data governance framework

How to Use a Data Governance Framework to Manage Data Assets [+ 13 Best Practices]

Data governance has transformed from an optional practice to a priority affair for most businesses over the years. Companies can reap multiple benefits like detailed analysis, enhanced security levels, higher efficiency, and managed conflict resolution with a set of well-implemented data governance practices. 

A data governance team has absolute control over the data used in the system, and wrong implementations of data governance practices can have catastrophic effects on any business.

Popularly said, a business needs to figure out the what-who-where-when and why of data governance to ensure maximum yields from their data policies. Utilizing the best data governance frameworks is an effective way to maximize benefits for your business and get an edge over your immediate competitors.

What is a data governance framework?

A data governance framework is a set of rules and policies that an enterprise follows to manage its data assets. This framework serves various crucial tasks, such as assigning roles to members within a governance team, establishing key quality factors (KQIs), and forming data risk and privacy policies for an enterprise. 

The framework also defines the key performance indicators (KPIs) and data quality rules for the data stored in a company’s database.

Why a Good Data Governance Framework Is Essential

The data governance framework defines the norms for every stage in the data lifecycle and documents them in one single repository. A good data framework is the backbone of strong data governance in an organization. The team streamlines and scales the essential governance processes as the business grows over time and the data volumes shoot up.

A good framework also facilitates the following: 

  1. Execution of data governance essentials like data catalog creation, reference assimilation, and mastering data requirements
  2. Enforcing data policies for various internal teams
  3. Identifying data owners and improving data literacy within the organization

The work of a data governance team is extensively simplified, especially if a good data framework is in place. It only needs to execute the framework and monitor the results that show up. These results are further helpful in optimizing the company’s services according to its needs.

Aspects of a Data Government Framework

Here are a few aspects of a framework that make it practical for an enterprise:


A data governance team includes team leaders like the Chief Data Officer and employees like Data Stewards to ensure the system is functioning well. All these members are recruited and assigned responsibilities according to the data governance framework in effect. 

This framework also provides guidelines to assist the team and further ensure everyone works in unison and in tandem with the data assets. 

Some frameworks use automation for monitoring purposes to cater to the needs of the company. Automation makes the monitoring fool-proof and cost-effective, as there are many savings concerning recruiting data stewards.


A data framework separates the valuable data from the raw data that comes into the system every day. The framework defines the parameters that the incoming data must fulfill to get accepted by the system. This majorly improves the data quality and results in better implementation of any service that uses this data.


The data governance framework takes care of the time for all the governance policies. It defines the audit time for the data and the data access rights to constantly bring positive changes to the system.  

A good framework deploys specific repeatable processes according to the needs of the enterprise with the right balance of technology. This orchestration of data processes eventually decides the success or failure of an enterprise. 


Last but not least, a data governance framework should identify the needs of the enterprise and form policies around these needs. Asking the question “why an enterprise needs data governance” is essential for tailoring policies for any business. 

This step helps in forming realistic goals for the company and establishing better data rules for your business.

Data Governance Framework Principles

Businesses need to focus on these principles to ensure they can determine the best data frameworks for their day-to-day procedures:

Value and Outcomes

Always make sure that the data governance framework aligns with the outcomes of your firm. A professional data governance team is capable of aligning the needs and policies of any enterprise.

Accountability and Decision Rights

The governance framework should clearly define each member’s roles and the decision rights of the data governance team. 

From the CDO to a data steward, everyone in the group should know their responsibilities and powers. The delegation of duties decreases conflicts in implementing any process and optimizes operational costs.

Transparency and Ethics

A data governance framework should always keep its ethics above any personal gains for the enterprise and maintain transparency in all data handling.  

These practices instill trust in the customers and employees. These practices also help employees comply easily with the data protection laws.

Risk and Security

A data framework should analyze the risks involved in any data governance strategy and minimize the risk. The framework should also ensure the data stored in the system is well-maintained and only accessed by authorized personnel.

13 Best Practises to Ensure Better Data Governance

It is always important to follow best practices to ensure data governance is achieved without sacrificing data accessibility. 

Let’s look at some of the best data governance practices:

  1. Do not set unrealistic goals for your enterprise, especially when laying the basics of data governance. Set small goals and focus on effectively completing them; the framework can be homegrown slowly and steadily with experience. 
  2. Always set well-defined and measurable goals. Constantly monitor the process of reaching the end goal and try to improve on lessons learnt from past mistakes. Make sure to celebrate these small targets as it helps to keep the morale high for the team.
  3. Define data ownership for all the data assets in the system. This step is crucial for the proper functioning of a data framework.
  4. Clearly define the roles and responsibilities of every member within the data governance team. Also, make sure that every team member is well-versed with the data rules made by the data committee.
  5. The technology and policies are rapidly changing in the data governance industry. You should frequently educate your employees about the business terms and translate the data governance principles into meaningful content in business terms. 
  6. Align the operating model with the data framework to ensure better implementation of all the governance policies. A data governance framework should integrate the way of doing business in your enterprise.
  7. It is essential to develop standardized data definitions for every department in the enterprise. Also, make sure to categorize data elements that are too centralized or localized.
  8. Make sure to identify the data domains. Initially, work on a domain that offers the best ratio between impact and effort and then slowly adapt to the governance methods to improve the yields.
  9. It is also essential to identify the critical data elements and focus on the most critical data elements. Data-driven decisions can make or break a governance model. 
  10. Control measures are a big part of the data governance policies. Derive the best control measures and implement them in the business process and IT applications. Additionally, try to evolve these measures by reporting the errors in the control measures.
  11. Build a business case and identify the advantages of rising data governance maturity related to different aspects of business such as growth, cost efficiency, risk evaluation, and compliance.
  12. Ensure frequent communication between the data governance team and other departments in the enterprise. It is a well-known fact that better communication often leads to enhanced efficiency for the business.
  13. Most importantly, remember that data governance is a practice and not a project. This means that you should constantly strive to improve the policies and practices in the enterprise.

How Kloudio Helps Establish a Data Governance Framework

Enterprises can rely on Kloudio to create a robust data management model, coupled with the latest technology, data repositories, and data manipulation techniques. 

As technology continues to evolve, there is a lot available to business firms these days. To keep data management working like a well-oiled machine, it’s necessary for companies to follow the right data extraction, transformation and loading processes. 

Kloudio’s tools and services are geared towards helping enterprises manage their data assets with utmost ease and high-level security. Connect to a series of data repositories, and carry out the ETL process to initiate automated reporting, and scheduling on a regular basis. Create your free Kloudio account today. 

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