationModel would be responsible for creating/adding/removing any child views from it's display but how do you do this without passing in the DashboardView to the DashboardPresentationModel? The list of available and visible WidgetViewN components needs to be accessible to a few other components as well. Is it okay for a reference to a WidgetViewN to be stored/referenced in a model? Are there any good examples of the presentation model pattern online in Flex that also include creating child views at runtime?

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  • Is there really Object-relational impedance mismatch?

    - by user52763
    It is always stated that it is hard to store applications objects in relational databases - the object-relational impedance mismatch - and that is why Document databases are better. However, is there really an impedance mismatch? And object has a key (albeit it may be hidden away by the runtime as a pointer to memory), a set of values, and foreign keys to other objects. Objects are as much made up of tables as it is a document. Neither really fit. I can see a use for databases to model the data into specific shapes for scenarios in the application - e.g. to speed up database lookup and avoid joins, etc., but won't it be better to keep the data as normalized as possible at the core, and transform as required?

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  • MVP, WinForms - how to avoid bloated view, presenter and presentation model

    - by MatteS
    When implementing MVP pattern in winforms I often find bloated view interfaces with too many properties, setters and getters. An easy example with be a view with 3 buttons and 7 textboxes, all having value, enabled and visible properties exposed from the view. Adding validation results for this, and you could easily end up with an interface with 40ish properties. Using the Presentation Model, there'll be a model with the same number of properties aswell. How do you easily sync the view and the presentation model without having bloated presenter logic that pass all the values back and forth? (With that 80ish line presenter code, imagine with the presenter test that mocks the model and view will look like..160ish lines of code just to mock that transfer.) Is there any framework to handle this without resorting to winforms databinding? (you might want to use different views than a winforms view. According to some, this sync should be the presenters job..) Would you use AutoMapper? Maybe im asking the wrong questions, but it seems to me MVP easily gets bloated without some good solution here..

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  • Help to translate SQL query to Relational Algebra

    - by Mestika
    Hi everyone, I'm having some difficulties with translating some queries to Relational Algebra. I've a great book about Database Design and here is a chapter about Relational Algebra but I still seem to have some trouble creating the right one: Thoes queries I've most difficuelt with is these: SELECT COUNT( cs.student_id ) AS counter FROM course c, course_student cs WHERE c.id = cs.course_id AND c.course_name = 'Introduction to Database Design' SELECT COUNT( cs.student_id ) FROM Course c INNER JOIN course_student cs ON c.id = cs.course_id WHERE c.course_name = 'Introduction to Database Design' and SELECT COUNT( * ) FROM student JOIN grade ON student.f_name = "Andreas" AND student.l_name = "Pedersen" AND student.id = grade.student_id I know the notation can be a bit hard to paste into HTML forum, but maybe just use some common name or the Greek name. Thanks in advance Mestika

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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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  • Model Driven Architecture Approach in programming / modelling

    - by yak
    I know the basics of the model driven architecture: it is all about model the system which I want to create and create the core code afterwards. I used CORBA a while ago. First thing that I needed to do was to create an abstract interface (some kind of model of the system I want to build) and generate core code later. But I have a different question: is model driven architecture a broad approach or not? I mean, let's say, that I have the language (modelling language) in which I want to model EXISTING system (opposite to the system I want to CREATE), and then analyze the model of the created system and different facts about that modeled abstraction. In this case, can the process I described above be considered the model driven architecture approach? I mean, I have the model, but this is the model of the existing system, not the system to be created.

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  • Synonym for "Many-to-Many" relationship (relational databases)

    - by Byron
    What's a synonym for a "many-to-many" relationship? I've finished writing an object-relational mapper but I'm still stumped as to what to name the function that adds that relation. addParent() and addChild() seemed quite logical for the many-to-one/one-to-many and addSuperclass() for one-to-one inheritance, but addManyToMany() would sound quite unintuitive to an object-oriented programmer. addSibling() or addCousin() doesn't really make sense either. Any suggestions? And before you dismiss this as a non-programming question, please remember that consistent naming schemes and encapsulation are pretty integral to programming :)

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  • Embedded Model Designing -- top down or bottom up?

    - by Jeff
    I am trying to learn RoR and develop a webapp. I have a few models I have thought of for this app, and they are fairly embedded. For example (please excuse my lack of RoR syntax): Model: textbook title:string type:string has_many: chapters Model: chapter content:text has_one: review_section Model: review_section title:string has_many: questions has_many: answers , through :questions Model: questions ... Model: answers ... My question is, with the example I gave, should I start at the top model (textbook) or the bottom most (answers)?

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  • Are factors such as Intellisense support and strong typing enough to justify the use of an 'Anaemic Domain Model'?

    - by David Osborne
    It's easy to accept that objects should be used in all layers except a layer nominated as a data layer. However, it's just as easy to end-up with an 'anaemic domain model' that is just an object representation of data with no real functionality ( http://martinfowler.com/bliki/AnemicDomainModel.html ). However, using objects in this fashion brings the benefit of factors such as Intellisense support, strong typing, readability, discoverability, etc. Are these factors strong arguments for an otherwise, anaemic domain model?

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  • Using design-patterns to transform web-service model classes into local model classes and vise versa

    - by Daniil Petrov
    There is a web-application built with play framework 1.2.7. It contains less than 10 model classes. The main purpose of the application is a lightweight access to a complex remote application (more than 50 model classes). The remote application has its own SOAP API and we use it for synchronization of data. There is a scheduled job in the web-app which makes requests to the remote app. It gets bunches of objects from the remote model and populates corresponding objects of the local model. Currently, there are two groups of classes - the local model and the remote model (generated from wsdl schema). It is not allowed to make any modifications to the remote model. Transformations are being made in the scheduled job class. When it gets objects from the remote app it creates local objects. Recently, it was decided to add a possibility to modify the remote objects. It requires more transformations on our side. We need to transform from remote to local model when reading objects and from local to remote when changing objects. I wonder if this would be possible to use some design-patterns to reduce a number of transformations?

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  • Waterfall Model (SDLC) vs. Prototyping Model

    The characters in the fable of the Tortoise and the Hare can easily be used to demonstrate the similarities and differences between the Waterfall and Prototyping software development models. This children fable is about a race between a consistently slow moving but steadfast turtle and an extremely fast but unreliable rabbit. After closely comparing each character’s attributes in correlation with both software development models, a trend seems to appear in that the Waterfall closely resembles the Tortoise in that Waterfall Model is typically a slow moving process that is broken up in to multiple sequential steps that must be executed in a standard linear pattern. The Tortoise can be quoted several times in the story saying “Slow and steady wins the race.” This is the perfect mantra for the Waterfall Model in that this model is seen as a cumbersome and slow moving. Waterfall Model Phases Requirement Analysis & Definition This phase focuses on defining requirements for a project that is to be developed and determining if the project is even feasible. Requirements are collected by analyzing existing systems and functionality in correlation with the needs of the business and the desires of the end users. The desired output for this phase is a list of specific requirements from the business that are to be designed and implemented in the subsequent steps. In addition this phase is used to determine if any value will be gained by completing the project. System Design This phase focuses primarily on the actual architectural design of a system, and how it will interact within itself and with other existing applications. Projects at this level should be viewed at a high level so that actual implementation details are decided in the implementation phase. However major environmental decision like hardware and platform decision are typically decided in this phase. Furthermore the basic goal of this phase is to design an application at the system level in those classes, interfaces, and interactions are defined. Additionally decisions about scalability, distribution and reliability should also be considered for all decisions. The desired output for this phase is a functional  design document that states all of the architectural decisions that have been made in regards to the project as well as a diagrams like a sequence and class diagrams. Software Design This phase focuses primarily on the refining of the decisions found in the functional design document. Classes and interfaces are further broken down in to logical modules based on the interfaces and interactions previously indicated. The output of this phase is a formal design document. Implementation / Coding This phase focuses primarily on implementing the previously defined modules in to units of code. These units are developed independently are intergraded as the system is put together as part of a whole system. Software Integration & Verification This phase primarily focuses on testing each of the units of code developed as well as testing the system as a whole. There are basic types of testing at this phase and they include: Unit Test and Integration Test. Unit Test are built to test the functionality of a code unit to ensure that it preforms its desired task. Integration testing test the system as a whole because it focuses on results of combining specific units of code and validating it against expected results. The output of this phase is a test plan that includes test with expected results and actual results. System Verification This phase primarily focuses on testing the system as a whole in regards to the list of project requirements and desired operating environment. Operation & Maintenance his phase primarily focuses on handing off the competed project over to the customer so that they can verify that all of their requirements have been met based on their original requirements. This phase will also validate the correctness of their requirements and if any changed need to be made. In addition, any problems not resolved in the previous phase will be handled in this section. The Waterfall Model’s linear and sequential methodology does offer a project certain advantages and disadvantages. Advantages of the Waterfall Model Simplistic to implement and execute for projects and/or company wide Limited demand on resources Large emphasis on documentation Disadvantages of the Waterfall Model Completed phases cannot be revisited regardless if issues arise within a project Accurate requirement are never gather prior to the completion of the requirement phase due to the lack of clarification in regards to client’s desires. Small changes or errors that arise in applications may cause additional problems The client cannot change any requirements once the requirements phase has been completed leaving them no options for changes as they see their requirements changes as the customers desires change. Excess documentation Phases are cumbersome and slow moving Learn more about the Major Process in the Sofware Development Life Cycle and Waterfall Model. Conversely, the Hare shares similar traits with the prototyping software development model in that ideas are rapidly converted to basic working examples and subsequent changes are made to quickly align the project with customers desires as they are formulated and as software strays from the customers vision. The basic concept of prototyping is to eliminate the use of well-defined project requirements. Projects are allowed to grow as the customer needs and request grow. Projects are initially designed according to basic requirements and are refined as requirement become more refined. This process allows customer to feel their way around the application to ensure that they are developing exactly what they want in the application This model also works well for determining the feasibility of certain approaches in regards to an application. Prototypes allow for quickly developing examples of implementing specific functionality based on certain techniques. Advantages of Prototyping Active participation from users and customers Allows customers to change their mind in specifying requirements Customers get a better understanding of the system as it is developed Earlier bug/error detection Promotes communication with customers Prototype could be used as final production Reduced time needed to develop applications compared to the Waterfall method Disadvantages of Prototyping Promotes constantly redefining project requirements that cause major system rewrites Potential for increased complexity of a system as scope of the system expands Customer could believe the prototype as the working version. Implementation compromises could increase the complexity when applying updates and or application fixes When companies trying to decide between the Waterfall model and Prototype model they need to evaluate the benefits and disadvantages for both models. Typically smaller companies or projects that have major time constraints typically head for more of a Prototype model approach because it can reduce the time needed to complete the project because there is more of a focus on building a project and less on defining requirements and scope prior to the start of a project. On the other hand, Companies with well-defined requirements and time allowed to generate proper documentation should steer towards more of a waterfall model because they are in a position to obtain clarified requirements and have to design and optimal solution prior to the start of coding on a project.

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