With the Snowflake model, dimension analysis is easier. For example, “How many accounts or campaigns are online for a given advertiser?” The Star schema model is useful for metrics analysis, such as “What is the revenue for a given customer? Snowflake schemas offer the following benefits compared to normal star schemas: Compatible with many OLAP database modeling tools: Certain OLAP database tools, which data scientists use for data analysis and modeling, are specifically designed to work snowflake data schemas. Saves on data storage requirements: Normalizing the data that would typically be denormalized in a star schema can offer a tremendous reduction in disk space requirements. Essentially, this is because you're converting long strings of nonnumerical data (the information pertaining to descriptors and names) into numerical keys that are dramatically less taxing from a storage perspective. Benefits of Star Schemas Star schemas offer the following benefits: Queries are simpler: Because all of the data connects through the fact table the multiple dimension tables are treated as one large table of information, and that makes queries simpler and easier to perform. Easier business insights reporting: Star schemas simplify the process of pulling business reports like as-of-as and period-over-period reports. Better-performing queries: By removing the bottlenecks of a highly normalized schema, query speed increases, and the performance of read-only commands improves. Provides data to OLAP systems: OLAP (Online Analytical Processing) systems can use star schemas to build OLAP cubes. I would go with Start schema, Want to know detailed information about Star Schema, Check this post.
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