Lecture 05A

© 2010 SAP AG

Module BI1-M2 Data Warehouse Architecture

BI Platform: Data Warehousing

Architecture Alternatives

Conceptual Layers

SAP University Alliances Version 1.0

Author Lorraine Gardiner

Paul Hawking

Robert Jovanovic

ProductNone

FocusData warehousing overview

SAP BI Curriculum

BI1-M2 Data Warehouse Architecture

SAP University Alliances

© 2010 SAP AG

Agenda

• BI Platform: Data Warehousing• Architecture Alternatives• Conceptual Layers

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Common BI Architecture

Source: Eckerson, W. (May 2006). Business intelligence 2006 – only the beginning. What Works: Best Practices in Business Intelligence and Data Warehousing, 21.

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Data Warehousing: Single Version of the Truth

“The truth, the whole truth, and nothing but the truth …”

Source: Inmon, B. (September 9, 2006). The single version of the truth. Business Intelligence Network. Retrieved February 22, 2008 from http://www.b-eye-network.com/view/282

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Extraction – Transformation – Load (ETL)

Source: Data warehouse framework. BiPM Institute. Retrieved February 22, 2008 from http://bipminstitute.com/template/topic.php?topic_id=DAC

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Agenda


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© 2010 SAP AG

Source: Sen, A., & Sinha, A. P. (January 2007). Toward developing data warehousing standards: an ontology-based review of existing methodologies. IEEE Transactions on Systems, Man, and Cybernetics. 37, 17-31.

Data Warehousing Architecture Alternatives

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Standard Practices for Architecture Design

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Standard Practices for Data Modeling

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Agenda


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Data Warehousing Conceptual Layers

Source: Architecture of a data warehouse. SAP AG. Retrieved February 22, 2008 from http://help.sap.com/saphelp_nw70/helpdata/en/43/4a86b4224847b6e10000000a11466f/content.htm

Any Source

(Persistent) Staging Area

Data Warehouse

(Architected) Data Marts

OperationalData Store

Access to Information

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Persistent Staging Area (PSA)

• Storage area for data extracted from sources

• Requested data is saved directly from its source (without changes)

• First step in loading data into the operational data store (ODS) or data warehouse

Any Source


Data Warehouse

(Architected) Data MartsOperationalData Store


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Operational Data Store (ODS)

• Operational reporting• Granular data• Volatile, near real

time• May feed Data

Warehouse layer at set intervals

Any Source


Data Warehouse



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Data Warehouse

• Historical foundation for BI

• Granular data• Integrated• Nonvolatile• Application neutral Any Source


Data Warehouse



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(Architected) Data Marts

• Focus: Information needs of a business unit or function

• Often aggregated, may be granular

• Often dimensional data models Any Source


Data Warehouse



Lecture 05A

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Transcript of Lecture 05A