Enhancing Retail Performance with Semantic Layer As an Enabler for Data and Analytics Teams

The Challenge In the fast-paced retail sector, organizations need to be able to quickly view store performance analytics in order to make crucial decisions. A leading global retail chain faced significant delays of up to 5-6 weeks when attempting to retrieve essential store performance metrics and create reports for executive leadership. This bottleneck was largely due to a data landscape where the organization had no central repository to store analytics and reporting information, aided further by a lack of standardized metadata or a coherent taxonomy system. As such, employees could not locate crucial data metrics, find information to aid their understanding of existing metrics from previous data projects, or locate the creators/curators of said metrics or analytics. Consequently, the chain decided to make significant investments into a migration of their content and data into a data lake and data warehouses as part of a data analytics transformation and modernization effort.