Guide: Data Governance

The Basics of Data Governance Solutions

Data Governance has become more important than ever before in today’s rapidly changing and aggressively competitive market. The amount of data available for collection and analysis continues to expand and offers multiple options for security, information, and innovation.

Yet, entities that collect this data need to have proper organization, filtering, and security measures to safeguard it. Organizations require discipline to optimize their value, manage risks, and cut costs now that they can acquire huge amounts of diverse internal and external data.

As organizations face new data privacy regulations and rely more and more on data analytics to help optimize operations and drive business decision-making, having an enterprise data governance solution in place is critical.

In this article, you will learn the following:

This is part of our Data Governance Guide.

What is Data Governance?

The term “data governance” refers to procedures, responsibilities, policies, standards, and measurements designed to ensure that an organization’s data gets used effectively and efficiently to meet its objectives while increasing its security. These regulations are continuously updated to ensure compliance with changing regulations and security standards.


A data governance platform establishes an organization’s data quality and security policies and procedures. Thus, a data governance solution establishes a single set of clear guidelines for who has access to what data assets, when, and how. 


A data governance team is a steering committee that serves as the governing body, and a group of data stewards is often included in a well-designed data governance solution. The data governance team and data stewards collaborate to develop data governance standards, policies, and implementation and enforcement methods, which a master data management steward generally carries out.


Data governance is a requirement for digital transformation and other data-driven projects, particularly those with sensitive data, to flourish. However, many organizations lack the enterprise data governance visibility, efficiencies, and business user involvement necessary to make data governance a reality. Data governance software can give teams the tools and automation they need to make a difference.


Finally, data governance ensures that data responsibilities are clearly defined and that responsibility and accountability is established across the organization. In the end, strategic, tactical, and operational roles and duties are all covered by well-planned data governance platforms.

Types of Data Governance Solutions

There are two types of data governance solutions: standalone data governance software and integrated data governance platforms. Many data governance companies incorporate data governance into their data quality, catalog, or analytics software. Data governance applications are generally required when enterprises need to comply with laws relating to securing sensitive client, patient, or customer data.


The capacity to establish a business glossary, data lineage, and rules-based workflows are common aspects of both types of systems. Numerous data governance tools include Artificial Intelligence (AI) and Machine Learning (ML). Still, some data governance products additionally provide data discovery, master data management (MDM), data cleansing, data integration, data literacy, data security, data cataloging, data modeling, and other data capabilities.

Selecting the Best Data Governance Tools

Keep the following in mind if you are searching for the top data governance companies or the right data governance vendors:


  • Determine who your primary users are. Some cloud data governance tools are geared toward regular business users, while others are geared toward IT and data scientists as high as your Chief Data Officer (CDO). Make sure you know who in your business will be using the data access governance tools the most.
  • Make your requirements clear. While people might say they want a data governance solution, they may be searching for a data quality, MDM, or data integration solution. Make sure you know what features you require from a data governance platform, and do not be afraid to compare data governance tools to arrive at the right choice.
  • Match products to your data governance tool requirements. Only a few data governance vendors specialize in data governance software. The majority of them include other relevant capabilities. However, those capabilities differ greatly. You will have to search around to ensure you receive what you need without overpaying for features you will never use. To get the best data governance software, check if your solution connects with other leading solutions for data access management, unstructured data management, and identity governance.
  • Take it for a spin. Many vendors of data governance automation tools offer free trials. Take advantage of these free open source data governance tools deals before making a purchase.

Examples Of Data Governance Solutions

Data governance solutions follow one of two basic example models. These two examples follow either a decentralized approach or a centralized approach. Which will work best for your organization largely depends on your organizational structure and the tools you use for data governance.

Decentralized Data Governance

With decentralized data governance, individual users manage their own data. Each individual in an organization can collect, maintain, and use data following established procedures. This example of a data governance solution provides a very simple way for a business to establish basic data governance principles. However, it can just as easily result in data inconsistencies and a lack of security if left poorly monitored.


Going beyond individual users managing their own data, organizations can use decentralized data governance with each department managing their own data. This provides slightly more oversight over how data is managed as more individuals will be monitoring each set of data within a department. But, it can still result in a lack of security and inconsistencies can quickly get out of hand.


Decentralized data governance works best for small organizations where business data is seldomly used for crucial decision making.

Centralized Data Governance

Instead of allowing individuals to manage data, centralized data governance places one individual or team in charge of managing all business data. All data collected and used is managed by a centralized individual or team who can ensure data quality and compliance. Then, any individual or team that needs to use data can acquire the data they need from the centralized data governance team.


You can also combine centralized data governance and decentralized data governance by creating a centralized team that oversees a decentralized data governance system. This allows for specialization in data control and management while still promoting agility in business teams when needed.


Centralized data governance generally works best for medium and large organizations that require strict data controls to ensure compliance and data quality.

Data Governance Solutions Best Practices

Given all the necessary information, here are steps on how to take your Data Governance endeavor to its highest potential:

Begin by Using a Small Sample Size

It is preferable not to start your data governance program with a difficult or lengthy project. Instead, start with a smaller, more manageable job, such as data analysis for one team. Assess the current state of the data, including its collection, storage, and use, and then decide how much of your money will go toward the project.

Form a Team to Work on Your Data Governance Solution

You will need to create roles dedicated to your data governance program if you want it to succeed. For starters, the program’s leader should have excellent communication skills and be able to convey the program’s relevance to the rest of your organization. Each team member should have distinct tasks to ensure that each data governance endeavor works smoothly and efficiently to reduce role explosion.


Your data governance team should include individuals who understand how to manage customer data effectively.

Set Clearly Defined Data Governance Objectives

These objectives could include safeguarding top-level data, eliminating team friction, lowering data management costs, and speeding up the data entry process. Whatever your goal is, it should be measurable and have a plan for achieving it.

Establish Risk Milestones

It is essential to consider the potential dangers of creating your data governance software. The information you collect from customers is vital, but its privacy may be at risk over time if it gets distributed throughout your company.


Establishing risk milestones serve as an early warning system of potential dangers that may arise whenever data is transferred or shared within an organization. Thanks to these milestones, your team can prevent costly setbacks that can adversely impact their relationships with their customers.

Evaluate Projects After they are Done

If the project does not help you achieve your objectives, you will need to modify it before moving on to the next endeavor. Carry out some tests on your data to keep track of any changes, and then have a conversation with your team about which procedures should get streamlined and which ones should get readjusted.

Refine Your Data Governance Framework Regularly

Your framework for a data governance solution consists of a standardized procedure for collecting and disseminating data. However, as your company expands and evolves, it is essential to modify your plan to account for the various organizational changes. If you do not keep it up to date, you risk losing customer data or inadvertently disclosing critical information.


The amount of data available to businesses nowadays is staggering. An organization will be more successful if it uses this knowledge to understand the market and its target audience better. The best data governance tools will ensure this data is trusted, well-documented, easily accessible, secure, compliant, and private.



Satori helps you with DataSecOps for your modern data stack. This includes continuous sensitive data discovery, integration with existing data governance tools to make data governance more efficient and immediate, and means to streamline access to sensitive data and create security policies that are independent of the specific data infrastructure you’re using.

Last updated on

August 1, 2022

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