Integration and Reuse of Heterogeneous Information Hetero-Homogeneous Data Warehouse Modeling in the CWM

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1 Integration and Reuse of Heterogeneous Information Hetero-Homogeneous Data Warehouse Modeling in the CWM Christoph Schütz, Bernd Neumayr, Michael Schrefl

2 Overview Background Data Warehousing and OLAP Hetero-Homogeneous Data Warehouse Hetero-Homogeneous Modeling in the CWM Logical Modeling Physical Modeling Implementation Summary and Future Work 2

3 Data Warehousing and OLAP, Hetero-Homogeneous Modeling BACKGROUND 3

4 Data Warehousing and OLAP Cube of data 4

5 Data Warehousing and OLAP Dimensions 5

6 Data Warehousing and OLAP Dimensions are hierarchically organized. Dimensions 6

7 Data Warehousing and OLAP Measure Fact / Cell 7

8 Data Warehousing and OLAP Dice operation France 8

9 Data Warehousing and OLAP The dice operation selects a sub-cube with a reduced set of cells. 9

10 Data Warehousing and OLAP USA 10

11 Data Warehousing and OLAP 11

12 Data Warehousing and OLAP Multi-granular Heterogeneous 12

13 Hetero-Homogeneous Data Warehouse 13

14 Hetero-Homogeneous Data Warehouse Globally heterogeneous model Measures may be defined at multiple levels of granularity Different parts of the cube may have different measures Homogeneous local models For each sub-cube, a hetero-homogeneous model defines a homogeneous schema This homogeneous schema defines the common denominator of all cells within a sub-cube. 14

15 Logical Modeling, Physical Modeling HETERO-HOMOGENEOUS MODELING IN THE CWM 15

16 Hetero-Homogeneous Modeling in the CWM Multilevel objects (m-objects) can be used for the conceptual modeling of hetero-homogeneous data warehouses How to use hetero-homogeneous data with existing tools? The Common Warehouse Metamodel (CWM) is a standardized way for modeling data warehouses Administered by the Object Management Group (OMG) Based on OMG s UML and MDA (= Model-driven architecture) The logical model describes cubes and dimensions The physical model maps the logical model to the database In our case, it is a relational database 16

17 Logical Model Heterogeneous global schema Union of the various sub-schemas 17

18 Logical Model Homogeneous local schemas 18

19 Physical Model 19

20 Physical Model Fact table 20

21 Physical Model Dimension tables 21

22 Physical Model Heterogeneous fact table 22

23 Physical Model < Model, Month, City > 23

24 Physical Model < Model, Month, Store > 24

25 Physical Model < Category, Year, City > 25

26 Physical Model Homogeneous views on the heterogeneous fact table 26

27 Physical Model Measures available at finer granularities are aggregated 27

28 Proof-of-Concept Prototype in Oracle, CWM Export IMPLEMENTATION 28

29 Overview 29

30 Overview Management system for hetero-homogeneous data warehouses in Oracle 11g Implemented as stored procedures using PL/SQL Stores the conceptual model in object-relational tables, based upon m-objects Provides basic analysis functionality Also provides an export mechanism Parts of the export mechanism are executed locally Generation of CWM/XMI in Java, using Pentaho metadata Export of actual data runs on the database server 30

31 Summary and Future Work We extend our implementation for managing heterohomogeneous data warehouses with an export mechanism This export mechanism to CWM should facilitate the reuse of hetero-homogeneous data in other tools Future work: Empirical evaluation (user studies) of the usability of hetero-homogeneous data warehouses Definition of the transformation process from the conceptual model to the logical and physical models according to OMG s model-driven architecture (MDA) 31

32 References Neumayr, B., Schrefl, M. and Thalheim, B. (2010) Heterohomogeneous hierarchies in data warehouses, APCCM 10. Poole, J., Chang, D., Tolbert, D. and Mellor, D. (2003) Common Warehouse Metamodel developer s guide. Schütz, C. (2010) Extending data warehouses with heterohomogeneous dimension hierarchies and cubes: A proof-of-concept prototype in Oracle, Master s thesis, JKU Linz. 32

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