Prarang Knowledge Webs
Bridging the Digital Divide – By City, By Language
Bridging the Digital Divide – By City, By Language
Prarang builds India’s District-level big data (768+ districts, 140+ parameters) using 42+ credible public sources and standardizes key Demographic, Socio-Economic, and Culture-Nature indicators. It applies an Indian Four-Step logic method — Pramana (evidence-based data), Anumana (estimation modelling), Upamana (District ranking), and Samana (national average benchmark) — to generate real, comparative district insights.
Explore via India–Physical to view aggregated State/UT metrics and drill down into ranked District insights, or navigate through India–Political to directly access a District’s highlights.
768 District Capitals – Discover beyond 28 States & 8 UTs.
Metrics – Socio-Economics contextualized by (a)Demo/Language/Web (b)Culture & Nature
A calculator to determine how far your Advertisement on conventional All-India TV/Radio/Internet actually reached in any specific town (4500+), based on Ad type ( Text, Audio, Video) & each town’s language-wise literacy. Multi-lingual diversity check included too.
Successful advertising campaigns in India require a deep understanding of regional nuances. Local language communication is the key to digital marketing in India. Prarang's India Advertising Planner offers a groundbreaking tool (using local language & literacy hyperlocal data) for 768+ City comparison and analytics, providing valuable insights to boost marketing strategies & even identify possible fake-Ids of various social-media. By analyzing factors like cultural preferences, consumer behavior, and regional trends, businesses can tune their advertising campaigns to resonate with specific hyperlocal target audiences in different cities (all district headquarters) across India.
With India comprising of 768+ Districts and Union Territories, each with several towns and villages, selecting the right entry points for market expansion is critical for businesses. Prarang's India Market Planner provides the necessary data and analytics to make informed decisions about entering specific districts and their respective District Head Quarters (DHQs). Instead of dealing with thousands of urban and rural markets or merely focusing on the 28 State capital metropolises, companies can focus on the most promising Districts ( bio- regional geographic areas with a clear & measure-able urban & rural governance structure) & their DHQs for their market entry.
India's incredible diversity presents unique opportunities and challenges for businesses. State-level comparisons do not reveal the diverse economic models of big India. The India Development Planner now helps uncover hidden patterns and differences between regions ( 768 Districts – mix of towns & villages) in the country. By analyzing various indicators like GDP, infrastructure development, education, healthcare, and social indicators across Indian districts, businesses can understand the level of development in different regions and tailor their strategies accordingly. This tool is invaluable for answering questions like, "How developed is one part of India compared to another?“ You can even customize your own – India Development Index – and generate unique insights.
India
Artificial Intelligence for Governance
India can be better managed using new A.I. technologies only if we build big data from reliable sources. At Prarang, we collect data of India at a "District" level. Using 42+ different sources of government ( eg. Census 2011) & some other public domain socio-economic, internet & culture/nature metrics , we have created our Prarang database for 768+ Districts of India on 140+ parameters each. Often government data is only available at 28 States & 8 Union Territories level.
Prarang does not do surveys to collect data. We mostly use Public sources of data - both government census, surveys, reports and private surveys whose results are available in news media & public websites. We follow a three-fold Indian logic ( Tarkashastra) method of information/data classification - We collect Pramana ( Evidence based i.e. Census, Reliable Surveys etc) data & then do Anumana ( Estimation modelling ) to Geo tag fill data in the residual Districts/DHQ (District HQ), to ensure data completion for "All India". We then do Upamana ( comparison) i.e. rank all districts/DHQs for a relative comparison. For each data field, the Samana ( Country Average) is calculated to again rank all districts/DHQs on Rank Above or Rank Below the Samana/Average. All our data sources, and our estimation modeling methods are transparently shared on each data field title , and can be accessed by clicking on the "i" icon.
On each of the Prarang Analytics pages of India's 768 District pages, we present a basic Artificial Intelligence ( Traditional A.I. not Generative A.I. ) based - District Performance "HIGHLIGHTS". Each performance parameter ( currently, just Socio-Economic data & not Culture/Nature metrics) of the respective District is ranked vis-a-vis all other 767 Districts of India & also ranked Above/Below India Average, on the same parameter.Based on these comparative rankings, each District's USP is highlighted on its Best & Worst parameters. Effectively, this has created an unbiased & automated - "Standard District Performance Report Card" - for all India. The role of the D.M. ( District Magistrate) & his team can particularly benefit from such standardized accountability.
Do note that each of the English language sentences in the District HIGHLIGHTS box on the Prarang District Analytics page, are A.I. generated - The first statement is a logic statement ( " Tarka" statement in Indian logic) & the second statement is an inference statement ( " Tatpurya" statement in Indian logic).
Please select any India geography by District name & note the - District Highlights - India