Best of Data Warehouse — July 2024

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   Article

   Substack·2y

   Data pipelines and SCDs

   Designing backfillable data pipelines using idempotent transformation code avoids the complications of ad-hoc SQL. When handling Slowly Changing Dimensions (SCDs), SCD Type 2 is preferred for its immutability and compressive qualities, though it involves complex surrogate key lookups. Alternatively, snapshot tables offer a simpler, reproducible model at the cost of higher data replication, making them ideal in cloud environments where storage is cheaper than engineering time.

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2. 2
   Article

   Towards Data Science·2y

   Data Modeling Techniques For Data Warehouse

   Data modeling is a key process in creating conceptual representations of organizational data and its relationships. Focusing on various methodologies like Kimball's, Inmon's, and Data Vault, this guide provides insights into dimensional modeling, including benefits like simplicity, improved query performance, and scalability. It also covers different schema types (star and snowflake), and strategies for data loading. Special attention is given to innovative approaches like using one big table (OBT) for modern data warehouses.

   19
3. 3
   Article

   Data Science Central·2y

   Role of AI in Building Data Warehouses

   Leveraging AI in data warehousing offers multiple benefits including automation, enhanced efficiency, improved data quality, and optimization of the querying process. It aids in data integration, modification, and ETL processes while ensuring consistent and reliable data. AI enhances security by detecting unusual behaviors and helps in scaling the data warehouse seamlessly with cloud integration.

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