Data Warehousing Architectures Issues to consider when deciding which architecture to use Which database management system(DBMS)should be used? Will parallel processing and/or partitioning be used? Will data migration tools be used to load the data Warenouse ? What tools will be used to support data retrieval and analysis? Pearson Copyright C 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved
Copyright © 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved Data Warehousing Architectures • Issues to consider when deciding which architecture to use: – Which database management system (DBMS) should be used? – Will parallel processing and/or partitioning be used? – Will data migration tools be used to load the data warehouse? – What tools will be used to support data retrieval and analysis?
A Web-based dw architecture Web pages Application Server Client Web (Web browser) Internet Server Intranet/ Extranet Data warehouse Pearson Copyright C 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved
Copyright © 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved A Web-based DW Architecture Web Server Client (Web browser) Application Server Data warehouse Web pages Internet/ Intranet/ Extranet
Alternative DW Architectures (1 of2 (a) Independent Data Marts Architecture Staging Independent data marts End user Source Systems Area (atomic/summarized data) access and applications (b) Data Mart Bus Architecture with Linked Dimensional Datamarts End user Y Source Dimensionalized data marts linked by conformed dimentions access and (atomicsummarized data) (c) Hub and Spoke Architecture(Corporate Information Factory) malized rela System Area ouse(atomic applications (summarized/some atomic da Pearson Copyright C 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved
Copyright © 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved Alternative DW Architectures (1 of 2) Source Systems Staging Area Independent data marts (atomic/summarized data) End user access and applications ETL (a) Independent Data Marts Architecture Source Systems Staging Area End user access and applications ETL Dimensionalized data marts linked by conformed dimentions (atomic/summarized data) (b) Data Mart Bus Architecture with Linked Dimensional Datamarts Source Systems Staging Area End user access and applications ETL Normalized relational warehouse (atomic data) Dependent data marts (summarized/some atomic data) (c) Hub and Spoke Architecture (Corporate Information Factory)
Alternative DW Architectures (2 of 2) (d) Centralized Data Warehouse Architecture ET Staging Normalized relational End user Systems Area summarized data applications (e) Federated Architecture Data mapping /metadata End Existing data warehouses ogical physical integration of access and Data marts and legacy systmes common data elements Each architecture has advantages and disadvantages Which architecture is the best? Pearson Copyright C 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved
Copyright © 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved Alternative DW Architectures (2 of 2) Source Systems Staging Area Normalized relational warehouse (atomic/some summarized data) End user access and applications ETL (d) Centralized Data Warehouse Architecture End user access and applications Logical/physical integration of common data elements Existing data warehouses Data marts and legacy systmes Data mapping / metadata (e) Federated Architecture • Each architecture has advantages and disadvantages! • Which architecture is the best?
Ten Factors that Potentially Affect the Architecture selection Decision 1. Information interdependence between organizational units 2. Upper managements information needs 3. Urgency of need for a data warehouse 4. Nature of end-user tasks 5. Constraints on resources 6. Strategic view of the data warehouse prior to implementation 7. Compatibility with existing systems 8. Perceived ability of the in-house it staff 9. Technical issues 10. Social/political factors Pearson Copyright C 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved
Copyright © 2018, 2014, 2011 Pearson Education, Inc. All Rights Reserved Ten Factors that Potentially Affect the Architecture Selection Decision 1. Information interdependence between organizational units 2. Upper management’s information needs 3. Urgency of need for a data warehouse 4. Nature of end-user tasks 5. Constraints on resources 6. Strategic view of the data warehouse prior to implementation 7. Compatibility with existing systems 8. Perceived ability of the in-house IT staff 9. Technical issues 10. Social/political factors