If you can remember my last blog post regarding Vertipaq engine inside SSAS Tabular , I’ve discussed three algorithms which are in use when process the model. Processing in the sense perform data loading from the relational source and load into the tabular structure. In here data compression is taken place in order to save the memory footprint. It is really important because all the data we had in the data warehouse or source relational database after processed the model load into the memory. So by the compression save the huge amount of memory space and it will utilize your hardware optimum way while faster scans because the data model is smaller than the original. These are the steps taking place when we process the tabular model from SSDT or via SQL Server Management Studio. Read the data from the source database and transform into columnar structure or vertipaq data structure while data encoding and compression occurs. Creating of dictionaries and indexes for eac...
A journey towards the AI space