What do you do if your data governance frameworks are hindering your data architecture skills?

1 Assess Impact

When you notice that data governance frameworks are impeding your data architecture efforts, the first step is to conduct a thorough assessment of the impact. Look at specific instances where governance policies have created bottlenecks or prevented you from implementing optimal data solutions. Consider how these constraints affect the business's ability to leverage data for insights and decision-making. By identifying and documenting these pain points, you can build a strong case for revising the governance strategies that are in place.

2 Engage Stakeholders

Engagement with stakeholders is critical when addressing issues caused by restrictive data governance. You need to bring together key players, including data stewards, IT professionals, and business leaders, to discuss the challenges you're facing. This collaborative approach helps to ensure that everyone understands the importance of a flexible and enabling governance framework. It also allows you to gather diverse perspectives and insights on how to refine the existing policies to better serve the organization's data architecture needs.

3 Propose Solutions

Once you've identified the hindrances and engaged stakeholders, it's time to propose solutions. Develop a set of recommendations that balance the need for governance with the flexibility required for effective data architecture. This might include suggesting updates to policies, introducing new tools that align with governance requirements, or advocating for a more decentralized approach to data management. Your solutions should aim to enhance data accessibility and usability without compromising on compliance and security standards.

4 Pilot Changes

Before overhauling your data governance frameworks, consider piloting the proposed changes in a controlled environment. This allows you to test the impact of your solutions on data architecture practices without risking widespread disruption. A successful pilot can demonstrate the benefits of your recommendations and help gain buy-in from hesitant stakeholders. It also provides an opportunity to refine your approach based on real-world feedback and results.

5 Monitor Progress

Implementing changes to data governance frameworks requires careful monitoring to ensure they positively impact your data architecture skills. Set up metrics and KPIs (Key Performance Indicators) to track progress and identify any unforeseen consequences of the adjustments made. Monitoring these changes helps in making sure that the new governance practices are not only facilitating better data architecture but also meeting the organization's broader data goals.

6 Iterate Process

Data governance is not a set-it-and-forget-it process; it requires continuous iteration to remain relevant and effective. As you monitor the progress of the changes, be prepared to iterate on your approach based on the outcomes observed. This might involve further tweaking governance policies, adopting new technologies, or even revising organizational structures. Remember that the goal is to create a governance framework that evolves alongside your data architecture skills and the needs of your business.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?