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Analysis Services Training

  1. MSAS - Browsing the Dependency Network
  2. MSAS - Building a Relational Decision Tree Model
  3. MSAS - Introduction to Data Mining
  4. MSAS - Applying security to a Dimension
  5. Tutorial 65: MSAS - Managing Cube Roles
  6. MSAS - Understanding Database Roles
  7. MSAS - Securing User Authentication
  8. MSAS - Introducing Analysis Services Security
  9. MSAS - Writebacks
  10. MSAS - Defining and Creating Drillthrough
  11. MSAS - Defining and Creating Auctions
  12. MSAS - Creating and Maintaining Calculated Members in Virtual Cubes
  13. MSAS - Building a Virtual Cube
  14. MSAS - Understanding Virtual Cubes
  15. MSAS - Introducing Solve Order
  16. MSAS - Implementing Calculations Using MDX Part 2
  17. MSAS - Implementing Calculations Using MDX Part 1
  18. MSAS - Merging Partitions
  19. MSAS - Introduction and Managing Partitions
  20. MSAS - Troubleshooting Cube Processing
  21. MSAS - Optimizing Cube Processing
  22. MSAS - Processing Dimensions and Cubes
  23. MSAS - Introducing Dimension and Cube Processing
  24. MSAS: Optimization Tuning Part 2
  25. MSAS: Optimization Tuning Part 1
  26. MSAS: Usage-Based Optimization
  27. MSAS: Analysis Services Aggregations
  28. MSAS: The Storage Design Wizard
  29. MSAS: Analysis Server Cube Storage
  30. MSAS: Defining Cube Properties
  31. MSAS: Introduction and Working with Measures
  32. MSAS: Introduction and Working with Cubes
  33. MSAS: Virtual Dimensions
  34. MSAS: Introducing Member Properties
  35. MSAS: Creating Custom Rollups
  36. MSAS: Creating a Time Dimension
  37. MSAS: Understanding Hierarchies
  38. MSAS: Dimension Storage Modes and Levels
  39. MSAS: Working with Levels and Hierarchies
  40. MSAS: Working with Parent-Child Dimensions
  41. MSAS : Basics of Levels
  42. MSAS : Working with Standard Dimensions
  43. MSAS : Shared vs Private Dimensions
  44. Understanding Dimension Basics
  45. MSAS : Office 2000 OLAP Components
  46. MSAS : Client Architecture
  47. MSAS : Cube Storage options
  48. MSAS : Meta data Repository
  49. MSAS : Analysis services Tools for Extended Functionality
  50. MSAS : The Wizards
  51. MSAS : The Analysis Manager and Analysis Server
  52. MSAS : The Data warehousing framework of SQL Server 2000 - Part 2
  53. MSAS : The Data warehousing framework of SQL Server 2000 - Part 1
  54. MSAS : Microsoft Data Warehousing Overview
  55. MSAS : Browsing the Cube
  56. MSAS : Designing Storage and Processing the Cube
  57. MSAS : Building the Cube Part #3
  58. MSAS : Building the Cube Part #2
  59. MSAS : Building the Cube Part #1
  60. MSAS : Setting up the Database in Analysis Server
  61. MSAS : Preparing to Create the Cube
  62. MSAS : Introducing Analysis Manager Wizards
  63. Microsoft Analysis Services Installation
  64. MSAS - Applying OLAP Cubes
  65. Understanding OLAP Models
  66. Designing the Dimensional Model and Preparing the data for OLAP
  67. Design of the data warehouse: Kimball Vs Inmon
  68. Defining OLAP Solutions and Data Warehouse design
  69. Microsoft Analysis Services Training
  70. Data Warehouse database and OLTP database
  71. Introduction to Data Warehousing

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MSAS - Defining and Creating Drillthrough

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Author : Exforsys Inc.     Published on: 26th Apr 2005
Actions used by end users to select a single cube cell and retrieve a result set from the source data of the cell are known as Drillthrough actions. Drillthrough has to be enabled if administrators want to drillthrough in a Cube Browser and the Cube Editor data tab.

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The DrillThrough operations are extremely useful when the user wants to look at the underlying causes for some abnormally high or low outputs in specific fields. For example, let us say a store is doing extremely well and the sales in that store is showing increase in a particular month. The Administrator would like to examine the reasons for this high sales figure and find out if there is any specific reason why this store is doing extremely well when compared to other stores in the region. He will then look at details of the sales in the particular store. Let us say that the sales in this store became abnormally high during the month of July---specifically--the sale of umbrellas. On deeper examination it was found that the sale was at a peak during the last fortnight of July. Then the Administrator could discover that during this period there was an unusual spell of rains and hence the increase in the sale of umbrellas. He would then conclude that the sale was a seasonal one and not to be examined further. However, if the increase in sales happened due to the extraordinary efforts or campaigns undertaken by the store, he would definitely like to study it and take action to replicate the campaign in the other stores and for other months if possible.

Nevertheless, it must be noted that he data in the Data warehouse goes through a process of Extraction, Transformation and loading. Pre-aggregations of data and summarization of data takes place before the data is ready for use in fact tables. The cubes are constructed using the fact tables and dimensions in the database. Therefore, the data that is actually available for Drill through in the Data warehouse is the data that has been pre aggregated, transformed or summarized in different ways. The data that is displayed at drillthrough is actually the data in the fact table. Though this makes for speed and accuracy of presentation, it loses out on the depth of detail that is available in the Online Transaction Processing (OLTP) database. Analysis of the kind illustrated above may not always be possible with the data available in the fact tables.

Drillthrough operations also require that the Client supports the Drillthrough operations. Clients such as the Cube Browser or applications that use COM interface of SQL Server 2000 Analysis Services libraries will be able to Drillthrough to the raw data from the OLAP cube to which they are connected.

The table rows have to be evaluated to the calculated value of the selected cube cell if the drillthrough result set is to be derived. For instance if a selected cube is a three dimensional cube and the intersection of the dimensions puts the values 1998 and Mexico into the cell and is sliced by All Customers and the measure used is Sales, the resulting data set from a drillthrough would be generated only if the fact table rows relate to both 1998 and Mexico--the time dimension table rows store 1998; the Location dimension table rows must store Mexico and all rows of the Customer dimension table. The result set will be summarized by the joins in the Cube’s schema.

Drillthrough is not supported for cells that have values based on expressions such as calculated member cells or ones that are associated with Custom Member formulas. Cells having values for the level members of a mining model dimension also cannot be drilled through.

Permissions to Drillthrough are granted by the Administrator in the Cube Role Manager. To enable or disable Drillthrough of a cube, users will have to Click the Drillthrough options in the Tools menu of the Cube Editor or the Virtual Cube Editor and check or uncheck the Enable Drillthrough check box. The Columns tab will permit the user specify the columns on which the drillthrough will have to be displayed. Drillthrough can be tested by right clicking on a cell in the cube and Clicking on Drill Through.

To specify drillthrough options for a regular cube

In the Analysis Manager tree pane, under the database that contains the cube, expand the Cubes folder.

Right-click the cube, and then click Edit.

On the Tools menu, click Drillthrough Options. (If this option is not available, the cube structure is not valid. The existence of the problem can be ascertained by clicking Validate Cube Structure on the Tools menu.)

In the Drillthrough Options dialog box, perform one of the following actions:

To enable drillthrough, select the Enable drillthrough check box.

To disable drillthrough, clear the Enable drillthrough check box. Go to Step 7.

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In the Columns tab, select the columns to be displayed when drillthrough is executed.
Please note that selecting a column to which a cube role is denied access and then granting the cube role the ability to drill through, security exposure becomes an issue. (Access to a column can be denied by using dimension security or cell security). When the end users of the cube role drill through, they can access the denied column.

(Optional.) In the Filter tab, specify a filter (WHERE clause expression) to limit the result set returned by drillthrough. Do not include the keyword WHERE. For example, to limit the result set to fourth-quarter data, specify:

"shipment_facts"."quarter"=4

Click OK.

In Cube Editor, on the File menu, click Save.



 
This tutorial is part of a Analysis Services Training tutorial series. Read it from the beginning and learn yourself.

Analysis Services Training

  1. MSAS - Browsing the Dependency Network
  2. MSAS - Building a Relational Decision Tree Model
  3. MSAS - Introduction to Data Mining
  4. MSAS - Applying security to a Dimension
  5. Tutorial 65: MSAS - Managing Cube Roles
  6. MSAS - Understanding Database Roles
  7. MSAS - Securing User Authentication
  8. MSAS - Introducing Analysis Services Security
  9. MSAS - Writebacks
  10. MSAS - Defining and Creating Drillthrough
  11. MSAS - Defining and Creating Auctions
  12. MSAS - Creating and Maintaining Calculated Members in Virtual Cubes
  13. MSAS - Building a Virtual Cube
  14. MSAS - Understanding Virtual Cubes
  15. MSAS - Introducing Solve Order
  16. MSAS - Implementing Calculations Using MDX Part 2
  17. MSAS - Implementing Calculations Using MDX Part 1
  18. MSAS - Merging Partitions
  19. MSAS - Introduction and Managing Partitions
  20. MSAS - Troubleshooting Cube Processing
  21. MSAS - Optimizing Cube Processing
  22. MSAS - Processing Dimensions and Cubes
  23. MSAS - Introducing Dimension and Cube Processing
  24. MSAS: Optimization Tuning Part 2
  25. MSAS: Optimization Tuning Part 1
  26. MSAS: Usage-Based Optimization
  27. MSAS: Analysis Services Aggregations
  28. MSAS: The Storage Design Wizard
  29. MSAS: Analysis Server Cube Storage
  30. MSAS: Defining Cube Properties
  31. MSAS: Introduction and Working with Measures
  32. MSAS: Introduction and Working with Cubes
  33. MSAS: Virtual Dimensions
  34. MSAS: Introducing Member Properties
  35. MSAS: Creating Custom Rollups
  36. MSAS: Creating a Time Dimension
  37. MSAS: Understanding Hierarchies
  38. MSAS: Dimension Storage Modes and Levels
  39. MSAS: Working with Levels and Hierarchies
  40. MSAS: Working with Parent-Child Dimensions
  41. MSAS : Basics of Levels
  42. MSAS : Working with Standard Dimensions
  43. MSAS : Shared vs Private Dimensions
  44. Understanding Dimension Basics
  45. MSAS : Office 2000 OLAP Components
  46. MSAS : Client Architecture
  47. MSAS : Cube Storage options
  48. MSAS : Meta data Repository
  49. MSAS : Analysis services Tools for Extended Functionality
  50. MSAS : The Wizards
  51. MSAS : The Analysis Manager and Analysis Server
  52. MSAS : The Data warehousing framework of SQL Server 2000 - Part 2
  53. MSAS : The Data warehousing framework of SQL Server 2000 - Part 1
  54. MSAS : Microsoft Data Warehousing Overview
  55. MSAS : Browsing the Cube
  56. MSAS : Designing Storage and Processing the Cube
  57. MSAS : Building the Cube Part #3
  58. MSAS : Building the Cube Part #2
  59. MSAS : Building the Cube Part #1
  60. MSAS : Setting up the Database in Analysis Server
  61. MSAS : Preparing to Create the Cube
  62. MSAS : Introducing Analysis Manager Wizards
  63. Microsoft Analysis Services Installation
  64. MSAS - Applying OLAP Cubes
  65. Understanding OLAP Models
  66. Designing the Dimensional Model and Preparing the data for OLAP
  67. Design of the data warehouse: Kimball Vs Inmon
  68. Defining OLAP Solutions and Data Warehouse design
  69. Microsoft Analysis Services Training
  70. Data Warehouse database and OLTP database
  71. Introduction to Data Warehousing
 

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