GIVING DATA ITS DUE

GIVING DATA ITS DUE 

#GS 03 Cyber Security

Context:

  • It has become cliche to say that “data is the new oil.” The ability to produce data is currently greatly increasing around the planet.
  • Servers gather data on every area of society every minute, including consumer and corporate behaviour as well as the execution of government programmes.
  • In many ways, the Indian government is not only spearheading this effort but also setting the groundwork for additional efforts by supporting the growth of a strong data ecosystem.
The following benefits are produced by the data ecosystem when used properly:
  • Data must first be gathered and stored in order to be effectively utilised.
  • A solid data ecosystem needs a strategy and a collection of tools for handling, managing, and utilising data. The data environment clearly has to be improved, especially with the Indian government’s size.

About NDAP:

  • To meet this need, the National Data and Analytics Platform, a transformational open data platform developed by the NITI Aayog in partnership with state and federal organisations, was formed in May 2022. (NDAP).
  • The NDAP provides machine-readable versions of basic datasets from federal and state government organisations along with a user-friendly interface and powerful analytics.
  • The platform combines diverse datasets from across the government using cutting-edge techniques, enabling the usage of multiple types of data at once.
  • The NDAP’s target audience consists of decision-makers, government employees, academics and researchers, journalists, inventors, and civil society organisations. As NDAP is a platform with this kind of reach and vision, it has the potential to become the norm.

Positive outcomes from NDAP anticipated:

  • It is especially made to deal with the problems that are now limiting the use of public data.
  • Prior to the NDAP design process, a thorough inquiry was conducted with a variety of data consumers to comprehend the demand for government data, the feasibility of doing so, and the difficulties associated with doing so.
  • Public data is frequently kept in formats that are difficult to analyse and on irrational platforms. Users cannot compare data from different departments or data obtained over time since data from diverse sources do not communicate with one another.
  • Not least of all, due to slow updating procedures and inconsistently high-quality data. Extensive user testing is a component of the NDAP design process at every level to address these concerns and ensure the platform does so successfully.

How could data be applied?

  • Consider a state employee who wishes to construct brand-new primary health centres (PHCs) in the state’s largest towns and cities where none already exist.
  • She must first find and combine three datasets from three different organisations in order to identify these communities. These datasets are the Population Census from the Registrar General of India, which prioritises villages based on their size, the Economic Census from the Ministry of Statistics and Programme Implementation, which produces a list of communities with private health facilities, and the Health Department’s MIS, which produces a list of communities with existing PHCs.
  • Despite the fact that all of these datasets are accessible to the general public, finding them and obtaining the pertinent state’s data requires effort and knowledge of three different portals. After that, her biggest problem will be effectively combining the data to create a single list of the major communities lacking health centres.
  • The decision-maker can obtain the information via NDAP because it is seamlessly merged from all three sources into a single dataset. She can then download the data and analyse it using her preferred methodology, or she can use the platform’s built-in analytics and visualisation features to better comprehend the data.
  • The public servant can work faster and make decisions based on more evidence. Better programme performance and governance will benefit state citizens as a result. Neither the data nor the technical tools that enable this improved scenario are novel; what makes NDAP revolutionary is its capacity to combine them on a platform that is specifically customised to the demands of its customers.

Conclusion:

  • The Indian government supports the creation and use of evidence-based policy. Yet, this requires active state cooperation, which is necessary to achieve.
  • NDAP is now a part of NITI Aayog’s State Support Mission. The creation of state-specific portals along the lines of NDAP not only ensures that all states are equal partners in this journey towards becoming leaders in data-driven policymaking, but also saves money and time.
  • The NDAP seeks to uphold the principles of cooperation everywhere in order to advance the cooperative federalism ethos.
  • Because NDAP is open access, everyone has the chance to support it by working to increase, update, and enhance the platform’s current datasets and capabilities, including states, ministries, and the Indian data community.
  • Aspiring public servants will also be able to employ data-driven decision-making from their first field position forward. By cooperating, we can turn NDAP into an open data platform that is vital to data-driven governance.

Source THE INDIAN EXPRESS

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