Summary
In this chapter, we discussed how the semantic layer is used to create a more performant layer for reporting. We learned the semantic layer can be implemented using either multidimensional or tabular models. Multidimensional models are based on the concept of cubes and provide analytical capabilities by aggregating the data. Tabular models, on the other hand, utilize a columnar in-memory technology known as the VertiPaq engine, which enables faster processing and compression. Tabular models are well suited for scenarios where fast query performance and self-service analytics are paramount.
The VertiPaq engine was explained as a key component of tabular models and powers their impressive performance capabilities. By leveraging in-memory storage and columnar data structures, the VertiPaq engine optimizes data compression and enables efficient query execution. This engine plays a significant role in the success of tabular models, allowing for interactive and near-real-time...
