11.7. CHAPTER SUMMARY

• Slowly changing dimensions may be classified into three different types based on the nature of the changes. Type 1 relates to corrections, Type 2 to preservation of history, and Type 3 to soft revisions. Applying each type of revision to the data warehouse is different.

• Large dimension tables such as customer or product need special considerations for applying optimizing techniques.

• "Snowflaking" or creating a snowflake schema is a method of normalizing the STAR schema. Although some conditions justify the snowflake schema, it is generally not recommended.

• Miscellaneous flags and textual data are thrown together in one table called a junk dimension table.

• Aggregate or summary tables improve performance. Formulate a strategy for building aggregate tables.

• A set of related STAR schemas make up a family of STARS. Examples are snapshot and transaction tables, core and custom tables, and tables supporting a value chain or a value circle. A family of STARS relies on conformed dimension tables and standardized fact tables.