At the time of this project, our client’s business intelligence team worked with data from an on-premises data warehouse. While the data warehouse was set up correctly, it simply didn’t have the capacity to handle the client’s data volumes. As a result, the data warehouse was not providing the data needed for business intelligence in a timely manner.
First of all, this delay in BI data affected the company’s own financial reporting capability. The company’s management did not have access to the up-to-date financial insights they needed to steer the business effectively.
Secondly, the poor data warehouse performance also affected a BI service that the company provided for its customers. This meant that the BI platform, which customers used to track their subscription sales, was not meeting customers’ expectations. And this resulted in customers calling our client’s BI team for IT support, which added to the team’s workload.
Finally, the company had plans to onboard new customers — but expanding the data warehouse was prohibitively expensive. It was clear that a high-performing and scalable alternative was required.
Overall, the drawbacks of this poorly performing BI data warehouse were:
- decreased ability to produce timely financial reports
- reduced customer satisfaction from BI services
- increased time spent on customer service calls
- lack of scalability needed to take on new customers