The concept of the semantic layer is almost as old as the BI tools themselves. Earlier, each BI tool had its own semantic layer and was used by specific teams within the enterprise. Those were the days of data silos and moderate data volumes. However, as volumes increased, enterprises began to consolidate all their data on modern data platforms while business users continued to use their existing, familiar BI tools. Multiple versions of business logic in each BI tool often led to different interpretations of the same data. And, that’s why it became important to create a single data view or semantic layer across BI tools and business teams. Before we discuss why you need a semantic layer and how you can build one that can handle future data workloads, let us first understand what it means.
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