Data warehouse design patterns are proven solutions for common data modeling, integration, and analysis scenarios. Anti-patterns are common mistakes or bad practices that lead to poor performance ...

The data architect also designs the conceptual, logical, and physical data models, and chooses the appropriate data warehouse design pattern, such as star schema, snowflake schema, or data vault ...

Three-tier Architecture: A three-tier architecture design has a top, middle, and bottom tier; these are known as the source layer, the reconciled layer, and the data warehouse layer. This design ...

When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the ...

The RA Warehouse dbt framework is a set of data models, data transformations and data warehousing design patterns for use with dbt ("Data Build Tool"), an open-source data transformation and ...

By now, every data-driven business understands the value and role of a data warehouse as the central repository of an enterprise’s data, providing a trusted source of data that can be used for ...

In order to resolve the issues with handling of irregular data, standard design patterns are required for data integration. Here are five easy methods: 1. ETL and full integration with data ...