Building an Azure Analysis Services Model on Top of Azure Blob Storage—Part 1
In a comment to a recent blog article, Bill Anton raised a question about the target scenarios for the modern Get Data experience in Tabular 1400 models, especially concerning file-based data sources. So, let’s look at a concrete example from my personal to-do list: Building a Tabular model on top of industry standard synthetic data for testing purposes.
Performance testing and benchmarking is an important part of quality assurance for Analysis Services. A prerequisite is a representative workload and TPC-DS provides such a workload, widely accepted across the industry. It defines a relational database schema and includes tools to generate data files at various scale factors (see TPC-DS on the TPC.org site). It also defines SQL queries to evaluate performance in a replicable way. Of course, for Analysis Services, these SQL queries must be converted to DAX and/or MDX queries, but that’s beside the point. The point is that TPC-DS can generate a large amount of file-based source data, which I want to bring into a Tabular model to enjoy blazing fast query performance.