How can schema design improve query performance?
Schema design is a crucial aspect of data warehousing that affects how efficiently you can query and analyze your data. Different schemas have different trade-offs between storage space, data quality, and query performance. In this article, you will learn how to choose and implement two common schema designs for data warehousing: star and snowflake schemas.
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Normalize data structures:A snowflake schema organizes data into sub-dimension tables, reducing redundancy and improving data integrity. This meticulous arrangement can enhance query performance in complex datasets.
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Optimize for clarity:Implementing a star schema streamlines your database, making it easier to navigate and understand. By directly connecting each dimension to the fact table, queries run faster, which is especially beneficial for smaller data sets.