To ensure success, it’s crucial to begin by asking why. Why are we taking a certain action or making a specific plan? This mindset applies particularly well to data governance. Organizations may choose to implement data governance for a variety of reasons. Here are some of my thoughts on the subject.
In today’s age, data is one of the most valuable assets a business can have. It drives decision-making, powers innovation and helps organizations stay competitive. However, with the amount of data growing at an unprecedented rate, managing and governing that data has become increasingly complex and critical. This is where data governance comes in.
Data governance supports managing data as a strategic asset. It involves the development and enforcement of policies, standards, procedures, and guidelines for data as well as defined roles and responsibilities to support it all. In short, data governance helps organizations ensure the availability, reusability, quality, security, and compliance of their data.
So why is data governance important for businesses?
Here are a few possible value drivers:
- Increase in revenue by better utilization of data assets: With good data governance in place, organizations can more effectively use their data assets to create data products, gain insights, and make data-driven decisions, leading to better performance, optimization, and process improvement.
- Better decision-making with the support of better data quality and common understanding of data: With data governance in place, organizations can better ensure that the data they use is accurate, complete, consistent, and understandable. This leads to more effective decision-making and a greater return on investment in data projects. Fit-for-purpose data quality is crucial when implementing AI/ML models, and based on studies, one of the key reasons why these development projects fail is bad quality data.
- Support efficient data development by ensuring the creation of reusable data assets: With data governance in place, organizations can develop standardized data models and create reusable data assets. This reduces the need for redundant data processing and storage and allows for more efficient development of new data products and applications. Additionally, it reduces the likelihood of errors and inconsistencies in data, leading to improved data quality and greater confidence in the accuracy of data-driven decision-making.
Here are a few possible risk avoidance drivers:
- Increase in revenue by better utilization of data assets: Improved compliance to avoid bad publicity and possible fines: In an age where data-related regulations are becoming increasingly strict, data governance can help organizations comply with laws and regulations such as GDPR or the upcoming EU Data and AI Acts. Failure to comply can result in significant fines and reputational damage.
- Ensure sufficient understanding of sensitive data to make sure customers data is safe: Data breaches can cause severe damage to a business, both financially and reputationally. Data governance provides organizations with a comprehensive understanding of their sensitive data, enabling them to implement effective security measures to protect it. By safeguarding customer data, businesses can build trust and maintain their reputation in the market.