Data Governance: Use Cases and Ways of Implementation

Data statistics

We live in the era of overflowing data. It’s everywhere, especially when it comes to businesses.

Nowadays, companies gather more and more unstructured and cluttered data, thus it becomes more and more important to know how to manage it effectively and not let it hinder business performance.

In fact, a dataset when governed effectively is supposed to leverage a lot of processes and bring an organization plenty of opportunities for growth.

In this article, we are going to dive deep into data governance. We will explain to you what data management/governance  is, what are the main data governance use cases, why it’s important for companies, and so much more. Let’s get started!

Main Use Cases of Data Governance

Before we will showcase the core business use cases for data governance, let’s start with the simple definition of data governance. So what is it?

Data governance is a set of certain standards, policies, and processes that are aimed at making the use of data and documents more effective and efficient which will help in achieving the company’s objectives. It is a data governance framework that enables businesses and organizations to better manage their data assets.

Even though data governance challenges are inevitable, here are the main benefits that data governance can bring to companies:

benefits of data governance

Data quality can make a big difference for companies. Evaluating data governance rules and standards allows organizations to reduce risks, minimize operational costs, optimize their workflows, and so much more.

By focusing on and optimizing your database governance as part of your business or enterprise software strategy it’s possible not only to improve operational processes within your organization but also with your clients as well.

Moreover, data governance fundamentally impacts master data management, increases the efficiency of a data management process and value from data, and improves data quality.

Now, we can proceed to explore the main use cases of data governance:

  • Self-service business intelligence. As self-service BI is a main priority of many organizations, data governance can help a lot. The information about data sets and reports will be easily accessible and available in a well-governed environment. It would be possible for users to quickly review and compare data, and understand its quality, and source. Therefore, data governance will facilitate the decision-making process and will make it more likely for a self-service BI program to succeed.
  • Personal information protection. When it comes to sensitive data, it’s important to understand where this personal information is captured and stored. In case of a data breach, it’s crucial to assess the overall impact as well as notify data subjects affected by the breach. And data governance is completely about it. It helps to understand who is accountable for data, to set policies for data use and access, and to define processes to solve issues with data.
  • Master data management. For making master data management successful, a high degree of engagement & decision-making across data silos is required. Without it, implementing a technology solution won’t be possible. Data governance can help make master data projects easier and allow them to reach final completion.
  • Digital customer experience. With the increased adoption of digital channels by businesses, the need for data collection also increases. Effective and quality data management might enable the simple collection, storage, and analysis of clients’ data, thus giving more opportunities for delivering positive experiences.

Let’s take a look at other most important and valuable data management use cases.

team working

Grounded Data Analytics for Companies

We all know how data analytics helps with operational processes as well as with business decision-making. As more companies are becoming data-driven, you should know that effective data governance can also help companies create grounded data analytics.

For ultimate success, it’s important for data to be easily accessible to all business users and employees. Sometimes it’s not possible to access and analyze existing data as a relevant specialist is required.

In this case, data management plays a crucial role as it eliminates this blocker by enabling anyone to access and analyze data without extra professional or special tech training.

With effective data governance, it’s possible to analyze multiple data sets simultaneously and share the results with ease while improving the overall data availability.

Every business and organization possess plenty of sensitive data that can be subject to malicious attacks, misusage, and breaches. Therefore, protecting data and following privacy compliance standards are paramount. The regulations like GDPR or IAPP are meant to protect customers’ personally identifiable information. However, at the same time, these regulations also create plenty of risks for companies.

Optimizing your data governance practices will help you leverage those risks while having your client’s best interests in mind. Data management can assist you in identifying the place where this sensitive client data is stored, providing the data to customers if needed, deleting data if requested, simplifying the auditing process, organizing and reporting privacy terms, etc.

big data

Data: Collection, Structuring, and Access Control

If the company works with large amounts of data, data governance can be very helpful as it enables the creation of certain standards for data collection and structuring. Moreover, there are a lot of risks associated with big volumes of data stored. It’s pivotal to manage carefully who can access this data.

For example, if data is stored in multiple places, it’s difficult to make sure that all employees can easily access the data needed, and it’s even more challenging to perform audits. On the contrary, even if data is stored in a single location, it’s pretty difficult to manage permissions so the right data can be accessed only by the right employees.

Efficient data access governance can improve the situation as it makes it possible for simple and streamlined data access no matter where it’s stored. Automation allows businesses to classify data, come up with data policies, and achieve full control over all data they possess.

Creation of Terminology and Technical Metadata

Last but not least, data governance tools can work effectively with databases, and build up a business glossary across your organization which is possible to continue updating as the business evolves and expands.

This glossary can include specific company terms & definitions, technical metadata, data classification, and so much more if needed. It will allow all new employees to access it easily and get familiar with the basics.

Data Governance Impact on ML and AI outcomes

It’s worth noting that 97.2% of organizations are investing in big data and AI. Efficient data governance can play a huge role in the successful outcomes of artificial intelligence and machine learning implementation.

It’s important to remember that the effectiveness of ML and AI systems depends on the scale and diversity of the data as well as on its cleanliness. Investing in data management will help to achieve this data quality.

Even the top AI systems can fail in case the data used is not properly governed and didn't pass through quality checks and data governance is the right solution.

coding process

Intellectsoft’s Approach to Data Governance

We hope this article about data governance use case examples shed a light on this burning topic. Our professionals believe that data governance is very important and can help companies achieve ultimate success, facilitate workflow, and drive more revenue in the future.

Intellectsoft is a reliable software development and IT consulting partner with an impeccable reputation and strong corporate culture and ethics. Our team has more than 15 years of experience in the field of enterprise software development as well as other services we recommend you get familiar with.

We have collaborated with dozens of renowned global companies as well as Fortune 500 businesses across various industries. Intellectsoft has specialists with exceptional knowledge of fintech, healthcare, construction, and other industries.

In addition, we encourage you to take a look at the list of our most prominent client cases that will show you how Intellectsoft’s expertise enabled us to deliver effective solutions that transformed our clients’ businesses.

If you have any questions left — don’t hesitate to get in touch with us and our managers will get back to you to provide all the information needed. We can start developing the solution that will take your business to a whole new level. Start your digital transformation with us!


What Are the Pillars of Data Governance? 

To enable companies to optimize their data governance, it’s important to know about the main pillars effective data management is based on.

By adhering to them, you increase your chances of success. These pillars include developing standards, setting policies and processes, framing the organizational structure, and using technologies.

Is Data Privacy Part of Data Governance?

Yes, data privacy is considered the branch of data governance that handles personal data and makes sure it complies with all data protection laws, and regulations, and corresponds to overall data privacy best practices.

It’s crucial to protect an organization's data from unauthorized access as well as maintain data integrity. Therefore, data privacy and data governance should be one of the top business priorities.

What are the main data governance use cases? 

Although there are plenty of use cases of data governance, the most popular ones include data analytics, or other data products, data privacy compliance, data collection and structuring, access control, etc.

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