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NITI Aayog, the apex public policy think tank of the Government of India, recently launched the National Data & Analytics Platform (NDAP) for open public use. The platform aims to democratise access to public government data by making data accessible, interoperable, interactive, and available on a user-friendly platform.
For those who wonder why open data is so important, the short answer is that it speeds up innovation, minimises biases, improves data quality, and minimises data gathering costs. Open access provides interoperability required to solve complicated problems and to enable multiple organisations to find new approaches to better existing systems and develop innovative products and services.
To that end, the platform provides standardised datasets from India's huge administrative data ecosystem. NDAP makes it simple for users to search, merge, view, and download datasets. Here, we have curated the top four most viewed datasets from NDAP.
The Primary Census Abstract from the Ministry of Home Affairs provides basic information on the area, count of households, population by age, gender, caste, level of education and types of workers. Further, it provides information on main workers and marginal workers classified by the four broad industrial categories, namely,
Look at the data on SC population across states visualised in the form of a column chart.
Source: NDAP
Significance: From literacy rate to work participation rate, sex ratio, and reasons for migration to occupation - the whole depository of datasets is a gold mine for policymakers to better government services and move towards the idea of "Less government, more governance." Moreover, the data on languages spoken presents a ripe pitch for multiple NLP use cases.
Find the data here.
This dataset from the Ministry of Finance reports the statewide coverage, claims paid and scholarship disbursement under Aam Aadmi Beema Yojana. Aam Aadmi Beema Yojana (AABY) is a social security insurance scheme which extends life and disability insurance cover to persons between the age of 18 years to 59 years, living below and marginally above the poverty line under identified vocational or occupational groups. The scheme is implemented through the Life Insurance Corporation of India (LIC).
Significance: The data on the number of people availing of banking services across states, districts, to village levels can be of great use for the BFSI sector to roll out suitable financial products.
Find the data here.
The datasets of transactions are available in the Digital India programme. It is a flagship programme of the Government of India with a vision to transform India into a digitally empowered society and knowledge economy. Digital India promotes cashless transactions and converts India into a less-cash society. Digital India consists of three core components: the development of secure and stable digital infrastructure, delivering government services digitally, and universal digital literacy. It is centred on three key areas:
Take a look at the sum of BHIM transactions by year, visualised in the form of a pie chart.
Source: NDAP
Significance: While the study is preliminary, it clearly shows that transactional data might be a valuable supplement to the more typical demand- and supply-side data sources used to track digital payment uptake and usage. Additional phases of study can include time or day of the week of customer adoption, as well as consumer usage journeys across time, especially for younger, first-time account holders.
Find the data here.
Ministry of Health and Family Welfare is providing data on key indicators of NFHS-5 at the state level. The National Family Health Survey (NFHS) provides information on population, health, and other many important indicators. NFHS-5 (2019-20) is the fifth survey, while NFHS-4 (2015-16) is the fourth in the NFHS series. The data thus covered will provide information on issues including pre-school attendance, disability insurance coverage, ownership of physical and economic assets by women, antenatal care and other health indices. Take a look at a column chart visualisation.
Source: NDAP
Significance: The collected data on fertility, maternal and child health, family planning, nutrition, and many more, will provide an overview so that programme managers, policymakers, and researchers are better able to use the data to make evidence-based decisions.
Find the data here.