Data Governance and its Importance

 

Data is the most valuable asset in any organization. It requires a set of careful management practices, a collaboration of its integrated resources, and an efficient governing structure to retain its integrity during different phases of the data lifecycle.  Suppose a company needs to cope with the fast-moving trends of enterprises today. In that case, they need to formulate robust Data governing policy (Panian, 2010).

Data Governance:

Data Governance is broadly defined as a system of processes, policies, roles, standards, and metrics to ensure efficient use of information to help an organization achieve its goals. It addresses functions and responsibilities required for retaining data integrity and quality with security in any enterprise. The quality of data is measured by its relevance, inclusiveness, precision, and reliability, along with effective data management (Cheong & Chang, 2007). However, it is neither data management nor data stewardship; rather, it is the planning stage of allocating the right resources for data responsibilities (What is Data Governance (and Do I Need It)? - Talend, 2021). If accessibility, availability, quality, consistency, auditability, and security of the data are the key attributes that should be managed and developed to enhance the value of data for the organization (Fisher, 2009). The data governance process includes policies and operations of an enterprise that are deployed to handle big data. The careful management, storage, and documentation of high-quality data at every step of the data lifecycle are carried out utilizing these policies ( The Cloud Team, 2021).

There are three basic goals of Data governance in any organization (Panian, 2010):

• To ensure that the data retained in the organization is relevant to the needs of business.
• To carefully manage and protect data in an organization
• To reduce the cost of data management in an organization.

To achieve the goals of data governance, an organization must implement a carefully drafted framework to streamline the activities involved in data management. This framework must have a clear idea regarding control, roles, and expectations from data managers and the third parties involved in the processes (Breault, 2019).

Data Governance Framework:

Each organization requires a well-crafted data governance policy to secure and use their big data. It helps to narrow down the “business drivers” such as

•  Growing revenues by means of improved customer retention
•  lowered cost of operation by means of increased operation efficiency through   business automation and elimination of redundancy in an organization.
•  Ensuring process compliance with internal and external regulations and governing   policies through data reporting and auditing (Panian, 2010).

It is essential to select the business drivers which are consistent with the goals, responsibilities and processes involved in an organization for achieving their targets.

Several policies are drafted and interlinked to ensure error-free and smooth data governance, including data access policy, data usage policy, data classification policy, and data integrity policy. Each policy refers to different aspects and components of business for internal as well as external use (for the vendors) (the Cloud Team, 2021).

Each data governance system requires a set of rules, enforcement strategies, and management of the data to ensure effective data governance. Therefore, the policies, procedures, and the overall structure of the data governance policy should have a clear mission statement, measurable goals, metrics to measure the progress in the plans, and a thorough roadmap to understanding the hierarchy of responsibilities involved during this process (Hartman, 2018).

Components of Data Governance:

There are four basic components of data governance which should be considered to maintain the integrity of the data and its key attributes. The details are discussed as under:

• Standards:

It is essential for the organizations to establish standards (data definitions, define mater data, taxonomies, models, and technical standards) of data.

•  Policies and Processes:

Design, development, management, and control of audit of data provides basis for effective governance of data in an organization. It is essential for the companies to determine their rules for accessing and controlling, monitoring, and measuring data through progressive set of policies and processes.

• Structure of an organization:

Companies require clearly defined roles and responsibilities of managers, IT technicians, data stewards and data analysts to avoid issues pertaining data governance in an organization.

• Technology:

Technology plays an extremely important role in automation and enforcement of data governance policies and standards in an organization. The implications of using sophisticated data governing tools is unlimited. Companies may initiate their data defining and management through simple computer programs however, they require upgraded tools for accessing data quality, managing availability, and tackling the issues of data security (Mallory, 2006).

Advantages of Data Governance:

There are numerous benefits of implementing a data governance system in an organization. It helps to develop a shared understanding of the asset (data) in the organization. This is also helpful for effective communication of data with vendors. It allows developing a consistent and complete data resource for improved decision making easy data integration for enhanced business planning and financial performance to upscale a business in terms of profit maximization (Breault, 2019). Other advantages of data governance include:

• Improved efficiency through time and money saving through careful resource mobilization.
• Reduction in security threats through enhanced compliance with regulations.
• Clarity and confidence in the existing data sets.

        (Hartman, 2018).

Challenges in Data Governance:

There are various challenges encountered in the management of big data. Each data set arises due to inevitable processes and products; therefore, it is essential to categorize and manage data for better outcomes carefully. The data governance program must demonstrate the organization's business value by quantifiable data metrics along with accurate and quality data with minimum or reduced error rate.

Various types of structured, semi-structured, and mixed data are obtained from different platforms. Accuracy and accessibility of data for self-service customers are also significant challenges; while handling big data challenges, business analysts and data scientists (Stedman, 2021).

Enterprises today have a tremendous amount of data regarding their clients, suppliers, employees, customers, etc. Handling this data through the right tools is essential to understand better the market trends, target audience, and ROI of an organization. Therefore,  data governance is highly recommended to save an organization from chaotic events and financial losses.

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           References:

• Cheong, L.K. and Chang, V., 2007. The need for data governance: a case study. ACIS 2007 Proceedings, p.100.
• Talend - A Leader in Data Integration & Data Integrity. 2021. What is Data Governance (and Do I Need It)? - Talend. [online] Available at: <https://www.talend.com/resources/what-is-data-governance/> [Accessed 30 October 2021].
• Panian, Z., 2010. Some practical experiences in data governance. World Academy of Science, Engineering and Technology, 62(1), pp.939-946.
• Fisher, T., 2009. The data asset: How smart companies govern their data for business success (Vol. 24). John Wiley & Sons.
• Mallory, C., 2006. The Genesis of Data Quality: The emergent Data Steward. Available at http://www.firstlogic.com
• Breault, G., 2019. Data Governance: What Are The Benefits For Your Organization?. [online] HICX.com. Available at: <https://www.hicx.com/blog/data-governance-benefits-for-organisations/> [Accessed 30 October 2021].
• Hartman, L., 2018. 3 Reasons Why Data Governance is Important. [online] Blog.semarchy.com. Available at: <https://blog.semarchy.com/3-reasons-why-data-governance-is-important> [Accessed 30 October 2021].
• Stedman, C., 2021. What Is Data Governance and Why Does It Matter?. [online] Search Data Management. Available at: <https://searchdatamanagement.techtarget.com/definition/data-governance> [Accessed 30 October 2021].
• The Cloud team., 2021. Data Governance: Roles, Policies, and Challenges. [online] Cloud.netapp.com. Available at: <https://cloud.netapp.com/blog/data-governance-roles-policies-and-challenges-1> [Accessed 30 October 2021].

    -Rogin Joy, November of 2021