Case Study: Establishing an Enterprise Data Governance Program for a Non-Profit Educational Organization

Challenges

The client, a leading influencer within the education sector, proactively communicates with hundreds of individuals daily in order to pursue recruiting, fundraising, lobbying, and relationship building efforts.

It is essential that data for individuals (e.g. title, address) and organizations (e.g. school districts) are reliable in order to reduce time, cost, and effort while working to secure financial and human capital to ensure their dramatic growth plan is realized. There were no overarching data management principles or business data owners existing within the enterprise.

Approach

Knowledgent facilitated discussions with business executives to identify data stewards. Each business team provided at least one information steward, serving as a key representative of their business team, and an operational steward, appointed to directly manage data quality, particularly through CRUD functionalities and manual record matching. A data governor was appointed to head the council at the VP level. Knowledgent also established the council purpose and policies and procedures, procured through interviews with the client and our proprietary expertise. Expectations and data jurisdiction were established for each role. Stewards were educated about stewardship models and best practices, and were trained through a situational task practice.

Results

A data governance council was established to oversee the development and sustain the quality of data management as the result of a new enterprise data architecture initiative. A concise data governance and stewardship handbook was created in order to support the data stewards, both current and future, post-engagement. Auto and manual match rules were defined in conjunction with stewards, increasing data integrity and decreasing the amount of time spent on data consolidation. Security and editor roles were distinguished and applied to ensure confidentiality and quality of the data. One of two models of data stewardship, federated and centralized, were employed for each data entity based upon business needs and expertise suggestions. Policies and procedures for each entity were documented to ensure proper management and protection of data.

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