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Multidimensional Database in Context of DB2 OLAP Server Khang Pham Class: CSCI397-16C Instructor: Professor Renner.

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Presentation on theme: "Multidimensional Database in Context of DB2 OLAP Server Khang Pham Class: CSCI397-16C Instructor: Professor Renner."— Presentation transcript:

1 Multidimensional Database in Context of DB2 OLAP Server Khang Pham Class: CSCI397-16C Instructor: Professor Renner

2 Why Multidimensional Database Need of a business model Quick access to data Need of view data

3 DB2 OLAP SERVER Provide an abstraction of a multidimensional database on top of relational storage. Allowing quick access to data. Reliable storage. Close integration with warehouse data.

4 Architecture: Consist of 3 major components: 1) Application Manager and Excel Plug-in 2) Essbase Server 3) DB2

5 Example (page1) Application Manager: Build the Model

6 Example (page2) Application manager: import data

7 Example (page 3) Text Data File

8 Example (page 4) Application Manager: calculate data

9 Example (Page 5) Excel Plug-in: showing data

10 Storage Manager Functionality Implementation - Overview - Concept of Dense and Sparse dimension - Star Schema - Actual Storage

11 Overview: mapping multidimensional data to linear data. Physical storage are linear. We have to map multidimensional data to linear data in order to store it. Approach: - An array x[width][height] can be stored as x[width*height]. - Indexing element x[m][n] can be treated as indexing x[m*width+n] - Expanding this concept to store multidimensional data

12 Dense and Sparse Concept Structures are too big to store Mostly are missing data cells Idea: don’t store missing data cells Dense Dimension: densely populated Sparse Dimension: sparsely populated Block: data block made of dense dimensions Only allocate block that has data Index data block by sparse dimensions Greatly reduce storage space

13 Star Schema Consists of one central table that holds all the data -- Fact table. Surrounded by dimension tables. Joint dimension table and fact table to get the view of data on this dimension. DB2 is optimized for executing these joint query.

14 Actual Storage The structure of fact table - Columns consist of:. All members of one chosen dimension.. Key columns (one per sparse dimension). - Key composed of the key columns

15 Summary A Great business solution - Quickly build your model - Quickly get to your business decision Multidimensional view of data - Locating data of interest - Making report, statistics...etc. Have all relational features - Select, replicate, back up...etc.

16 References Websites: http://www-4.ibm.com/software/data/db2/db2olap/ http://www-4.ibm.com/software/data/db2/ http://www.software.ibm.com/ http://www.hyperion.com/essbaseolap.cfm Books and writings: Arbor Essbase Version 5: Database Administrator's Guide Volume I, copyright 1991-1997 Arbor Software Corporation, P/N: 06070-500000-000. Arbor Essbase Version 5: Database Administrator's Guide Volume II, copyright 1991-1997 Arbor Software Corporation, P/N: 06071-500000-000. DB2 OLAP Server Fundamentals, copyright 1998 IBM corporation. IBM DB2 OLAP Server: Using DB2 OLAP Server (Version 1.0.1), copyright 1998 IBM corporation, SC26-9235-01. Software packages and tutorials: DB2 Universal Database 6.1 Trial Version, copyright IBM Corporation 1999. DB2 OLAP Server 1.1 Trial Version, copyright IBM Corporation 1999.


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