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  • Now Shipping! NetAdvantage for .NET 2010 Volume 3!

    The new NetAdvantage Ultimate includes all four Line of Business user interface control sets for ASP .NET, Windows Forms, WPF and Silverlight plus two advanced Data Visualization UI control sets for WPF and Silverlight. With six NetAdvantage products in one robust package, Infragistics® gives you hundreds of controls and infinite development possibilities. Unified XAML Product Strategy-Share Code, Get More Controls In the 10.3 release, Infragistics continues to deliver code parity between the XAML platforms, WPF and Silverlight. In the line of business toolsets, Infragistics introduces the new xamSchedule™, full-featured, Outlook® 2010-style schedule controls, and the new xamDataTree™, a data bound tree view that comfortably handles tens of thousands of tree nodes. Mimicking our Silverlight Drag and Drop Framework, the WPF Drag and Drop Framework CTP empowers you to add your own rich touches to your applications. Track Users' Behaviors New to all NetAdvantage Silverlight controls is the Infragistics Analytics Framework (IGAF), which empowers you to track user behavior in RIAs running on Silverlight 4. Building on the Microsoft® Silverlight Analytics Framework, with IGAF you can analyze the user's behaviors to ensure the experience you want to deliver. NetAdvantage for Windows Forms--New Office® 2010 Ribbon and Application Menu 2010 Create new experiences with Windows Forms. Now with Office 2010 styling, NetAdvantage for Windows Forms has new features such as Microsoft® Office 2010 ribbon and enhanced Infragistics.Excel to export the contents of the high performance WinGrid™ into Microsoft Excel® 2010. The new Windows Message Support enables Infragistics standalone editor controls to process numerous Windows® OS messages, allowing them to respond just like native controls to changes in the Windows environment. Create Faster Web 2.0 Experiences with NetAdvantage for ASP .NET Infragistics continues to push the envelope to deliver the fastest ASP .NET WebForms controls available on the market. Our lightning fast ASP .NET grids are now enhanced with XPS/PDF Exporting and Summary Rows. This release also includes support for jQuery Templating (as a CTP) within our WebDataGrid™ and WebDataTree™ controls allowing you to quickly cut down overall page size. Deliver Business Intelligence with Power, Flexibility and the Office 2010 Experience NetAdvantage for WPF Data Visualization and NetAdvantage for Silverlight Data Visualization help you deliver flexible, powerful and usable end user experiences in Business Intelligence applications. Both suites include the Pivot Grid that delivers the full power of online analytical processing (OLAP) to present multi-dimensional data, sliced and diced in cross-tabulated form for end users to drill down into, interact with and easily extract meaning from the data. Mapping Made Easy 10.3 marks the official release of the WPF Data Visualization xamMap™ control to map anything and everything from geographic to geo-spacial mapping data. Map layers allow you to add successive levels of detail, navigational panes for panning in all directions, color swatch panes that facilitate value scales like Choropleth shading, and scale panes allowing users to zoom-in and out. Both toolsets introduce the first of many relationship maps! With the xamOrgChart™ CTP you can map out organizational charts of up to 50K employees, competitive brackets (think World Cup) and any other relational, organizational map your application needs. http://www.infragistics.com span.fullpost {display:none;}

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  • Migration a database from 32bit to 64bit

    - by Mike Dietrich
    Database migrations from an 32bit environment to an 64bit environment keeping the same platform architecture (e.g. moving an Oracle 10.2.0.5 database from MS Windows XP 32bit to MS Windows Server 2003 64bit) does not happen that often anymore. But still we see them getting done. And there are a few things to note when doing such a move. First of all the important question is:Will you upgrade your database as part of this move - Yes or No? If you say "Yes" then you are almost done with that topic as we will take care of that bitnes move during the upgrade. The only thing you have to take care is OLAP in case you are using OLAP Option with Analytic Workspaces (AW) by yourself. Those store data in Binary LOBs - and in order to move AWs from 32bit to 64bit you have to export your AWs prior to the move - and import them later on. People who don't use OLAP don't have to take care on this. But if you say "No" (meaning: no upgrade actions involved - you keep your database version) then you have to make sure to invalidate all packages and stored code in the database before you shutdown your database in the 32bit environment and prior to moving it over. And the same rule as above for OLAP applies once you use the OLAP Option. In the source environment: startup upgrade;    -- [or startup migrate; -- for Oracle 9i] @?/rdbms/admin/utlirp.sqlshutdown immediate In the destination environment: startup upgrade @?/olap/admin/xumuts.plb --Only if OLAP Option is installed@?/rdbms/admin/utlrp.sql The script utlirp.sql will invalidate all packages and stored code, utlrp.sql will recompile - and xumuts.plb will rebuild the OLAP Analytic Workspaces in case you have the OLAP Option installed.

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  • Python / Django : emulating a multidimensional layer on a MySQL database

    - by Sébastien Piquemal
    Hi, I'm working on a Django project where I need to provide a lot of different visualizations on the same data (for example average of a value for each month, for each year / for a location, etc...). I have been using an OLAP database once in college, and I thought that it would fit my needs, but it appears that it is much too heavy for what I need. Actually the volume of data is not very big, so I don't need any optimization, just a way to present different visualizations of the same data without having to write 1000 times the same code. So, to recap, I need a python library: to emulate a multidimensional database (OLAP style would be nice because I think it is quite convenient : star structure, and everything) non-intrusive, because I can't modify anything on the existing MySQL database easy-to-use, because otherwise there's no point in replacing some overhead by another.

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  • Python / Django : emulating a multidimensionnal layer on a mySql database

    - by Sébastien Piquemal
    Hi, I'm working on a Django project where I need to provide a lot of different visualizations on the same data (for example average of a value for each month, for each year / for a location, etc ...). I have been using OLAP database once in college, and I thought that it would fit my needs, but it appears that it is much to heavy for what I need. Actually the volume of data is not very big, so I don't need any optimization, just a way to present different visualizations of the same data without having to write 1000 times the same code. So let's recap : I need a python library : to emulate a multidimensional database (OLAP style would be nice because I think it is quite convenient : stat structure, and everything) non-intrusive, because I can't modify anything on the existing mysql database easy-to-use, because otherwise there's no point in replacing some overhead by another.

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  • Is it possible to create an efficient UDF alternative to Excel's CUBEVALUE function?

    - by bright
    We'd like to create a simpler alternative to Excel's CUBEVALUE function for retrieving data from an OLAP server. The details aren't critical, but briefly, our function will "know" the source connection and accept a very simple ticker-like parameter and a date, in place of CUBEVALUE's MDX-style parameters. This is for internal use within our firm, just FYI. However, Excel has optimized CUBEVALUE so that calls to the OLAP server are batched. Question: Is there a way to code the new function so that it can similarly batch calls rather than issue a separate query for each cell?

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  • What is the difference between cubes and the Unified Dimensional Model (if any)?

    - by ngm
    I'm currently researching SQL Server 2008 as a business intelligence solution, and currently looking at Analysis Services (and I'm pretty new to business intelligence as a whole...) I'm a bit confused by some of the terms in SSAS, particularly the conceptual differences between cubes and MS's Unified Dimensional Model. I believe that a cube in SSAS is basically an OLAP cube -- dimensions, measures, something that sits between the underlying data source and a business user. But then that's kind of what I understand UDM to be as well. The docs for SQL Server 2005 seem to suggest as much: "A cube is essentially synonymous with a Unified Dimensional Model (UDM)". But then the SQL Server 2008 pages sort of suggest that UDM is a wrapper for both multidimensional data (cubes) and relational data: "Use the Unified Dimensional Model to provide one consolidated business view for relational and multidimensional data that includes business entities, business logic, calculations, and metrics." This blog post suggests similarly: "UDM provides a single dimensional model for all OLAP analysis and relational reporting needs. So you can use either MDX or SQL" Is UDM something that sits above cubes? Or are they the same thing? I presume I would develop cubes with the Cube Designer application; what would I develop a UDM with?

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  • Master Note for Generic Data Warehousing

    - by lajos.varady(at)oracle.com
    ++++++++++++++++++++++++++++++++++++++++++++++++++++ The complete and the most recent version of this article can be viewed from My Oracle Support Knowledge Section. Master Note for Generic Data Warehousing [ID 1269175.1] ++++++++++++++++++++++++++++++++++++++++++++++++++++In this Document   Purpose   Master Note for Generic Data Warehousing      Components covered      Oracle Database Data Warehousing specific documents for recent versions      Technology Network Product Homes      Master Notes available in My Oracle Support      White Papers      Technical Presentations Platforms: 1-914CU; This document is being delivered to you via Oracle Support's Rapid Visibility (RaV) process and therefore has not been subject to an independent technical review. Applies to: Oracle Server - Enterprise Edition - Version: 9.2.0.1 to 11.2.0.2 - Release: 9.2 to 11.2Information in this document applies to any platform. Purpose Provide navigation path Master Note for Generic Data Warehousing Components covered Read Only Materialized ViewsQuery RewriteDatabase Object PartitioningParallel Execution and Parallel QueryDatabase CompressionTransportable TablespacesOracle Online Analytical Processing (OLAP)Oracle Data MiningOracle Database Data Warehousing specific documents for recent versions 11g Release 2 (11.2)11g Release 1 (11.1)10g Release 2 (10.2)10g Release 1 (10.1)9i Release 2 (9.2)9i Release 1 (9.0)Technology Network Product HomesOracle Partitioning Advanced CompressionOracle Data MiningOracle OLAPMaster Notes available in My Oracle SupportThese technical articles have been written by Oracle Support Engineers to provide proactive and top level information and knowledge about the components of thedatabase we handle under the "Database Datawarehousing".Note 1166564.1 Master Note: Transportable Tablespaces (TTS) -- Common Questions and IssuesNote 1087507.1 Master Note for MVIEW 'ORA-' error diagnosis. For Materialized View CREATE or REFRESHNote 1102801.1 Master Note: How to Get a 10046 trace for a Parallel QueryNote 1097154.1 Master Note Parallel Execution Wait Events Note 1107593.1 Master Note for the Oracle OLAP OptionNote 1087643.1 Master Note for Oracle Data MiningNote 1215173.1 Master Note for Query RewriteNote 1223705.1 Master Note for OLTP Compression Note 1269175.1 Master Note for Generic Data WarehousingWhite Papers Transportable Tablespaces white papers Database Upgrade Using Transportable Tablespaces:Oracle Database 11g Release 1 (February 2009) Platform Migration Using Transportable Database Oracle Database 11g and 10g Release 2 (August 2008) Database Upgrade using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007) Platform Migration using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007)Parallel Execution and Parallel Query white papers Best Practices for Workload Management of a Data Warehouse on the Sun Oracle Database Machine (June 2010) Effective resource utilization by In-Memory Parallel Execution in Oracle Real Application Clusters 11g Release 2 (Feb 2010) Parallel Execution Fundamentals in Oracle Database 11g Release 2 (November 2009) Parallel Execution with Oracle Database 10g Release 2 (June 2005)Oracle Data Mining white paper Oracle Data Mining 11g Release 2 (March 2010)Partitioning white papers Partitioning with Oracle Database 11g Release 2 (September 2009) Partitioning in Oracle Database 11g (June 2007)Materialized Views and Query Rewrite white papers Oracle Materialized Views  and Query Rewrite (May 2005) Improving Performance using Query Rewrite in Oracle Database 10g (December 2003)Database Compression white papers Advanced Compression with Oracle Database 11g Release 2 (September 2009) Table Compression in Oracle Database 10g Release 2 (May 2005)Oracle OLAP white papers On-line Analytic Processing with Oracle Database 11g Release 2 (September 2009) Using Oracle Business Intelligence Enterprise Edition with the OLAP Option to Oracle Database 11g (July 2008)Generic white papers Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture (February 2010) Optimizing and Protecting Storage with Oracle Database 11g Release 2 (November 2009) Oracle Database 11g for Data Warehousing and Business Intelligence (August 2009) Best practices for a Data Warehouse on Oracle Database 11g (September 2008)Technical PresentationsA selection of ObE - Oracle by Examples documents: Generic Using Basic Database Functionality for Data Warehousing (10g) Partitioning Manipulating Partitions in Oracle Database (11g Release 1) Using High-Speed Data Loading and Rolling Window Operations with Partitioning (11g Release 1) Using Partitioned Outer Join to Fill Gaps in Sparse Data (10g) Materialized View and Query Rewrite Using Materialized Views and Query Rewrite Capabilities (10g) Using the SQLAccess Advisor to Recommend Materialized Views and Indexes (10g) Oracle OLAP Using Microsoft Excel With Oracle 11g Cubes (how to analyze data in Oracle OLAP Cubes using Excel's native capabilities) Using Oracle OLAP 11g With Oracle BI Enterprise Edition (Creating OBIEE Metadata for OLAP 11g Cubes and querying those in BI Answers) Building OLAP 11g Cubes Querying OLAP 11g Cubes Creating Interactive APEX Reports Over OLAP 11g CubesSelection of presentations from the BIWA website:Extreme Data Warehousing With Exadata  by Hermann Baer (July 2010) (slides 2.5MB, recording 54MB)Data Mining Made Easy! Introducing Oracle Data Miner 11g Release 2 New "Work flow" GUI   by Charlie Berger (May 2010) (slides 4.8MB, recording 85MB )Best Practices for Deploying a Data Warehouse on Oracle Database 11g  by Maria Colgan (December 2009)  (slides 3MB, recording 18MB, white paper 3MB )

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  • Any books or other resources on Cognos TM1?

    - by Alex
    I have been assigned to a project to create a activity based costing system using Cognos TM1. I'm familiar with a number of other OLAP tools but have zero experience with TM1. Can anyone suggest a good book (searching doesn't turn up anything obvious) or any good online resources?

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  • Star schema [fact 1:n dimension]...how?

    - by Mike Gates
    I am a newcomer to data warehouses and have what I hope is an easy question about building a star schema: If I have a fact table where a fact record naturally has a one-to-many relationship with a single dimension, how can a star schema be modeled to support this? For example: Fact Table: Point of Sale entry (the measurement is DollarAmount) Dimension Table: Promotions (these are sales promotions in effect when a sale was made) The situation is that I want a single Point Of Sale entry to be associated with multiple different Promotions. These Promotions cannot be their own dimensions as there are many many many promotions. How do I do this?

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  • Building a Data Warehouse

    - by Paul
    I've seen tutorials articles and posts on how to build datawarehouses with star and snowflakes schemas, denormalization of OLTP databases fact and dimension tables and so on. Also seen comments like: Star schemas are for datamarts, at best. There is absolutely no way a true enterprise data warehouse could be represented in a star schema, or snowflake either. I want to create a database that will server for reporting services and maybe (if that isn't enough) install analisys services and extract reports and data from cubes. My question was : Is it really necesarry to redesign my current database and follow the star/snowflake schemas with fact and dimension tables ? Thank you

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  • How to create a custom ADO Multi Dimensional Catalog with no database

    - by Alan Clark
    Does anyone know of an example of how to dynamically define and build ADO MD (ActiveX Data Objects Multidimensional) catalogs and cube definitions with a set of data other than a database? Background: we have a huge amount of data in our application that we export to a database and then query using the usual SQL joins, groups, sums etc to produce reports. The data in the application is originally in objects and arrays. The problem is the amount of data is so large the export can take 2 hours. So I am trying to figure out a good way of querying the objects in memory, either by a custom OLAP algorithm or library, or ADO MD. But I haven't been able to find an example of using ADO MD without a database behind it. We are using Delphi 2010 so would use ADO ActiveX but I imagine the ADO.NET MD is similar. I realize that if the application data was already stored in a database the problem would solve itself. Also if Delphi had LINQ capability I could query the objects and arrays that way.

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  • How to create a custom ADO Multi Demensional Catalog with no database

    - by Alan Clark
    Does anyone know of an example of how to dynamically define and build ADO MD (ActiveX Data Objects Multidimensional) catalogs and cube definitions with a set of data other than a database? Background: we have a huge amount of data in our application that we export to a database and then query using the usual SQL joins, groups, sums etc to produce reports. The data in the application is originally in objects and arrays. The problem is the amount of data is so large the export can take 2 hours. So I am trying to figure out a good way of querying the objects in memory, either by a custom OLAP algorithm or library, or ADO MD. But I haven't been able to find an example of using ADO MD without a database behind it. We are using Delphi 2010 so would use ADO ActiveX but I imagine the ADO.NET MD is similar. I realize that if the application data was already stored in a database the problem would solve itself. Also if Delphi had LINQ capability I could query the objects and arrays that way.

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  • MDX query- How do I use a member property?

    - by WaggingSiberian
    I'm a complete newb to MDX / OLAP, "data warehousing" in general. I have the following MDX query and would like my results to display the month's number (1 = January, 12 = December). Luckily, the cube creator create a member property named "Month Number Of Year" When I try to run the query, I get the following... "Query (4, 8) The function expects a tuple set expression for the 1 argument. A string or numeric expression was used." Any suggestions for fixing this? Thanks! WITH MEMBER [Measures].[Tmp] as '[Measures].[Budget] / [Measures].[Net Income]' SELECT {[Date].[Month].Properties("Month Number Of Year")} ON COLUMNS, {[Measures].[Budget],[Measures].[Net Income],[Measures].[Tmp]} ON ROWS FROM [AnalyticsCube]

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  • Cannot connect to a SQL Server 2005 Analysis Services cube after installing SQL Server 2008 SP1.

    - by Luc
    I've been developing an application that talks directly to an SSAS 2005 OLAP cube. Note that I also have SQL Server 2008 installed, so the other day I did a Windows Update and decided to include SQL Server 2008 SP1 in my update. After doing that, my SSAS 2005 cube is no longer accessible from my application. I'm able to browse the data just fine within SQL Server 2005 BI Studio Manager, but I'm not able to connect to the cube from my application. Here is my connection string that used to work: Data Source=localhost;Provider=msolap;Initial Catalog=Adventure Works DW Here is the error message I get: Either the user, [Server]/[User], does not have access to the Adventure Works DW database, or the database does not exist. Here is the beginning of my stack trace if it would help: Microsoft.AnalysisServices.AdomdClient.AdomdErrorResponseException was unhandled by user code HelpLink="" Message="Either the user, Luc-PC\\Luc, does not have access to the Adventure Works DW database, or the database does not exist." Source="Microsoft SQL Server 2005 Analysis Services" ErrorCode=-1055391743 StackTrace: at Microsoft.AnalysisServices.AdomdClient.AdomdConnection.XmlaClientProvider.Microsoft.AnalysisServices.AdomdClient.IDiscoverProvider.Discover(String requestType, IDictionary restrictions, DataTable table) at Microsoft.AnalysisServices.AdomdClient.ObjectMetadataCache.Discover(AdomdConnection connection, String requestType, ListDictionary restrictions, DataTable destinationTable, Boolean doCreate) at Microsoft.AnalysisServices.AdomdClient.ObjectMetadataCache.PopulateSelf() at Microsoft.AnalysisServices.AdomdClient.ObjectMetadataCache.Microsoft.AnalysisServices.AdomdClient.IObjectCache.Populate() at Microsoft.AnalysisServices.AdomdClient.CacheBasedNotFilteredCollection.PopulateCollection() at Microsoft.AnalysisServices.AdomdClient.CacheBasedNotFilteredCollection.get_Count() at Microsoft.AnalysisServices.AdomdClient.CubesEnumerator.MoveNext() at Microsoft.AnalysisServices.AdomdClient.CubeCollection.Enumerator.MoveNext() at blah blah... I've looked for a solution for the last 4+ hours and haven't had any success. Thanks in advance for any help. Luc

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  • How can I set PivotField.Calculation in Excel/VSTO?

    - by Kang Su
    I'm trying to set the Calculation property on an OLAP PivotField with VSTO 3.0. For example: pivotField.Calculation = XlPivotFieldCalculation.PercentOf; If I do the above, the value I assign does not stay (Excel appears to revert the change). I suspect the reason is that the BaseField property of the PivotField also needs to be populated (as PercentOf needs a BaseField). But it appears to me that you can't set the BaseField property until you've set the Calculation property (otherwise you get a COMException). I've tried to set ManualUpdate on the PivotTable to true, but with VSTO this rarely works, as this gets reverted immediately back to false. Note, that this seems to work fine in VBA as you can assign multiple values in a single statement, like this: With ActiveSheet.PivotTables("PivotTable1").PivotFields("[Measures].[Reseller Sales Amount]") .Calculation = xlPercentOf .BaseField = "[Geography].[Geography].[Country]" .BaseItem = "[Geography].[Geography].[Country].&[France]" .NumberFormat = "0.00%" End With But with C#/VSTO there's no construct like this (that I know of) and I'm stuck not able to do something like the above. Further note, Calculation values that don't require a BaseField, e.g., XlPivotFieldCalculation.xlPercentOfTotal, get set just fine. Any help on this would be greatly appreciated!

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  • Crosstab/Cube/Pivot Components for Delphi

    - by Anagoge
    I'm looking for a Delphi VCL crosstab/cube/pivotcube/olap grid component for Delphi 2009, 2010, or XE. I'm willing to sacrifice advanced features to get something open/free (or very cheap if I must) to make it easier to collaborate with any future developers without anyone having to purchase more components than I already use, since this will just be used in one screen. If there isn't anything appropriate out there, I may try to implement something simple on my own. I can live with some fairly basic features: drag and drop to configure dimensions, sort by a column, allow totals/min/max for a column, and (optionally) expand/collapse or drill down to sub-categories. Blazing performance and enterprise scalability are not required, since there should be less than 2000 source rows. There appear to be several decent options in the commercial space (ExpressPivotCube, FastCube, HierCube), but they are all a few hundred dollars. This project already uses existing installations of Excel 2007 and SQL Server 2005/2008, so I might consider leveraging those, though I'd prefer a native Delphi component, if possible. There are also the very old Decision Cube components included in Delphi's Source\xtab directory, but they apparently no longer support unicode compilers (Delphi 2009+), since I got dozens of unicode-related compilation errors while test compiling that source in Delphi XE. Those components also still link to the long-deprecated BDE! Has anyone modified Decision Cube to support unicode/pure-TDataSet? The online tutorials I found were incomplete and silent on the dozens of BDE/unicode compilation errors I see, so I might have to tackle that on my own. Does anyone have suggestions where to start for a free/cheap basic crosstab/pivot grid component?

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  • Database warehouse design: fact tables and dimension tables

    - by morpheous
    I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to seek some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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  • Database warehoue design: fact tables and dimension tables

    - by morpheous
    I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to see some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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  • SSAS Cube reprocessing fails - then succeeds if I try again

    - by EdgarVerona
    So I'm basically brand new to the concept of BI, and I've inherited an existing ETL process that is a two step process: 1) Loads the data into a database that is only used by the cube processing 2) Starts off the SSAS cube processing against said database It seems pretty well isolated, but occasionally (once a week, sometimes twice) it will fail with the following exception: "Errors in the OLAP storage engine: The attribute key cannot be found" Now the interesting thing is that: 1) The dimension having the issue is not usually the same one (i.e. there's no single dimension that consistently has this failure) 2) The source table, when I inspect it, does actually contain the attribute key that it says could not be found And, most interestingly... 3) If I then immediately reprocess the dimensions and cubes manually through SSMS, they reprocess successfully and without incident. In both the aforementioned job and when I reprocess them through SSMS, I am using "ProcessFull", so it should be reprocessing them completely. Has anyone run into such an issue? I'm scratching my head about it... because if it was a genuine data integrity issue, reprocessing the cube again wouldn't fix it. What on earth could be happening? I've been tasked with finding out why this happens, but I can neither reproduce it consistently nor can I point to a data integrity problem as the root cause. Thanks for any input you can provide!

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  • Drill through table does not show correct count when used with a dimension having parent child hiera

    - by Arun Singhal
    Hi All, I have a dimension with parent child hierarchy as shown in code block. The issue i am facing is if i have a filter on parent child dimension then drill through table does not show filtered data instead it shows all the data for that dimension. Here is an example. <Dimension type="StandardDimension" name="page_type_d" caption="Page Type"> <Hierarchy name="page_type_h" hasAll="true" allMemberName="all_page_types" allMemberCaption="All Page Types" primaryKey="id"> <Table name="npg_page_type_view" alias="pt"> </Table> <Level name="Page Type" column="id" nameColumn="display_name" parentColumn="parent_id" nullParentValue="0" type="Integer" uniqueMembers="true" levelType="Regular" hideMemberIf="Never" caption="Page Type"> <Closure parentColumn="parent_id" childColumn="page_type_id"> <Table name="dim_page_types_closure"> </Table> </Closure> </Level> </Hierarchy> Now suppose i have 4 rows in npg_page_type_view table id display_name parent_id 19 HTML 100 20 PDF 100 21 XML 0 100 Total 0 Now suppose in my fact table i have following records id count 19 2 20 3 21 1 Following is my analysis view. Total (HTML and PDF) - 5 HTML - 2 PDF - 3 XML - 1 Now if i add filter(say Total) on this analysis view using OLAP cube. Then my analysis view shows the following. Total (HTML and PDF) - 5 Upto this point everything works fine. Now if i click on 5 (to view drill through table) It shows me data against all page type i.e. HTML, PDF, XML but as per filter it should show only HTML and PDF. Is it an exciting issue or am i doing something wrong here? Please help me.

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  • SSAS: distribution of measures over percentage

    - by Alex
    Hi there, I am running a SSAS cube that stores facts of HTTP requests. The is a column "Time Taken" that stores the milliseconds a particular HTTP request took. Like... RequestID Time Taken -------------------------- 1 0 2 10 3 20 4 20 5 2000 I want to provide a report through Excel that shows the distribution of those timings by percentage of requests. A statement like "90% of all requests took less than 20millisecond". Analysis: 100% <2000 80% <20 60% <20 40% <10 20% <=0 I am pretty much lost what would be the right approach to design aggregations, calculations etc. to offer this analysis through Excel. Any ideas? Thanks, Alex

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  • MDX Except function in where clause

    - by rfders
    Hi, i'm having problem restricting a query in mdx, using except function at where clause. i need to retrieved a set of data but which not in an specific set. Then i created the next query: select {[Measures].[Amount], [Measures].[Transaction Cost], [Measures].[Transaction Number]} ON COLUMNS,{[ManualProcessing].[All ManualProcessings].[MAGNETICSTRIPE], ManualProcessing].[All ManualProcessings].[MANUAL]} ON ROWS FROM [Transactions] where except([Product].[All Products].Children,{[Product].[All Products].[Debit}) apparently this works fine, but when i try to add another restriction to slicer, i got this error: No function matches signature (Set,Member). I'm currently working on mondrian 3.1 Is it possible to add multiple restriction to slicer when im sing the except funtion ? are there any other way to get this ? thanks in advance.

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