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Understanding Data Governance

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  • Last Updated : 06 Sep, 2021
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Data Governance :

Data governance is an act that takes the action according to data provided using its own method. Data governance refers to a complete set of processes and policies and people as well for ensuring effective data management. It’s a term using on both macro and micro levels as data governance is required from lower-level activities to higher-level activities as each activity works with some data. It’s very efficient and also enables an organization to achieve any specific goals. Effective data governance provides strong strategies to the organization and also it establishes the processes and responsible which ensures the quality and all security of data across the organization. Some data governance practices start with small creating pictures with big scenarios in mind. Data governance is not data management as data governance is a core component of data management.

Benefits of Data governance : 

  • Basic understanding of data – 
    Data governance provides an overall view and provides common terminology and helps in retaining the flexibility of the business.
  • Improves data quality – 
    Complete and Correct data helps in achieving something perfectly. Data governance makes it easy as the plan created with data governance results in data correctness, completeness, and consistency.
  • Data Map – 
    Data governance provides an advanced ability to understand location data-related entities, which helps in data integration.
  • Consistent compliance – 
    Data governance provides a platform for fulfilling the demands of regulations by the government.

Building data governance : 

If the integrity is not managed then it’s totally worthless so it’s important some principal should be followed that will ensure data remains high-quality and its compliance throughout the lifecycle. Here are some listed principles –  

  • Coverage – 
    The volume and completeness of data are kept in view of and level of unique identities.
  • Accuracy – 
    It’s important to merge data fields from multiple sources into one centralized system.
  • Freshness – 
    The data records should be fresh as possible. That monitors the system continuously to confirm the last update and ensures contacts and keeps updated.
  • Flows –
    Marketing campaigns and the company’s sales lead data flows should remain in sync and Tracks errors via the lineage of data across sources, transformation, and dependencies.
  • Labels and rules –
    It helps in standardize organization and visualizing tags and unidentified data models. And nominate data authorities to be the source of part across connected systems.

Main characteristics of data governance :

  • Administers the public policy and affairs of data.
  • Exercises the sovereign authority of data and influences the database
  • Controls the speed or magnitude of data.
  • Regulates data
  • Controls the actions of data and their behavior
  • Restrains the data
  • Manages political authority over data

Goals of data governance :  

  • Minimizes risks factors
  • Establishes internal rules of data
  • Implementation compliance requirements
  • Improves internal and external communication
  • Increases the value of data
  • Facilitates the administration
  • Optimizes cost

Data governance roles :

  • Steering committee – 
    It includes managing, protecting, and ensuring the integrity and usefulness of organization data. It designates data stewards and supports planning and governance to meet the data requirement and usages.
  • Data owner – 
    Mainly handled by senior managers in the organizations who are responsible for specifying the organization’s requirements on data and on data quality. Responsible for data creation and maintenance and also accountable for the data definition in specific areas of responsibility which differs according to the role and data requirement.
  • Data steward –
    A functional end-user in an operational area with responsibility for a subset of data. So, we can say data expert in a particular operational area. Implements data policies in an operational area and monitors the data quality as well.

Finally, good governance requires balance and adjustment. If done properly it fuels innovation without compromising security which automatically helps in the betterment of the process. Ultimately, it’s all about the process, people, and technology. A successful program results in a clear understanding of where data comes from its owner.  Together this process will provide data that depends on and strategic decisions and drive forward organization.

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