Designing Data Governance Framework Using Best Practices that Deliver Value

Data Modernization & Analytics
Cloud Technology

Data governance acts ensure your company’s data is usable, accessible, and protected from all threats. Act upon these best practices to design a data governance framework.

Recent research from Mordor Intelligence projects that the data governance market will be worth 5.28 billion USD by the year 2026. Data governance is essential for enterprises that want to secure trust and stay accountable for all their information-driving assets. Enterprises that securely collect and standardize their data to derive valuable insights needed for the growth of an organization follow best practice data governance to support a secure process. Implementing a robust data governance framework will play an integral role in your company’s data availability, usability, security, and integrity. 

Enterprises need to design a practical data governance framework that works in their favor for implementing efficient policies, processes, and standards to regulate the availability and usage of data across the organization. This article will discuss the core components of effective data governance and how to design a robust data governance framework using the best practices.

What Is Data Governance?

Data governance is a way to organize and structure data within a company; the practice of defining the ownership of data and the policies around data security and retention. Governance also covers methods for implementing these policies effectively. Data governance is the umbrella under which all the data management policies and procedures fall; the term refers to the rules, laws, and other formalized methods put in place by an organization, government, or other groups to ensure efficient organization of their data. 

Data governance typically includes deciding on the type of data to collect, its usage, who can access it, and under which circumstances. The key differentiating factor of a best practice-led data governance framework is setting clear objectives communicated to everyone involved in the data process behind its implementation. A successful data governance framework will provide value to the business and make it more efficient, but only if everyone in the company buys into its implementation and continued maintenance.

Why Data Governance Matters

Data is an essential asset for any company. Data governance acts to make this asset usable, accessible and ensure protection from any malicious threats. In addition, analyzing data helps you to measure success by highlighting areas of improvement, identifying the root causes of failures/discrepancies, and offering insights on process enhancement.

Furthermore, data governance is a critical component in compliance management. An effective data governance framework provides a scalable and repeatable method of governing data to meet necessary compliance regulations according to the vertical your company may operate in.

A strong data governance framework is also crucial because it helps you assign ownership and accountability for data. Any new initiatives or projects involving data must start with a needs analysis to identify requirements and priorities. This approach will also ensure that your business has an accurate understanding of the current state of its IT landscape, which can help detect any gaps in your overall IT strategy.

How to Audit Data Governance

Take the first necessary step to audit your data governance framework once interactions are complete. Next, you need to make sure that your framework is effective in providing values for your business by taking the following steps:

Step 1: Plan an Audit 

Understand the necessary audit processes before you start an audit and prepare a plan, which will include reviews for data management processes within the company. This way, you can iterate on and repeat the program in future audits as well.

Step 2: Review Policies

Review policies on storage and retention to ensure that they are effective in providing value to the business. Policies should also be reviewed even before a framework implementation.

Step 3: Review Implementations 

Review implementations to check if they are appropriate in meeting the company’s objectives.

Before you start your first data governance framework audit, you must understand the necessary processes. You can do this by meeting with all key stakeholders to discuss their expectations before starting the review. Then, as the review progresses, put a plan in place to address issues as quickly as possible when they are identified. 

Lastly, when you have finished your audits and have implemented policies on storage and retention, it becomes necessary to review implementations in order to check if they are appropriate in meeting the company’s objectives. Of course, all processes and procedures need to be reviewed carefully to accomplish this too. While the auditing steps may sound like a repetitive process, this is an effective approach to identify issues and places to improve the audit and the framework itself.

Data Governance Best Practices

If your enterprise wants to get the most out of the data governance framework, then follow the identified best practices below to make data governance more valuable for your business:

Expand Gradually

Every data governance framework has three counterparts; people, processes, and technology. A robust governance framework requires input from people to align data management processes correctly.

If people cannot align the processes, then technology alone cannot make a data governance framework successful. Therefore, an equal contribution from all three components is necessary.

Define Data Governance Team Roles

A successful data governance framework requires your department to address roles and responsibilities and the ownership structure properly. In addition, every data governance framework requires input from owners and other stakeholder entities inside an organization. 

Each organization has a different structure, but many more or less have the same defined key roles such as data governance council or board, team members, owners, and data users. 

Measure Progress

As you move forward with your data governance framework, it is vital to measure your progress by using original metrics. Audits can also be helpful while measuring your current progress in your current governance framework. It allows you to see your current standpoint and fix any arising issues.

Make Data Governance a Long-Term “Practice”—Not a Short-Term Project

Many companies tend to implement data governance as a project, creating dedicated teams for data management, but such an approach often hinders the data governance process. However, if companies start treating data governance as an ongoing long-term best practice, this can help develop a sustainable data governance framework. In an organization, defined team roles can effectively operate and manage this framework. 

Summary

Data Governance is a complex process that requires both the understanding of your business and IT department. The steps outlined in this article are best practices for implementing an effective data governance framework, but there are many nuanced considerations to be made when designing one. 

Define who will be responsible for governing data across your organization, establish policies around data retention and storage, and put in place security measures to protect against unauthorized access or accidental deletions. Data governance best practices can help get you started on creating a strategy that works with your company’s needs!

Caylent provides a critical DevOps-as-a-Service function to high growth companies looking for expert support with microservices, containers, cloud infrastructure, and CI/CD deployments. Our managed and consulting services are a more cost-effective option than hiring in-house, and we scale as your team and company grow.

Data Modernization & Analytics
Cloud Technology

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