Travers – Data and AI
SQL migration services for metalworking tools distributor
Industrial Supplies and Metalworking tools
- SQL Migration
- .NET (middleware)
A 98-year-old manufacturer and supplier
of metal parts for machine shops
Founded in 1924, Travers provides product selection and expert application support for machine shops and metalworking. Travers offers over 500,000 tools from more than 800 brands and holds a vast range of Made-in-USA products. Their product portfolio includes end mills, calipers, abrasives, micrometers, drills, deburring tools, boring bars, and more. The brand also offers services like calibration, re-sharpening and technical support.
Travers' database had not been upgraded in quite some time. The migration, which involved moving from version 2008 to 2019, posed significant challenges due to the SQL server's critical role in managing the following key business functions
Aggregate data from ERP using SSIS packages, for faster access from eCommerce frontend
Process cubes for SQL Server Analysis Server (SSAS)
Deliver reports through SQL Server Reporting Services (SSRS)
Provide access via linked servers for internal access and direct exposure for third parties
During the discovery phase, team Ziffity analyzed the brand’s current SQL setup and identified areas to be addressed prior to staging a migration.
During the auditing phase, Ziffity identified the list of internal and external systems accessing the server by scripting an audit log. Also, we figured out the access patterns through which the several systems communicated with the server.
The audit log provided a clear idea of the access mechanism of the external systems interacting with the server. This crucial information helped us minimize the SQL server migration downtime, schedule it during the right time interval, and proactively inform our client to notify their customers beforehand.
The different access mechanisms posed a challenge in identifying the packages and code elements that used these linked servers. Ziffity came up with a Python-based Explorer to overcome the challenge.
Accelerating SQL Migration
After preparing for the migration using the above measures, we could accelerate the SQL server migration with an appropriate downtime. The migration was verified using automated data comparison between the source and target states.