A new PLUS tool increases efficiency.
The Insight team began with a discovery session, performing an in-depth analysis of the database within Azure Synapse to evaluate how the client was currently using the platform’s functions and features. They identified significant opportunities for optimization by taking advantage of newly available capabilities that would improve processing speeds and reduce consumption costs.
As the scope of work was being agreed upon, an Insight data architect began documenting the various aspects of the database which would need to be corrected or aligned to best practices. He realized the required optimizations would call for a significant amount of repetitive, manual labor.
To improve efficiency, the architect began developing a utility tool that would automate a significant portion of the database analysis and provide recommended changes in a script-based format to improve the client’s data environment.
The tool, dubbed the Performance and Learning Utility for Synapse (PLUS), was designed to collect metadata from tables within the database, including table type, row and column definitions, indexes and partitioning. It could also analyze how data was being queried and stored. Based on this information, PLUS then programmatically applied Microsoft® best practices to make recommendations for improved efficiency.
By the time the client’s initiative was ready to begin, a preliminary version of the tool had been finalized.
PLUS enabled a single Insight data architect to perform the work of a team, reducing the time and costs associated with the optimization project. The architect used PLUS to collect and track ongoing table types, storage options, indexing columns and data volumes, as well as collecting and analyzing the query workload. The tool identified and provided recommendations for resolving the majority of the manufacturer’s most common database issues, allowing Insight’s architect to focus on the more challenging problems.
After the application of PLUS, the Insight team implemented recommended changes and best practices to optimize the client’s data environment. 80 changes to table types and storage were applied by Insight’s architect, while PLUS was used to compress 66 tables that had been identified as frequently having uncompressed rows. Maintenance scripts were also provided to the client’s IT team to enable them to address this issue long term.