Data Catalog, Semantic Layer, and Data Warehouse:
Analytics at the core is using data to derive insights for measuring and improving business performance [1]. To enable effective management, governance, and utilization of data and analytics, an increasing number of enterprises today are looking at deploying the data catalog, semantic layer, and data warehouse. But what exactly are these data and kuwait whatsapp number data analytics tools and what value do they offer in improving the business performance of the firm?
What Is a Data Warehouse?
A data warehouse or enterprise data warehouse (EDW) is a system that aggregates data from different source systems into a single, central, consistent data store to support data analytics and artificial intelligence (AI). Data warehouses are commonly used primarily for combining data from one or more sources, reducing load on operational systems, tracking historical changes in data, and providing a single source of truth.
Historically, the data in the EDWs are organized as the star schema and the snowflake schema data structures.
Star schema consists of one central fact table, which can be joined to several denormalized dimension tables. It is considered the simplest and most common type of schema, and its users benefit from its faster speeds while querying.