by Data governance will once again become an important topic and topic for enterprise CIOs this year. The vigorous development of AI technology has set off a wave of AI in enterprises in the past few years. After a period of time, enterprises often find that the key to the success of AI models is not only technology, but also good data, especially AI models need to be continuously optimized and corrected , need to have an endless stream of data and information to support. Many companies have seen the power of AI, but also found that the materials on hand are not enough to use. In the past two years, after actively embracing AI, many large companies have turned their heads to re-squat, inventoryed and sorted out the big data in their hands, and even rebuilt the data collection mechanism, integrated more data channels and sources, and redesigned the data. The workflow and the construction of a new generation of data lakes or cloud data warehouses are all to store the data ammunition library needed by AI weapons. However, the more, more extensive, and more diverse data an enterprise has, the new issue of data governance (Data Governance) will be faced.
