The editors at Solutions Review compiled this list of data governance principles to live by for the success of your metadata initiatives.
Not only is data governance one of the most common data management use cases, but it’s also the most difficult to solve for. Data governance is perhaps the most important factor in modern data management and bridges the gap between data quality and democratization. In order for organizations to enable cross-enterprise data access (which is a major pain point in and of itself), data needs to be overseen in the correct fashion using industry-standard best practices.
Metadata simply summarizes data, which has the ability to make finding and working with relevant data easier. Metadata commonly describes how and when and by whom a particular data set was created and what native format it resides. Some people are looking to grow their use of metadata beyond an IT productivity project into something larger such as a data stewardship or data governance initiative. Some are just getting started. As a result, our editors assembled this short list of key data governance principles to consider as you build your thinking.
1. Start small, but Show Up and Execute:
Showing up is half the battle, ever hear of the 80/20 rule? Pick a small project that you can be successful at and show some tangible results quickly. Then, grow from there.
2. Quantify Everything
Be ready 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 because of bad data in a data warehouse?
3. Obtain Stakeholder Buy-In
Your project won’t succeed without the right executive sponsorship. Don’t shortchange the importance of getting the right sponsorship from both the business and IT sides of the house. This is also critical for getting other groups to contribute to the overall cause now and in the future.
4. Create a Data Governance Council
With a data governance initiative, a company moves beyond metadata as an IT productivity tool and into use cases that have much broader business benefits across the organization. The most important thing is that you have a data governance council to set the 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
Pick a specific problem and solve it before expanding into other new areas. The important thing is to pick a project that has high value and high strategic importance to the overall business. The first win using new data governance principles is a critical step, see tip #2.
6. Roadmap Your Plans
Organizations usually fail to establish data governance principles because they try to do everything at once. This does nothing but ensures projects get bogged down and then canceled when they failed to produce any meaningful results. Nobody has time or budget for endless meetings that produce no tangible results for the business. Often the failure comes from trying to resolve 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 Line-of-Business Users
In order to establish a successful data governance framework, data needs to be attached to business terms, definitions, term owners, reference data, and other documents and contracts. Once you have this business context, you can link the business terms and definitions to the underlying technical metadata, creating a common language between business and IT that will improve communication and collaboration.