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title: 'Data Governance: Why It Matters and How to Get It Right'

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Data Governance: Why It Matters and How to Get It Right
=======================================================

![](https://lh6.googleusercontent.com/o7EDcwpE2XQ2M117gUWdULVY9jCVMOYKa2lmVxrNztw_SjINSb4cTlZXWx06R-15nrC8qGesuH1zVR5mJuyC2HKyuifNhz4i_PwMyDgxvaPKvsb2Wd0yDFuAkcH5iZ3qT2JjCeRaXL7g4tkAVyDix29oFaFvMDLzupqTPfwLlkI4_5RNAK-nxqw)

Photo by [Goran Ivos](https://unsplash.com/@goran_ivos?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on [Unsplash](https://unsplash.com/s/photos/data-security?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText)

An increasing number of organizations are using corporate data to make key strategic choices when making business decisions. According to research, organizations are using data as a major strategic asset to gain a competitive advantage. However, data must be governed just like any other asset.

In this article, we'll look at what data governance is, why it matters, and the best practices to implement it.

What Is Data Governance?
------------------------

Data governance is a notion in data management that refers to the ability of an organization to guarantee high data quality over the whole life cycle of the data. It describes the procedures and job duties necessary for ensuring the accuracy and security of the data used by a company or organization. 

[Data security posture management](https://www.sentra.io/data-security-posture-management) aims to guarantee that sensitive data always has the appropriate security posture. These enable organizations to find all their sensitive data without having to create onerous rules or regex patterns. They offer full content- and context-driven data discovery.

Importance of Data Governance in an Organization
------------------------------------------------

![](https://lh5.googleusercontent.com/K-0CByqOmFhsrYiz-HoU5Olujdfp8PIaQ2UVwGx595bHRa2raoFLq67WK6U5is2E4hF862b2bt_e9WdLR9WPPWs-M2VlWjy-De-BpLqWjnw8OzQbPUjq6ApOb5Ul_VdY6_KmgVEssYsTppf2Wpq6sZ0dByIdX6yMllhny2Ko0cNnmlI5LGl_sns)

[Source](https://www.imperva.com/learn/data-security/data-governance/)

Arguably, data is an organization's most valuable resource. Data governance enables the protection, use, and accessibility of data. Better data analytics contribute to better decision-making and more operations support as a result of effective data governance. Additionally, it assists in avoiding data discrepancies or inaccuracies, which can result in problems with integrity, subpar judgment, and a number of organizational concerns. 

Data governance is also crucial for [regulatory compliance](https://www.knowyourgovernment.net/data-governance-and-regulatory-compliance/)---ensuring that organizations consistently comply with all regulatory obligations. This is essential for lowering operational expenses and limiting hazards.

Why Data Governance Matters
---------------------------

Data governance is the management of data and processes to make data a consistent, secure, and well-organized asset that complies with rules and regulations. Everyone on the team benefits from effective data governance throughout the entire organization. Many use cases can be addressed by data governance, but data governance adds value to various situations in comparable ways.

### It provides a framework for teams

Through a common language, data governance offers a framework for teamwork. Teammates within and outside of departments can discuss and evaluate the same data. Clarifying roles and duties also removes uncertainty and facilitates collaboration and data processes.

### It makes data more beneficial

Data governance gives an organization's data context. Teams can use it to organize, record, and assess the value of the information assets that are already available. Data governance ensures all team members have access to the context they require to use data and generate valuable insights by defining terminologies, establishing controls, and more.

### It develops a shared understanding between teammates

Data governance enables teammates from different departments to create business terms, KPIs, rules, and other concepts. As a result, organizations develop a shared understanding and use the same reliable information by developing this shared language.

What Are the Best Practices for Data Governance?
------------------------------------------------

[Building](https://www.talend.com/resources/building-data-governance-framework/) a solid data governance framework is a process. Therefore, it's vital to assess if your main goals are still clearly aligned periodically. The following are some best practices.

![](https://lh4.googleusercontent.com/ELnRsK2znCIS1TC97FX1_u_klM8IQdgRhE1FXy-kgq8DMMfN8LmCBZJ6rq-Y96epB4EdIdcb-CyRuUQr6VpaBhz9AjZ42i8G3MT1Wez952DMWa1QjfEpMeEdIdkpVmW_86YiWgzYY6qlhjed3QSar9aO39Gvptzx2ax-sonypk9Y7X8lNb1GfA0)

[Source](https://www.pinterest.co.uk/pin/365917538463896665/)

### Set goals

Clear measurements and KPIs should be included in a solid data governance strategy to track development over time. Goal-setting should involve business leaders as well to ensure organizational alignment and policy enforcement.

### Implement technology strategically

The truth is that there are a lot of amazing technologies out there that take advantage of brand-new ways to find data and tag phrases to speed up data recognition. 

### Define clear roles

Data can be changed and deleted. As a result, you should be able to create audit trails and data lineages with all users who interact with data over the whole lifecycle so that the appropriate parties are held responsible.

### Establish communication between teammates

Make sure that your employees are always kept in the loop about the creation and application of your data governance systems and procedures. It's important to stay in touch frequently with each and every teammate and partner. 

### Limit data restrictions

It can be tempting to impose severe restrictions on data access, but doing so can cause the organization to run much more slowly, increasing the chance of project failure and lagging behind the competition. Instead, try to learn how the data is handled before making judgments.

Implementing Data Governance
----------------------------

Implementing data governance in your organization is pretty simple. Create a data governance program that first considers the people, processes, and technologies. Now, establish goals, decision-making mechanisms, and decision-making rights appropriate for the teams, and select data managers to act as the go-to data authorities in their particular fields. Conduct a data audit to identify all the data sources being used, their present state, and the number of variations and versions of the same data that are available and being used. 

After establishing data managers and [auditing](https://www.techopedia.com/definition/28032/data-audit) the data, establish a procedure for integrating new data sources in a way that ensures they adhere to availability and quality standards. Business users typically identify and recommend new, important data sources during this phase, and IT will successfully operationalize them. Finally, construct a data architecture that enables consolidation and directs users to a shared, accurate data platform.

Conclusion
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Data governance establishes the guidelines that must be observed by everyone in the organization while engaging with the data. Strong governance guarantees both high-quality data creation and storage security when it is accessed. Lastly, data governance ensures that the organization stays in compliance with the law in every country in which it conducts business.