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Data Warehousing Concepts and Design

Data Warehousing Concepts and Design. Chapters 31 & 32 in textbook. What is Data Warehousing?. A subject-oriented, integrated, time-variant and non-volatile collection of data. Supports decision-making process. Benefits: Potential high returns on investment. Competitive advantage.

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Data Warehousing Concepts and Design

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  1. Data Warehousing Concepts and Design Chapters 31 & 32 in textbook

  2. What is Data Warehousing? • A subject-oriented, integrated, time-variant and non-volatile collection of data. • Supports decision-making process. • Benefits: • Potential high returns on investment. • Competitive advantage. • Increased productivity of corporate decision-makers.

  3. OLTP vs. DW

  4. DW Architecture

  5. Data Warehousing Design • DW Design depends on the questions that managers impose on a DW. • The data itself gets • Extracted from OLTP systems. • Cleaned to get rid of redundancy and missing values. • Stored in a warehouse. • In step 3, we design the DW.

  6. Dimensionality Modeling (DM) • DM = ER modeling with restrictions. • Each design consists of • 1 Fact Table: group of foreign keys. • Many Dimensional Tables: each has a primary key corresponding to a foreign key in fact table. • A join between all tables  the whole un-normalized DB. • Popular schemas • Star. • Snowflake. • Starflake.

  7. Example Star Schema

  8. DW Design Methodology • Choosing the process. • Choosing the grain. • Identifying the dimensions. • Choosing the facts. • Storing pre-calculations. • Rounding-out the dimension tables. • Choosing the duration of the DB. • Tracking slowly changing dimensions. • Deciding query priorities and modes.

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