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Inviting feedback and inputs on Draft National Data Governance Framework Policy

Start Date :
May 27, 2022
Last Date :
Jun 18, 2022
23:45 PM IST (GMT +5.30 Hrs)
Submission Closed

India is accelerating towards an increasingly digitised and data-driven economy. With increasing digitization and engagement, the volume of data is also increasing exponentially, ...

India is accelerating towards an increasingly digitised and data-driven economy. With increasing digitization and engagement, the volume of data is also increasing exponentially, providing opportunities for better governance, service delivery and innovation in sectors critical for societal transformation.

Against this backdrop, the National Data Governance Framework Policy aims to enhance access, quality, and use of data, in line with the current and emerging technology needs of the decade.

The Ministry of Electronics and Information Technology invites all Indian citizens to bring their best ideas, inputs and suggestions to the table as we move ahead to become the hub for Data-driven innovation and decision making.

Please refer to the policy document: Draft National Data Governance Framework Policy (PDF 509 KB)

Share your inputs on the MyGov platform.
The inputs/suggestions may also be sent to
Ms Kavita Bhatia,
Scientist 'F' at the email kbhatia@gov.in and pmu.etech@meity.gov.in

The last date to submit your entries is 18th June 2022.

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Showing 788 Submission(s)
JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
Roles are essential to every data governance program. These days, software tools provide data governance templates for metadata management, data quality, master data management and data integration.
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JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
The following tools provide assistance with the implementation of a data governance program: Data Management (DAMA) Framework BARC 9-Field Matrix
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JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
Before the start of any data governance program, questions about the reasons for the project should always be answered in order to avoid unnecessary additional work. Similarly, existing processes should be evaluated to determine whether they can be adapted to the new requirements within the framework of a data governance program, instead of starting with the perhaps unnecessary development of new processes.
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JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
Typical project steps are: define goals and understand benefits; analyze current state and delta analysis; derive a roadmap; convince stakeholders and budget project; develop and plan the data governance program; implement the data governance program; monitor and control.
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JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
It is therefore recommended to start with a manageable or application-specific prototype project and to continue iteratively. In this way, the project remains manageable and experience can be used for more complex projects or to expand the data governance programs in the company.
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JYOTHIKA R H
JYOTHIKA R H 4 years 3 months ago
Data governance is not a big bang initiative and would not work in this fashion. Instead, global initiatives are highly complex and long-term projects. They therefore run the risk that participants might lose trust and interest over time.
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Sundar Krishnaiyer
Sundar Krishnaiyer 4 years 3 months ago
Digital Data Policy should be in Local Road Side vendors vegetable flower fruit markets fish sellers rural areas schools cinemas and all villages
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