Data Warehouse and Data Lakes - Overview PDF
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Summary
This document provides an overview of data warehousing and data lakes. It covers topics such as objectives for data warehouses, different data warehouse architectures and types of schemas to design data warehouses with.
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Chapter 4 Objectives In summary Objectives In summary In summary In Summary STAR SCHEMA AND SNOWFLAKE SCHEMA Why do we use these schemas, and how do they differ? Star schemas are optimized for reads and are widel...
Chapter 4 Objectives In summary Objectives In summary In summary In Summary STAR SCHEMA AND SNOWFLAKE SCHEMA Why do we use these schemas, and how do they differ? Star schemas are optimized for reads and are widely used for designing data marts, whereas snowflake schemas are optimized for writes and are widely used for transactional data warehousing. A star schema is a special case of a snowflake schema in which all hierarchical dimensions have been denormalized, or flattened star and snowflake schema attributes. Attribute Star schema Snowflake schema Read speed Fast Moderate Write speed Moderate Fast Storage space Moderate to high Low to moderate Data integrity risk Low to moderate Low Query complexity Simple to moderate Moderate to complex Schema Simple to moderate Moderate to complexity complex Dimension Denormalized Normalized over hierarchies single tables multiple tables Joins per One One per level dimension hierarchy Ideal use OLAP systems, OLTP systems Data Marts In Summary
