Gartner says that data and analytics budgets continue to see large increases and a significant portion of them are spent on data governance policies. According to Cisco, nearly 5 quintillion bytes of data is produced every day and another report by Forbes suggests that 95% of businesses cite the need to manage unstructured data as a major problem for their enterprise. Data governance solutions help enterprises to tackle these challenges with effective data management solutions that can prevent data duplication and loss. The Big Data Governance market is set to be worth $5.28 billion by 2026.

A good data governance policy meets the security, compliance and privacy standards of an enterprise while continuously improving the availability, usability, quality and reliability of data. It is also important to ensure that if a CEO and marketing executive look at a set of revenue figures, they see the same numbers and understand them to mean the same thing. If stakeholders are unable to understand and trust the data, they will stop using them and simply make decisions without the relevant data.

Big data governance is less about the technology and more about operationalizing and ensuring an enterprise is equipped to support the massive amounts of data coming in effectively. A successful data structure system results in having a clear understanding of where data comes from and who owns what. Also, it results in following known processes when data changes are required.

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Best Practices in Big Data Governance:

Start small and keep it simple:

Big data governance is the convergence of people, process and technology. To build your big picture, first start with the people, then establish your processes and finally incorporate the technology. Develop the technology in a way that is thoughtful and linear, to govern from a centralized location. Keep your data governance architecture simple; fewer well-governed dashboards are better than many ungoverned ones. It can take many steps to reach a maturity scale, but keeping the system simple and robust will deliver consistency in the long run. Enterprises may begin by focusing on few issues and then moving it to a larger level.

Build a business case:

For many organizations, the need for big data governance may appear obvious, but it might not always be the case. Hence, it is vital to build a strong business case by identifying the benefits and opportunities that good data quality will bring. Big data governance can significantly increase the confidence of decision-makers in the data they use to make strategic and tactical choices.

Understanding consequences is key:

Help stakeholders to understand the time, energy and revenue required to make your enterprise data governance vision a reality. While most will agree that poor data quality and poor data management is a problem, only a few are truly committed to driving change in an enterprise. Poor data governance can attract heavy penalties, loss of brand value and cause setbacks. On the other hand, good data governance can uncover inefficiencies and shortcomings and when those issues are addressed it can be beneficial in terms of cost saving and mitigating risk.

Validate data sources:

Different types of data, in different formats, coming in from different sources in bulk amounts pose a variety of data challenges. To keep a big data environment healthy and trustworthy, it is essential to leverage technologies and monitoring tools that are up-to-date. In addition to cataloging data domains, it is also important to know how they relate to one another; that is validating data sources, understanding integration points, error resolution process and tracking them at each step along the way.

Identify roles & responsibilities:

Big data governance is teamwork and requires the cooperation of all departments. Defining role, responsibilities and ownership clearly is the backbone of every data governance program and it is advised to take time and assign the roles with care. Determining authority establishes an intelligent structure to handle data governance as one powerful team. Set up a data governance council, who will act as a steering committee on a strategic level and a data governance board for a tactical approach. Assign data managers, data owners, data stewards and arm all employees with data awareness for enhanced results.

Prioritize quick wins:

Prioritize issues and identify specific outcomes that can be achieved quickly. Starting with smaller pilots and using the learnings to take on more comprehensive initiatives can help. It is crucial to inform and educate executive management and all stakeholders about early wins when embarking on data governance initiatives. The road to big data governance does not have a finish line and is a continuous, iterative process that can bring tremendous results.

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