High-performance data architecture for global operations. That’s engineering.
With 150+ facilities and R&D centers spread across the world, this global Tier 1 wanted to create a high-performance digital network that enabled collaboration between teams and helped them engineer competitive products. Tata Technologies leveraged its manufacturing domain knowledge to migrate legacy systems into a high-performance environment.Challenge
The customer was looking to complete correct and clean data download and upload into the cloud in a limited time. However its multi-site legacy system with different latency was a deterrent in achieving this. Moreover, poor data standard from legacy systems, regional differences in system settings, and multi-language data were some key challenges faced by the customer. A major task at hand was to build a source system architecture understanding to fetch the physical data without compromising on data security. The data was complex, from disparate sources, with no proper structuring. To develop the hi-end comprehensive data management system framework, the customer chose Tata Technologies, a recognized global leader in digital engineering services for the automotive sector.
Solution
Aligning with the post-pandemic imperatives for OEMs to transform their operations for remote collaboration, we carried out a source to staging metadata extraction & transformation and created source vault to stage cloud data download. For data extraction and transformation, our team leveraged SQL Server Integration Services (SSIS) tool. We also provided our expertise in end-to-end product lifecycle management capabilities spanning from PLM implementation, integration, and migration to training & support.
We developed a multi-thread concept for physical data download according to the latency of the servers. To address standard data issues and regional differences, we carried out source data cleanliness. Our technical experts conducted a multiple data extraction to understand the data change trend and find the differential data.
The modular data extraction framework could be connected to any database, substantially reducing the need for further development for the customer. The complete migration of legacy systems resulted in a high performing environment. More than 53 terabytes of engineering data was migrated, spanning multiple applications, with data of approximately 2500+ users being extracted in 8 hours.
With the successful execution of the project, we have established a multi-year engagement with the customer, to provide application maintenance and support till Dec-2026.
