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What is Data Governance?

Data Governance Definition

Data Governance is a four-way framework comprising availability, applicability, integrity, and security. It is a set of processes, used by the stakeholders who use technology, to ensure that the important and critical data is managed and protected. It involves a streamlined coordination of individuals (people), methods (processes), and innovation (technology) in such an order that it results in realizing the value of data for any organization. It acts as a bridge between business and IT for decisions and initiatives. While people, process and technology are at the core of good Data Governance, technology is only an enabler not an essential for Data Governance. It has to be implemented as a disciplined workflow within the organisation. Without that discipline, data would never be treated as a valuable commodity.

Why is Data Governance important?

Data Governance is required to ensure that an organization’s information assets are formally, properly, proactively and efficiently managed throughout the enterprise to secure its trust & accountability.

Data Governance comprises the collecting of data, revising and standardizing it, and making it good for use. It makes the data consistent. Data Governance ensures that critical data is available at the right time to the right person, in a standardized and reliable form. This infers into better organization of business operations. Adopting and implementing Data Governance can result in improved productivity and efficiency of an organization.

Various methodologies for Data Governance

What is not known cannot be protected. This saying is all the more prominent for cyber security. Leading research shows that 65% do not have the ability to detect data breaches witData Governance must be viewed as an enterprise effort. You can implement it in segments, but it must always and necessarily have an enterprise perspective. For that, first a governance body must be established which creates the necessary strategy and policy for the organization. This is not a one-time exercise, but an ongoing effort that requires monitoring and maintenance. Continual monitoring, maintenance, and review of the data is crucial and important. The success of any Data Governance program can be obtained through effective communication amongst IT, Business Units and data stakeholders. Other success factors include sufficient documentation and communication of changes, issues, and tasks in a streamlined, pre-defined communication plan. A secure, high-performing Data Governance program will assist any organization to leverage its genuine business-worthy data with the help of appropriate technology solutions, when deemed necessary. The end objective of any Data Governance program is to enable organizations effectively react to challenges and opportunities posed by the market, by adopting the “Data First” philosophy.

What are some of the tools and technologies used for Cyber Protection?

As in case of any other program, cultural differences and silo-ed approaches to data acquisition and management create barriers in forming and sustaining a Data Governance program along with the lack of sustained senior business sponsorship. An improper foundation and absence of metrics are other reasons of a Data Governance fail. A proper foundation includes: proper data management, data models, metadata, etc. Fundamentally, a strong foundation of what needs to be governed is the most basic requirement for Data Governance.

An organization cannot be transformed overnight, especially in a labor-intensive program such as Data Governance. Expecting a radical change from a ‘no-program’ stage to an ‘enterprise-wide’ program in a few months is an unrealistic expectation and can lead to Data Governance failure. Underestimating the amount of work to be done, over-planning and less execution, lack of a sustained line/business commitment and absence of program staff/office also are some contributing reasons for Data Governance to fail. Planning, scoping and executing a Data Governance program can be challenging, it can therefore be done in stages to achieve the desired outcomes.

Data Governance Portfolio


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