Data governance has been around for a while. As a result of this, there have been various trends and challenges that have influenced this field. in this post, we will look at several laws that have had an impact on data governance along with various concepts that have been developed to address common concerns.

Laws

Several laws have played a critical role in influencing data governance both in the USA and internationally. For example, the Sarbanes-Oxley (SOX) Act was enacted in 2002. The SOX act was created in reaction to various accounting scandals at the time and large corporations. Among some of the requirements of this law are setting standards for financial and corporate reporting and the need for executives to verify or attest that the financial information is correct. Naturally, this requires data governance to make sure that the data is appropriate so that these requirements can be met.

There are also several laws related to privacy in particular. Focusing again on the USA there is the Health Insurance Portability and Accountability (HIPAA) which requires institutions in the medical field to protect patient data. For leaders in data, they must develop data governance policies that protect medical information.

In the state of California, there is the California Consumers Protection Act (CCPA) which allows California residents more control over how their personal data is handled by companies. The CCPA is focused much more on the collection and selling of personal data as this has become a lucrative industry in the data world.

At the international level, there is the General Data Protection Regulation (GDPR). The GDPR is a privacy law that applies to anybody who lives in the EU. What this implies is that a company in another part of the world that has customers in the EU must abide by this law as well. As such, this is one example of a local law related to data governance that can have a global impact.

Various Concepts that Support Data Governance

Data governance was around much earlier than the laws described above. However, several different concepts and strategies were developed to address transparency and privacy as explained below.

Data classification and retention deals with the level of confidentiality of the data and policies for data destruction. For example, social security numbers is a form of data that is highly confidential while the types of shoes a store sells would probably not be considered private. In addition, some data is not meant to be kept forever. For example, consumers may request their information be removed from a website such as credit card numbers. In such a situation there must be a way for this data to be removed permanently from the system.

Data management is focused on consistency and transparency. There must be a master copy of data to serve as a backup and for checking the accuracy of other copies. In addition, there must be some form of data reference management to identify and map datasets through some general identification such as zip code or state.

Lastly, metadata management deals with data that describes the data. By providing this information it is possible to search and catalog data

Conclusion

Data governance will continue to be influenced by the laws and context of the world. With new challenges will be new ways to satisfy the concerns of both lawmakers and the general public.