Along with the pervasiveness of information technology, the amount of data generated by human beings is growing at an exponential rate. Such massive data requires management with new methodologies. Data governance is the management of data for an organization (enterprise or government) as a strategic asset, from the collection of data to a set of management mechanisms for processing and applications, aiming to improve data quality, achieve a wide range of data sharing, and ultimately maximize the data value. Research and development on big data is nowadays popular in various domains, but big data governance is still in its infancy, and the decision-making of an organization cannot be separated from excellent data governance. This paper first introduces the concepts, developments, and necessity of data governance and big data governance, then analyzes existing data governance technologies-data specification, data cleaning, data exchange, and data integration, and also discusses the maturity measurement and framework design of data governance. Based on these introductions, analyses and reviews, the paper puts forward a "HAO governance" model for big data governance, which aims to facilitate HAO Intelligence with human intelligence (HI), artificial intelligence (AI), and organizational intelligence (OI), and then instantiates the "HAO governance" model with public security data governance as an example. Finally, the paper summarizes data governance with its challenges and opportunities.