Based on district data from NITI Aayog, can we build a dash board for comparing districts on various parameters and find sister districts?
This team presented their visualization that they had created to analyze District Level Quality of Life Data. They created visualizations to compare districts on key sectors of development like health, education, water and electricity. Combining this information, they wished to rank different districts on the quality of life. These visualizations could be useful to NGOs, activists, district and state administration to find the deficiencies in key development areas and work towards filling the necessary gaps.
The 3 people team from ilabs helps officials prioritize the bins and help for a faster and more efficient waste disposal from public roads also coded an algorithm which would help garbage collection vans take the shortest route and cover a maximum number of garbage bins on the way, thus, saving time and fuel.
Niti Aayog has public data for districts of all states regarding health, education & utilities. There is a need to analyze this data from following aspects
- Review visually how districts are doing on various criteria
- Visually Compare districts on multiple factors and check details
- Show multiple factors together to understand correlation between the factors.
- Rank the districts at individual factors as well as across the factors in each of the areas by applying weighted ranking process.
- Top N & Bottom N analysis by one or more factors across districts.
- District Administration ( Collector, JC etc)
- Central Government leadership
- Public Representatives ( MPs, MLAs )
- General public awareness
- Include financial data to analyze correlation in social investment and performance.
- Trending analysis over time ( for e.g YoY, QoQ ) for quantitative analysis of progress in effectiveness of policy implementation and social projects.
- overlaying policy timing on data will help doing impact analysis to drive continuous change.
- Include geographical data to do thematic analysis