The advent of advanced technologies like blockchain, cryptocurrency, etc. has posed threats to the humongous data of the organisations at voluminous scale hindering day to day activities of the institution which paves way for governance of data at every level of the organisation defining roles and responsibilities of each and every member. Data governance is one such way of collocating and administering policies, plan of action and calibre for the tacit usage of organisation's structured or unstructured information with the focus on 5 V's—namely, volume, veracity, value, variety, and velocity. The chapter focuses on providing the details of the need of data governance, the tools used, data governance framework, challenges posed to models of data governance and its solution.
Data that sit unused are no different from data that were never collected in the first place. -Doug Fisher
TopIntroduction
With the augmented magnification of data, a stringent regulatory skeleton with transparent data notions, standardization and processes to expeditiously and precisely capture and storing of data is necessary which can be quickly outpoured, perpetuated, sustained and transported. Data governance(Abraham et. al., 2019) is the hegemony and stewardship of the organizational data of worldly possessions which encompasses the fabrication of plan of action and specifications that ensure that data is precise, thoroughgoing and reliable. Data Governance Institute defines the term as the practice of collocating and administering policies, plan of action and caliber for the tacit usage of organization’s structured or unstructured information. The globe today is surrounded by big data which comprises the data of 5V’s (Kaur et. al., 2017), namely, volume, veracity, value, variety, and velocity as shown in Figure 1.
The protection of data determines the triumph of an organization’s business which makes it assertive to position a data governance framework to fit the organization’s demands along with delegation of roles and responsibilities on its operation relevant to critical information. The why element(Viljoen, 2021) in the context of securing data demands vital attention in correlation with should element to build a safe data driven erudition.
Figure 2 depicts the why aspect the data governance in pursuance of an organization.
Data governance manifest the subpoena to systematize, intermingle, fortify and accumulate the institutional data. The key goals that thwack the calculated, adroit and serviceable levels include:
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Reducing data security risks
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Subpoena intricate rules for data usage
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Intermingling compliance requisites
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Upgrading internal and external communication
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Rocketing the value of data
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Opening the door for a vigorous foundation for the continued existence of the company through risk management and optimization
Figure 3. Key components of data governance process
The foundation of management of data provides an outlay(Benfeldt et. al., 2020), onus and sound judgement to hold sway over the organization’s data. The key components of data governance process hold key as depicted in Figure 3 which are:
The professionals, stewards of data, and relevant key business and information technology personnel are the mainstays of a data governance program who establishes and develops outlays to ensure that the enterprise requisites are met.
The manpower involved play a critical role in the evolution and accomplishment of roadmap of an organization’s systematize data which is a governing document that provides high-level enterprise requisites for data and ensures that those requisites are met, an indispensable step in the organization’s managerial journey of data.