How do you train and raise awareness for data governance roles?

The Data Capability Assessment Model (DCAM) is an industry-standard framework designed to evaluate an organization's data management and governance capabilities. It covers a range of factors such as data quality, data governance, data architecture, and data operations. By using DCAM, organizations can gain a comprehensive understanding of their current data governance maturity level, which in turn helps in identifying gaps and opportunities for improvement. The model also aids in assessing the skills and roles within the data governance team, thereby offering a roadmap for training and skill development. Overall, DCAM serves as a valuable tool for organizations looking to optimize their data governance initiatives.

The data governance assessment should include dimensions on people and awareness. Here is a checklist for a first level assessment : 1️⃣ Value Are people in the organization consuming / producing data? For which business objectives? Are they trained to use them? 2️⃣ Organization Is there existing roles or instances related to data governance? What's the operating model? 3️⃣ Processes Is there policies, processes, standards regarding data - could be data quality, data accessibility, compliance, data security, etc? 4️⃣ Mapping How is the data structured and mapped? How can people find data? 5️⃣ Tools Is there data governance tools in place - could be data quality management, master data management, metadata management?

Data governance maturity refers to an organization's stage in implementing and adopting data governance initiatives. An immature organization will have a great deal of unorganized data and won't be using this data to drive growth. Alternatively, a mature organization will be well aware of the importance of data as a key business asset and govern and manage it accordingly. There are a handful of well-known data governance maturity models, including examples from IBM, Stanford, Gartner, and Oracle. These models provide a method by which a business can learn how to manage data effectively, provide user access, ensure that data is of high quality, and make it possible for everyone in an organization to benefit from these advances.

To ensure that your roles are not considered an academic exercise, capture existing and needed positions in your organisation, that are (execution) responsible, accountable, consulted, or informer w.r.t. any of these roles, and make explicit the tasks involved in fulfilling such a role, and the skills needed/expected. When binding this to concrete data topics, via glossary terms, or sources, via systems and meta-data, you can discuss the view on this from different stakeholders, and raise concern for areas where responsibility is unclear.

Any training in data governance should be balancing the WHY and the HOW - purpose and methods. While in theory data governance should be having rules and processes that everybody complied with, in reality it’s a much more fluid and adaptive process. Training data governance staff to have structure in their mindset while keeping a flexibility in their actions how to get to the needed outcome is key.

A different approach that can be used to put Data Governance at the center of the table is to perform a data risk assessment by linking data importance scores to the organization's operational risk matrix.

Data culture as a key pillar of data governance: Creating an internal data culture is not only a part of data governance, but a central pillar. This is often an overlooked aspect of data governance as the focus is often on the "technical" aspects of data governance. Effective data governance is built on the back of good data culture - one feeding into the other. When everyone understands the value of data and are committed to its quality and security, the organisation can harness the full potential of its data assets. As data governance leaders, our responsibility is to champion this culture, provide the necessary tools and guidance, and continually reinforce the importance of it in achieving organisational goals.