Data Governance

Why does Data Governance play a vital role for organizations?


-Data Governance helps organizations manage their data as a critical enterprise asset-

In an increasingly data-driven world, the ability to process and use large amounts of data becomes critical for businesses that want to remain competitive. This is where data governance comes in, as it provides the tools, standards, and practices that help collect, store, analyze, and access data appropriately. As its value becomes more apparent, more companies are willing to invest in data governance. Thus, the relevant market size reached $2.09 billion in 2021 and is expected to reach $10.93 billion by 2030 with a CAGR of 21.2% (N-IX, 2023).

Global data governance market size growth

Not only is data at the heart of most business operations, but there is increasing pressure from customers to see what is being stored, how and why. Yet some 40 percent of enterprise data is “either inaccurate, incomplete, or unavailable.” That results in an annual loss of approximately $14 million. For this reason, it is crucial to have a clear understanding of data governance and the different ways you should implement it (dataversity, 2020).

If you are not sure what and why data governance is, we invite you to follow this article to learn more about the basics of data governance. Also, if you need a free consultation by OMEKTA data science team, you can contact us.

What is Data governance?

Data governance is a process through which the organization can manage the quantity, compatibility, usability, security and access to data.

  • Data governance is an essential part of an effective enterprise information management program that seeks to manage data by establishing rules, processes, standards, solutions, training and organizational structure.
  • Data governance is based on agreed upon models that describe who can take what actions with what information when, under what conditions and using what method.
  • Deploying data governance is not a project that can be done in a limited amount of time, but rather an iterative process.

Why data governance?

Although the implementation of data governance can face challenges such as cultural and organizational barriers, financial factors, security and privacy factors, lack of technological infrastructure, etc., but its benefits have led to organizations seeking to survive in competitive markets. establish the foundations of governance. Some of the benefits of data governance are summarized below:

Some of the use cases of data governance are:

  • Self-service BI

The role of data governance (DG) in self-service business intelligence (BI) is crucial to ensure effective and responsible use of data by business users. Self-service BI allows users to access and analyze data without relying on IT or data professionals. While self-service BI offers agility and flexibility, potential risks and challenges related to data quality, security, and compliance must also be considered.

In this regard, data governance plays a vital role in self-service BI by ensuring the accuracy and quality of data. Establishes data quality standards, enforces access controls, and promotes regulatory compliance. In addition, data governance facilitates collaboration among users and enables effective data sharing and knowledge exchange. By implementing data governance practices, organizations can increase data integrity, security, and compliance in self-service BI environments, leading to better decision-making and insights.

  • Digital customer experience

As businesses’ adoption of digital channels increases, so does the need for data collection. Data governance is critical to increasing the business impact of digital customer service. It ensures accurate and reliable customer data and enables organizations to personalize interactions and deliver tailored experiences. By maintaining compliance with data privacy regulations, data governance builds customer trust and mitigates potential risks. It also facilitates data-driven insights and enables organizations to make informed decisions. Ultimately, data governance enables businesses to create consistent, integrated, and personalized experiences that increase customer satisfaction and loyalty.

  • Master Data Management

Key data management (MDM) is a comprehensive approach to managing an organization’s critical data. Key data includes key entities such as customers, products, suppliers, employees, and other key elements of the organization. The goal of MDM is to provide a single, reliable source of master data across the organization that ensures consistency, accuracy, and integrity.

Data governance (DG) plays an important role in MDM by establishing policies, processes, and guidelines for the effective management of master data. DG defines data standards, ownership and stewardship responsibilities and ensures data quality and regulatory compliance. It sets data policies, monitors compliance, and enables data-driven decision making. The DG works closely with data custodians to enforce policies, resolve data issues, and maintain the overall health of master data.

  • Big data management

If the organization is dealing with a large amount of data, data governance can be very useful because it enables the establishment of specific standards for data collection and structure. In addition, there are many risks associated with large amounts of stored data. Carefully managing who can access this data is critical.

For example, if data is stored in multiple locations, it is difficult to ensure that all employees can easily access the data they need, and even more challenging to conduct audits. Conversely, even if the data is stored in one place, permissions are very difficult to manage, so the right data can only be accessed by the right employees. Efficient data access management can improve the situation because it enables simple and efficient access to data regardless of where it is stored. Automation allows businesses to categorize data, provide data policies, and maintain complete control over all the data they have.

  • Success in exploiting machine learning and artificial intelligence projects

The effectiveness of ML and AI systems depends on the scale and variety of data, as well as on the quality and integrity of the data. Investing in data management helps achieve this data quality. Even the best AI systems can fail if the data used is not properly controlled and passed quality checks. In this regard, data governance plays a key role as the infrastructure of ML and AI projects, the business value of the products. And it increases the services of this area and reduces the possible risks.

  • Creation and management of metadata

Data governance is responsible for creating and managing unified terminology and technical metadata to ensure unified data operations. By creating standardized vocabularies and definitions, organizations achieve consistent communication and understanding among different data elements. Metadata provides detailed insights into data structure, format, relationships, and ancestry, enabling seamless integration and interoperability. Data governance teams work with stakeholders to create data dictionaries and guidelines, and to promote accurate and consistent terminology and metadata. This integrated approach increases data quality, facilitates efficient data management, and supports effective decision-making processes in the organization.

Does your organization need to establish data governance?

All organizations must be able to make decisions about how to manage data, realize the value of data, minimize costs and complexity, manage risk and ensure compliance with evolving legal, regulatory and other requirements.

Data governance is critical for large companies, SMEs, government agencies, non-profit organizations and startups, as it ensures consistency, standardization and compliance across different data sources and systems. By implementing data governance practices, organizations can streamline data processes, strengthen decision-making, and protect sensitive information. This is especially critical for companies with big data and for government agencies that manage citizen data. Data governance helps organizations of all sizes and types maximize the value of their data and maintain their competitive advantage.