Data governance: what is it and how do I approach it?

Discover, influence, and optimize the value of your business data

Data governance emerged in response to the growing amount of data that organizations collect and record, and the increasing need to manage and utilize this information effectively. In the past, this was often done on an ad-hoc basis, resulting in inconsistencies, duplication of effort, poor data quality, and security risks.

Practical examples always provide the best insight into what to do, but also what to avoid. Below, we list a few examples for you.

The 5 Ingredients of a well-thought-out data governance plan

1. Vision and strategy: What are you going to do?
   A clear vision and strategy are the foundation of every good plan. Data governance is no different. Determine in advance what you want to achieve and how data governance contributes to the objectives and ultimately the success of your organization.
2. Policies and procedures: How are you going to do it?
   Establish policies and procedures for the management, access, use, and security of data within your organization. This must align with your organization's objectives and comply with relevant laws and regulations.
3. Assigning responsibilities: Who is going to do it?
   Make individuals responsible for different parts of the management and execution of the program. Clearly describe what you expect from each stakeholder at any given time.
4. Identifying data assets
   If you want to manage something, you need to know exactly what it entails. Therefore, map out all data assets within your organization, including their sources, properties, availability, where they are stored, who has access, and what they are used for.
5. Good technology
   Use modern technology to support and automate data governance. Consider collecting, indexing, and organizing metadata, or tools that help improve data quality.
   
   

4 Pitfalls of data governance you want to avoid

1. Trying to manage too much data – Don't try to tackle everything at once, but focus on the data that has the most impact on your business objectives.
2. Rigid rules and procedures – Everything and everyone is subject to change, so avoid rigid data governance policies and processes.
3. Lack of measurements and monitoring – Without measuring and evaluating the effectiveness of your data governance program, you have no idea if it's doing what it's supposed to do.
4. One-sided focus – Technology, people, process: they are all equally important for successful data governance. Therefore, give them the attention they deserve.

EIM System as a Catalyst for Data Governance

Flexibility is not only important for rules and procedures. It is also a prerequisite for the Enterprise Information Management systeem that supports you in managing data and the activities involved. In addition to flexibility, scalability (growing in terms of the number of users and data), integration options (links with other applications from the information ecosystem), data quality (control, analysis, correction, and enrichment of data), and security (access control, data encryption, audit trails) determine the utility and contribution of technology to the management and use of data within your organization.

Interesting?
Want to learn more about data governance? Or are you curious about how an EIM system functions as a catalyst and accelerator for data governance? Then contact one of our WoodWing Xtendis experts.