Improving Data Quality with Master Data Management (MDM)

GOING DEEPER ON THEIR CHALLENGE

A leading eCommerce retail supplier needed help centralizing their enterprise data. Multiple disparate ERP systems were being used, duplicating the amount of work needed to input customer information fivefold. Additionally, Data Ideology’s data experts discovered severe data quality issues resulting from a lack of business processes and workflows around data management. By migrating the client to a modern data platform solution like the Snowflake Cloud Data Platform, Data Ideology’s experts were able to connect and pull the information from each ERP system into a centralized data warehouse. In addition, the duplication and fragmentation of data caused by the lack of data management and governance oversight was addressed at the source. This enabled key stakeholders to utilize one system for all data analyses, creating a single source of truth for the enterprise that was built on a foundation of trusted data. By removing inefficiencies and adding a layer of data governance, we were able to transform this client into a data-driven organization.

UNDERSTANDING DATA IDEOLOGY’S SOLUTION

Following the discovery of the data quality issue, we decided to incorporate a layer of data governance via a Master Data Management (MDM) program. The implementation of an MDM program in combination with the migration to the Snowflake Cloud Data Platform allows for a modern data warehousing solution that consists of a single source of truth with trusted, properly managed data. To gain executive buy-in, our team presented a Proof of Concept (POC) evidencing how MDM best practices would cleanse and steward data by aligning people, process, data & technology. Additionally, this then allows for business intelligence tools to be optimized so the client can start gaining valuable insights about their customers and supply chain.

THE RESULT

As a result of our MDM efforts, we were able to assist the client in multiple areas:

• Organizational Alignment: Only when we introduced the importance of discovery exercises did collaborations between the IT and business group commence. This is the point when the client began seeing the breakdown of its siloed data.
• Data Governance: By creating formal processes and documentation, like source to target mapping, user access management and business glossaries, we were able to implement data cleansing’s best practices for the purpose of improving data quality.
• Data Unification: Housing data in a singular, modern data warehouse allowed for the centralization, validation and standardization of data assets which provided the client with a single source of truth.
• Data Visualization: With much improved data quality, we were able to position the client to use its analytics tools to its fullest potential, allowing the organization to transform its critical data into rich visuals.

The benefits of a Master Data Management program in conjunction with a modern data warehouse platform allowed for the client to realize great improvement in multiple areas. Their Chief Information Officer described MDM best by saying it was a “game changer” for their organization.