What Is Data Governance And Why Do You Need It?

Data governance is increasingly becoming important. Data governance sets the framework for the processing and use of data within the company, thereby increasing the aggregation of data. Data governance can therefore be an important factor in the development of data science and artificial intelligence.

But what is data governance, why is it useful and what are the benefits for business? These questions are explored below.

What Is Data Governance?

Data governance is of particular interest and importance for companies that collect large amounts of data from different channels, and for companies that want to integrate more data into their solutions. Data governance is about controlling data-driven business activities and supporting the governance of business data. 

Data governance defines the structural framework for employees and the internal rules and requirements for data use and application within the company. The rules and requirements also cover decision-making responsibilities and rights as well as data security measures. This means that the company itself decides who has access to what data and under what circumstances. The motto is: the more, the less. These standards can vary depending on the culture and values of the company and serve as guidelines for data analysis, data warehousing and interpretation. Data governance supports the company’s data management strategy.

Data governance is a business value in addition to data security. Therefore, data governance can create the structural conditions for better exploiting the potential of data through data science. This adds value to the business and contributes to its sustainability and success. Therefore, the introduction of data governance is important to preserve the relevance of data, to manage it more professionally and to prevent harm.

What Includes Data Governance?

Data governance can be divided into 5 aspects:

• Data Quality
• Data Maintenance
• Data Protection
• Data Security
• Data Compliance

Compliance with the five points mentioned above can be achieved by a data governance policy that sets out all the requirements. A good data governance plan is a benchmark for quality assurance and ensures the quality of data.

It ensures data accuracy, integration and consistency. Data science and artificial intelligence initiatives are also encouraged. It also means that data is maintained in accordance with the standard. Data governance also needs to comply with company-specific requirements and the General Data Protection Regulation (GDPR) so that companies know exactly where personal or sensitive data is stored. This is in line with data protection compliance so that the company can manage data breaches and the resulting sanctions. In addition, data is better protected and easier to track through data governance requirements that are compatible with data privacy and security.

For example, data governance can be facilitated by appropriate software solutions. For example, the Informatica data science platform addresses the issue of data governance. These functions can be used to control and monitor rights, roles and access to data within the company, and to enforce rules.

Reasons To Implement Data Governance

Improving data quality through data governance can increase the efficiency of processes and employees. Therefore, less work is needed to manage data. By collecting data, complex decisions can be made faster and better within the company. This increases competitiveness in the digital age. It also saves additional costs.

Just as an ERP system helps to determine where products are stored, data governance helps to create transparency about the data in the company.

Still not sure how to get started? Let’s see how a professional data governance consulting service can make it work right for you!