What is a Data Governance Framework?

Data is arguably an organization’s most valuable asset. A data governance framework, at its core, leads to improved data quality, lower data management costs, and increased data access for all stakeholders. As a result, better decisions are made, and business outcomes are achieved.

Cloud governance is critical for regulatory compliance. Compliance ensures that organizations consistently meet all levels of privacy requirements. This is critical for reducing risks and operational costs. 

Why Does Data Governance Matter?

Without good data governance, problems with data across different systems in a company may go unnoticed. For instance, customer names may be listed differently in sales, logistics, and customer service systems. This could make it more challenging to integrate data and cause problems with data integrity.

It also affects the accuracy of:

• Business intelligence (BI)
• Corporate reporting
• Analytics systems

Data inaccuracies may go undetected and uncorrected, impairing the accuracy of business intelligence and analytics.

Poor data governance can also stymie regulatory compliance efforts. This could pose a difficulty for businesses that must comply with specific regulations. These regulations are new data privacy and protection regulations, such as:

• The GDPR (General Data Protection Regulation) in the European Union
• The California Consumer Privacy Act in California (CCPA)

A corporate data governance effort usually results in uniform data definitions and formats. These assure business and compliance data consistency across all corporate systems.

What Is a Data Governance Framework?

The data governance framework is a set of standards that describe how businesses set up and enforce data governance.

A well-designed data governance program includes:

• A Governance Team
• A Steering Committee
• Data stewards

These groups collaborate to develop:

• Data governance standards
• Rules, regulations, and processes

These are then implemented and enforced by data stewards. Along with IT and data management teams, business executives and other stakeholders also play a part.

Let’s discuss how to go about implementing a data governance framework.

Where to Start?

Although there are a variety of data governance frameworks available, they all follow the same core principles.

Each framework specifies the rules that businesses should adopt. It also defines the roles people must play for data governance to proceed effectively.

Most importantly, implementing a data governance framework requires support from the top. Therefore, this initiative is a board-level piece of work. Additionally, it is not a once-off. The implemented framework will require frequent review and change.

Roles in the Data Governance Framework

There are many roles within the data governance framework. Let’s look at them:

Chief Data Officer

Chief Data Officers (CDOs) have been increasingly popular in recent years. Companies are beginning to see the value of data management and creating a data governance framework. However, this necessitates the hiring of a CDO.

Appointing a CDO displays a company’s commitment to data and top-level buy-in to take data governance seriously.

Data Owners

The persons who have direct responsibility for data are known as data owners. They are tasked with ensuring the security and quality of data as a company asset. There will be a data owner on the team that uses the data. A Data Owner for the Finance team’s data, for example, should be a member of the Finance team.

When it comes to their own business, data owners know who should access their data. Giving data owners the tools to monitor and audit data access is an effective data governance practice.

Data Stewards

Data stewards also play an important role. They help Data Owners to execute data governance policies and teach new Data Owners and Workers.

Data Governance Committee

The Data Governance Committee establishes data governance policies and processes. In addition, this committee collaborates with the CDO to determine who, what, when, where, and why data governance is essential.

Set Some Goals for the Framework

Now that we know what a data governance framework is and, who it involves, it is time to set some visible, achievable and, measurable goals.

Here is a list of some examples:

• Document data asset lineage and access limits to avoid regulatory fines
• Make informed business decisions with data that meets the enterprise’s data needs
• Improve data security by defining data ownership and the obligations that go along with it
• Having data assets that are trustworthy, standardized, and multi-purpose reduces rework
• Profits can be increased by using data (everybody likes this one).
• Profits can be increased by using data (everybody likes this one). Validated data is correctly saved, classified, and made available for monetization

The preceding are just a few things you can achieve if you have good data governance capabilities.

There are two reasons to implement data governance. Either we want to grow the business or to meet regulatory compliance. Or both, either way, implementing a framework will undoubtedly add value.

The Benefits of Data Governance

Throughout this article, we’ve discussed the advantages of better decision-making and regulatory compliance. But, there are some other benefits worth mentioning.

Improve Digital Transformation

Only by governing the company’s data assets is a complete digital transformation possible. This necessitates the implementation of a data governance framework tailored to the organization’s future business objectives and business models.

Areas in the business that will benefit include:

• Top-level management – To track data assets and their value to the business as well as market possibilities
• Legal – This will be the only option to meet increasing regulatory obligations in terms of legal and compliance
• Sales – This will help sales and marketing understand client preferences and behavior
• Finance – This will ensure consistent and accurate reporting for finance
• Workforce – This will lessen staff annoyance when compelled to use dirty data every time a decision is needed
• Procurement – improves data-driven cost reduction and efficiency measures in supply chain management

A rapid, complete view of all your data flows, sources, transformations, and interactions are required to gain data control.

Put a stop to time-consuming, manual lineage collection and update methods. Automated lineage can save you on costs during the discovery phase.

Get that Competetive Advantage

Finally, data governance assists management in making better business decisions. It does this by providing better and higher quality data, resulting in competitive advantages and improved revenues.

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