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Data governance framework: How to Set up and Best Practices

Data governance framework: How to Set up and Best Practices

Are you still wondering about the best approach for building a solid data governance framework? This blog lists ten steps to building a data governance framework that improves business processes and enhances data quality, security, and data management without breaking the bank.

Around the world, across all industries, organizations have to deal with an explosion in data: there are more data sources than ever before. From complex and unstructured data to system-generated cache files, organizations are struggling to develop in line with the speed at which data is being created. In many industries, the current data management needs to evolve and adapt to this changing business landscape.  

However, you may still wonder about the best way to take care of all this data. Well, this is where a data governance framework steps in. 

If you are asking, "why now? My data management operations are working fine. Can't we still live with the current one?" 

Well, firstly, data management is not data governance. It is not often that one creates the need for a framework out of the blue. Like so many other things, the notion of building a data governance framework is an evolution—an evolution of groups that have already been in high-assurance situations. Building a data governance framework can affect your organization like a smallpox vaccine in the discovery of America. It may not result in as much visibility as the discovery of America, but establishing a data governance program is key to building a robust data management infrastructure that never fails. And is future proof. 

Here are two stages to getting your data governance plan off the ground. 

Setting up a Data Governance Framework happens in 2 Stages and 10 Steps. 

Data Governance Framework Strategy

If data is the most valuable asset of every business, it only makes sense to govern it accordingly. However, for many companies and organizations, setting up a data governance framework can be a difficult task. To make things easier, we've gathered together some of the best practices in this area and summarized them in the top 10 steps in 2 stages to build a data governance program. 

Watch this video from our Senior Business Analyst, Bhavana Maddineni, to learn how to set up a data governance framework. Listen to the video and let us know your views or questions in the comments section.

Data governance framework stage #1: Asking key questions to build a data governance framework. 

Before setting up a data governance framework, the following questions need to be answered to build a robust and accurate framework. 

Step #1: Why do we need a data governance framework as an organization? 

Before starting, you need to ask: Why does my organization need a data governance framework? What's motivating you and your organization to have one? Is it because it's the shiny new tool someone heard about and now wants? Or are you responding to an adverse event that happened with your data, and you want to ensure it doesn't happen again? Regardless, first, articulate precisely why you need a framework around data governance. 

  

Step #2: What does my current data governance look like? 

You need to understand what your organization's current data governance framework looks like. Do you even have one? And if you do, what sort of controls and policies are in place? You need to understand if your current data governance is up-to-date and reflects current best practices or if it was written several years ago and hasn't been updated. 

  

Step #3: What are we trying to achieve with a data governance framework? 

This goes beyond the general question of whether or not you need a data governance framework; what do you specifically hope to realize by having one? In short, what is the end goal of having a data governance framework? What KPIs can I attach to its implementation? It's a fundamental question that will help determine what sort, if any, of data governance framework will best help you reach sound business objectives. 

  

Step #4: What does the future state of my data look like? 

Once you've identified what you're trying to achieve with data governance software, you next have to identify how your data might look in the future – and how that differs from today. What has your information technology group planned for data management for the next three or five years?  

What kind of customer/consumer data will you even have on hand regarding expanding regulations like the GDPR and CCPA? These are the sort of questions that will help you accurately frame the future state of your data. 

  

Step #5: Build a cross-disciplinary data governance team 

The data governance team should be cross-disciplinary. The team should be a mix of subject matter experts, data security experts, IT personnel, project managers, data governance visionaries with business line professionals who can offer frontline and cross-functional experience to the team. 

What is MLOps

Data governance framework stage #2: Logical progression of creating an organizations data governance framework  

The second stage of setting up data governance is Logical progression. The Logical progression happens in 5 steps.  

Step #1: Determine your data governance strategy 

To get started on your data governance framework, you need to first determine your strategy for data governance. This can be a tricky step, especially if you're looking to get buy-in from multiple departments across the organization. Think about who needs to be involved. 

The goal of this step is to outline your overall approach to data governance within your organization. It will cover things like how data will be managed and how decisions will be made on how that data is used. It should also outline where you're planning to go with your data governance framework in the future. 

Pro Tip: It is best advised to create a data strategy by bringing together existing processes, people, and workflows. 

  

Step #2: Start small 

For a new initiative, you don't want to take on too much at one time. The goal here is to build momentum and prove that data governance is worth the effort. 

Data governance success depends on establishing and maintaining strong relationships across departments and business units. Although it's tempting to start by addressing the most inter-departmental or urgent issues, this approach may be too ambitious for an initiative that is new to an organization. 

Start with an area of information with a single owner and where there are few key stakeholder groups involved in the decisions about how it is defined and managed.  

Remember: The objective is not only to build momentum but also to show that data governance is worth the effort. Start with just one business area or data issue and expand from there.  

Pro Tip: It's good to start with one where significant problems or imminent risks make it a good testing ground for data governance. 

 

Step #3: Pick the right framework 

Once you've outlined your data strategy and governance program requirements, it's time to start evaluating potential frameworks. There is no shortage of options out there, so this step can be overwhelming. However, if you have a clear understanding of your requirements, you will be able to narrow the list and find the right fit. 

 At the very least, all frameworks should provide a comprehensive overview of the organization's data landscape. Data governance frameworks should also clearly define business and technical roles and responsibilities and outline the processes that must be followed when working with data. 

The best frameworks set measurable goals for the organization and outline how progress will be tracked moving forward. This allows a company to continually refine its approach and improve its overall data quality over time. 

 

Step #4: Communicate 

The next stage in creating an organization's data governance framework is to establish a communications strategy to inform people about data governance. 

This communication strategy forms an integral part of your organization's awareness and training program. It will also be a critical factor in determining the success of your data governance initiative. 

 

Step #5: Keep it updated 

A data governance framework needs to be refined and reviewed regularly to be fully successful. The business is constantly changing and so too are the organization's needs. Don't let your data governance framework become obsolete. Refine it as needed and make sure it remains relevant to your organization's needs. 

Data governance best practices 

1. Data governance is not data management

Data management is the administration of data as a valuable resource, which includes securing, quality-assuring, integrating, and processing data. Data governance is the organizational structure and tools used to define policies for managing data as an enterprise asset. 

Data governance practices are often confused with best practices for data management. However, it's essential to understand that data governance best practices focus on effectively governing data as a critical business asset. 

Data management is the actions taken to facilitate the data governance software framework. Data governance is the decision-making function over data management decisions. 

 

2. Collaboratively made frameworks are the most effective

Making a framework is a process that requires the collective input of experts to ensure its effectiveness. The best example is the Data Governance Institute's data management body of knowledge. It lists five categories and their characteristics: 

  • Principles: General statements that guide data governance. 
  • Strategy: The organization's goals, objectives, and functions for data governance. 
  • Organization: Structures and roles required to manage data governance. 
  • Processes, rules, and standards: Guidelines for how data governance functions are accomplished. 
  • Assets, resources, and technology: Elements necessary to support data governance. 

Employees within the organization who know how to manage the data best should play a critical role in the framework design as this will ensure optimal optimization of the process. 

 

3. Data governance needs to be integrated organization-wide

Data governance is not just about IT but needs to be integrated organization-wide. Data stewardship should be clearly defined and understood by all parties involved. The information governance process must be described at an enterprise level with a clear understanding of the organization's goals for data governance. 

Once the framework is functional, ensuring it is implemented across the organization will ensure consistency in data collection to help every team achieve their goals. 

 

4. Risk milestones

Data is valuable, and the risk increases when shared within the organization. Establishing risk milestones will put the spotlight on potential threats to help avoid costly breaches. 

 

5. Continuously refine

As your organization grows, keep revisiting the data governance strategy to ensure it is still meeting the needs of your customers and your organization. 

Final Thoughts 

Data is growing exponentially. The number of sources, volume of data, and changes are increasing each year. Consequently, businesses find it increasingly difficult to cope with this vast amount of data. 

This list will help you ensure that data governance is a seamless part of your business process, not an uphill battle. It may seem like a lot to handle, but it doesn't have to be overwhelming if you break it down into manageable pieces. Start with step one and take it one step at a time, and before you know it, you'll have a fully-functioning data governance framework. 

 

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Janaha

Janaha Vivek

I write about fintech, data, and everything around it | Senior Marketing Specialist @ Zuci Systems.