KImball vs inmon vs data vault modeling approaches

 

How to implement a data governance process effectively

 

How to implement a data governance process effectively in six steps

by Jon Kowieski, Senior Growth Marketing Manager at ThoughtSpot

Published Oct 17, 2022

As companies increasingly rely on data to drive their organizations and bring insights to more and more pockets of their business, it’s critical they implement a data governance process in tandem. 

Data governance when done effectively documents clearly defines the rules and regulations surrounding data access and usage. In addition, a data governance process can help to improve data quality, which in turn increases the value of data initiatives at large. Last, data governance is an essential element in adhering to privacy, compliance, and security protocols by ensuring individuals only have access to the data they should. 

Despite the vital role data governance plays in business today, many organizations still struggle with implementing a program at scale. There are several steps that you can take to implement a data governance process in your organization. In this post, we will outline the key steps involved in this process.

Step 1 : Define the goals and objectives of your data governance initiative

Before embarking on a data governance initiative, it is important to have a clear understanding of the goals and objectives you hope to achieve. Do you want to improve data quality? Increase transparency and accountability? Improve decision-making? These goals must serve as the foundation from the broader project, and provide the structure for step 2.

Step 2: Identify the stakeholders who will be involved in the initiative

Once your goals have been outlined, you need to bring in the cross functional team who will be essential to implementation. Data governance is not something that can be done in isolation – it requires buy-in and involvement from a range of stakeholders. Who needs to be involved in your initiative? For some organizations, they may be your data team. For others, they may be your IT department or individuals in your security department.

Step 3: Develop a framework for how data will be managed and governed

Once you have defined the goals and objectives of your data governance initiative, and identified the stakeholders who will be involved, you need to develop a framework for how data will be managed and governed. This should include processes and controls for things like data quality, security, access, and retention.

Step 4: Implement processes and controls to support the data governance framework

After developing a framework for how data will be governed, it is time to put it into action. This includes implementing processes and controls to enforce the framework, such as data quality assurance processes or access control measures. If you’re looking to truly capitalize on the value of your data and extend it to multiple parts of your organization, it’s important to ensure the tools in your data stack give you the ability to manage these down to the finest level, at every row of your data, for every user.