The editors of Solutions Review have compiled this list of data governance principles to follow for the success of your metadata initiatives.
Not only is data governance one of the most common data management use cases, but it is also the most difficult to solve. Data governance is perhaps the most important factor in modern data management and bridges the gap between data quality and democratization. For organizations to enable cross-enterprise data access (which is a major issue in itself), the data must be appropriately overseen using industry standard best practices.
Metadata simply summarizes the data, which has the ability to facilitate the search and use of relevant data. Metadata generally describes how, when, and by whom a particular dataset was created and in what native format it resides. Some people are looking to expand their use of metadata beyond an IT productivity project into something larger, like a data management or data governance initiative. Some are just getting started. Accordingly, our editors have put together this short list of key data governance principles to consider when building your thinking.
1. Start small, but show up and perform:
Showing up is half the battle, have you ever heard of the 80/20 rule? Choose a small project in which you can succeed and quickly show tangible results. Then grow from there.
2. Quantify everything
Be prepared to quantify your results continuously. Quantify what you can and keep looking to quantify other benefits. Example: What would be the cost of a bad investment decision due to bad data in a data warehouse?
3. Obtain stakeholder buy-in
Your project will not succeed without the right executive sponsorship. Don’t underestimate the importance of getting the right sponsorship on both the business side and the IT side of the house. It is also essential to get other groups to contribute to the global cause now and in the future.
4. Create a Data Governance Council
With a data governance initiative, a business moves beyond metadata as an IT productivity tool and into use cases that have much broader business benefits across the organization. Most importantly, you have a data governance board to set overall direction and priorities for data-driven projects. They also need to design an overall framework for business users to collaborate with IT on these projects.
5. Choose a high value target
Choose a specific problem and solve it before expanding into other new areas. The important thing is to choose a project that has great value and strategic importance for the whole company. The first win using new data governance principles is a critical step, see tip #2.
6. Roadmap of your plans
Organizations typically fail to establish data governance principles because they try to do everything at once. This only ensures that projects get bogged down and then canceled when they produce no meaningful results. No one has the time or the budget for endless meetings that produce no tangible business results. Often the failure comes from trying to resolve a common business vocabulary across divergent business units.
Our recommendation: start with a single project in a single business unit if possible and grow from there.
7. Enable business users
In order to establish an effective data governance framework, data must be associated with business terms, definitions, term owners, reference data, and other documents and contracts. Once you have this business context, you can link business terms and definitions to underlying technical metadata, creating a common language between business and IT that will improve communication and collaboration.