Vorlesung Datawarehousing

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Vorlesung Datawarehousing

• Prof. Rudolf Bayer, Ph.D.
• Institut für Informatik, TUM
• SS 2002

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My Coordinates

• Office Orleansstr. 34, 108
• Tel [phone]
• Secretary Fr. Kollmann 48095 172
• Email bayer_at_in.tum.de
• Hörsaal 3555, Ls. Prof. Schlichter
• Mittw. 1015 und Freitag 1015 in HS 1402
• homepage www3.in.tum.de

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Ch. 1 What is a Datawarehouse?

• Enterprises need 2 different types of data
• OLTP (online transaction processing) for
  operational data of enterprise, e.g. in
  relational DBMS, IMS, SAP/R3, ...
• DSS Decision Support System to store
  data/information for strategic management
  decisions aggregations, summaries, time series,
  time trends, unexpected, exceptional patterns,
  etc.

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DWH Requirements

• Up to date (timely)
• Reliable
• Complete
• Relevant for decisions and presented properly
• Interactive people generate hypotheses,
  computers check hypotheses

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Total View for Management

• Business relevant enterprise data
• Orders, production, deliveries, personnel,
  finances, cash flow, production capacity, moves
  of the competition
• All above data integrated in DWH schema
• Loading of DWH?
• Data cleansing
• Data transformations, conversions e.g DM, US,
  S, , LIT, etc.

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DWH Requirements Market

• Large volumes of data, 10 GB
• Very ambitious analyses
• Interactive?
• Market size 1995 Europe
• 4.4 billion (Milliarden) US
• 25 SW
• 33 HW
• 42 projects
• 95 of companies plan DWH
• Growing 25 - 30 annually

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Typical DWH Analyses/Queries

• What are the consequences of new orders for
  production capacity w.r. to investment,
  personnel, maintenance, extra hours, ...
• Seasonal adaptions, e.g. when to produce how many
  skis, bikinis, convertibles, ...
• Influence of external financing on profits