The importance of data governance in AI

The relevance of data governance has much more to do than just managing the behemoth data within an organization’s repository. The organizational-level practice, data governance focuses on improving the accessibility, integrity, quality, and above all, the trustworthiness of data assets. In a time, when AI and ML are relied upon for various business activities, most importantly for data-driven decision making, it is the quality of data that will influence business outcomes than the power and capabilities of these sophisticated algorithms.



Remember the saying “Garbage in Garbage out” – similarly, it is the quality and integrity of the input data that will impact the output of the frontier technologies, like AI, ML, Data analytics, etc, which in turn will affect the business value. Hence, it is necessary for businesses to ensure the quality and integrity of their organization’s data to forge ahead in today’s data-driven world.



Why data governance is essential for your AI success?



The first and foremost reason for the development of a data governance process is to address the data-related conflicts that are innate in an organization. For example, a customer’s name could be listed differently across customer service systems, sales, and logistics. This could affect the consistency and integrity ...


Read More on Datafloq