About our client and their challenges:
Our client is a Hong Kong based global alliance of quality management solutions
specialists in textiles and apparel. They have multiple offices across the globe.
Our client used multiple different systems for the inspection and analysis of all products for multiple areas in multiple regions of the world. As the business was widely client was using multiple applications and solutions for inspecting elements, auditing inspection, the product information and providing a proper report for the product to the customer. All the output was later visualized in Power BI and strategy was planned by the team based on the visual output after inspection and analysis
The challenge over here was when they finalized the strategy for a particular they had to wait for all power bi sources to get refreshed and validated. This was not giving a good customer experience affected productivity.
Augmented Systems with its Hands-on expertise and experience took up this challenge to integrate all their multiple application databases to Azure Data Warehouse. Our best minds got on this project to understand the functioning of both applications in depth and integrate them for a smooth customer experience. Our expertise in Microsoft Azure, Azure Data Factory & Azure Data Warehouse helped our client the right technology that addressed their challenges and develops a solution that is robust and secure.
The integration removed any manual interventions and allowed the team to free up their time for other important and innovative tasks. The response time to their customers improved by 80% it allowed the team to directly work on visuals and provide all product strategies to the end client. The data was processed in ADF pipelines and was stored in Azure SQL Database which was further forwarded to Power BI using AAS Service which provided similar visualizations in Power BI for which client had to wait all day to load daily data.
Technology Used: Azure SQL Database, Azure Data Factory, Azure Analysis Services, Power BI