From the course: Introduction to Career Skills in Data Analytics

Understanding how data governance impacts the data analyst

From the course: Introduction to Career Skills in Data Analytics

Understanding how data governance impacts the data analyst

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- Have you ever asked permission to gain access to data and been denied? Have you ever asked for permissions and just been given global admin when all you needed was read permissions? If so, then you've been a part of the data governance of the organization, or the lack of it. Data governance is a framework that incorporates strategies to create solid quality data, enable accountability, and provide transparency to the data in the organization. Data governance has processes, procedures, and people at various levels of the organization. It's meant to control every aspect of the data in the organization. Data governance can support quality of data, accountability, trust, and compliance. There is some form of data governance in every organization at every size and level. If you work in a regulated industry, then data governance will likely be more mature than other industries. I have worked in almost every size industry, regulated or not regulated, and I'm either at the mercy of the data governance or protecting myself for the lack of it. Here are some common components of data governance that directly impacts the data analyst. Access to information, how you can access it. There is typically a chain of command and the data analyst is rarely meant to be the top of it. If you need access to information, there is someone that you will request permission to gain access to the information like your manager. Once they hear the request, they will typically instruct you to contact the next person responsible, or they will contact them on your behalf. I once requested access to the back end of a system to my manager. He then sent the request to the technology department who then between the two parties agreed I could have it. Little did I know it would go to a third person to implement it and notify me. The third person was the person in the cube to my left. I ate lunch with him every day. It was very controlled, and I did not understand it at the time, but now I have an appreciation of it. As a data analyst, we seek the source of truth, the golden record, and data governance is a part of providing that. We want to make sure there's an identifiable truth and that we can trust what we're working with. When we do not have at least two or three of these components to work with, we'll deal with challenges. For example, you may have been given more access than you need, and it might leave you wondering which data set you could really trust. Master data management is also a key component of the data governance framework. Making sure that the data we all need is complete, accurate, and meets the business rules. This is one area where organizations that do not have a strong data governance plan or strategy will have suffering data analysts. You may find yourself always correcting something as simple as a product name that have been entered incorrectly, but are literally the same product. You might be constantly customer address information. I'm always telling organizations that regardless of regulations, they have a data governance plan in place, whether they documented it or not. As a data analyst, determining the data governance plan at your organization will help you to know who to talk to, when to talk to them, and how to adequately follow the process of all things that relate to the life cycle of data at the organization.

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