CASE STUDY
KEY OUTCOME
A retail supply chain overcame fragmented data challenges by centralizing its data systems, enhancing data performance, and achieving a unified, reliable data source, significantly improving both internal and customer experiences.
CHALLENGE SUMMARY
A growing eCommerce retailer was stuck with legacy systems, manual processes, and no real data management resources which made it almost impossible for the organization to have 360-degree view of their customers.
SOLUTION SUMMARY
The solution involved creating a centralized data model using modern data warehousing best practices, enabling Microsoft Power BI analytics. This approach streamlined the reporting process and provided timely, accurate program insights.
GOING DEEPER ON THEIR CHALLENGE
A retail supply chain organization was plagued by a fractured data ecosystem due to disparate enterprise resource planning (ERP) systems, disconnected processes, siloed business units, and a lack of data governance. In the current state, a customer’s information or pieces of a customer’s information could exist on one or several ERP systems.
To further exacerbate the issue there were no standardization guidelines in place resulting in the inputted data lacking uniformity. In combination, these issues caused end users to question data quality and integrity. Furthermore, the organization was dealing with a legacy reporting system with limited data loads. This data constraint led to delays in report delivery that resulted in partial, stale enterprise reporting.
UNDERSTANDING DATA IDEOLOGY’S SOLUTION
After a brief assessment, it was clear to our team of experts that the best way to cleanse the organization’s data to optimize reporting and analysis capabilities was to unify all data systems into a central repository. This meant:
THE RESULT
Now equipped with a combination of a proven methodology and modern data tools, the organization was able to break down their data silos and help improve data performance through a data centralization initiative. In tandem with the business’s key stakeholders, our architects were able to design a sophisticated data model and build an enterprise data warehouse that could integrate multiple data sources into a single repository.
Additionally, our business analyst was able to help create updated policies & procedures that defined data ownership and access. Bridging the gap between people and technology allowed for the organization to upgrade their data ecosystem to not only achieve a single source of truth but to improve the overall experience for both the data consumers and their customers.
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