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Designing Data Systems for Skilling India

If you haven’t already, check out the latest IiT article, “Designing Data Systems for Skilling India.” Stefan Bender, Jörg Heining, and Kaushik Krishnan show some lessons from Germany on how India can collect better data on employment, wages, and the labor market. They argue that collecting this data need not be costly or time-consuming since much of it is already being collected by various departments.

“India’s unemployment rate currently sits at 9 percent. Yet, one in three citizens with at least a bachelor’s degree is out of work. Its working age population,is projected to rise from over 750 million today to almost a billion by 2020. At the same time, agricultural employment is in decline, accounting for less than 50 percent of total employment for the first time in Indian history. These market pressures are pushing the labor force towards higher skilled occupations. Yet, even young, college-educated,Indians often lack the requisite skills to obtain these jobs.” Continue reading..

Read more of CASI’s India in Transition (IiT) bi-weekly publications on the CASI website.

Stefan Bender

Stefan Bender

Jorg Heining

Jorg Heining

Kaushik Krishnan

Kaushik Krishnan

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Following the 2014 Election through Data-Driven Blogs and Articles


The last few years have seen the introduction of data analysis for election coverage into the public sphere. In the US, from the Nate Silver phenomenon to the team of “quants” that helped Obama get re-elected in 2012, data and numbers have wormed their way into the public discourse. In India, a lively debate is taking place on the role of opinion polls in voter behavior, as well as the transparency in reporting the results of the polls.

More than ever before, people are asking:

1) What are the numbers saying?
2) How do I interpret these numbers?
3) What other information do I need to believe these numbers?

The run-up to the 2014 general election has seen the emergence of quite a few impressive data-driven blogs and articles analyzing Indian political data. We are active readers of each of these authors, and we encourage you to follow them as well.

Below is a list of what we are reading these days:

Amitabh Dubey [@dubeyamitabh] at — Original analysis from multiple sources often leads to new, insightful conclusions

Puram [@puram_politics] at — Sharp prose and wit in analyzing election data from a Madras perspective

Rukmini Shrinivasan [@rukmini_shrini] at — A seasoned data writer for the Hindu delivers her thoughts with a penchant for clearly explaining and interpreting the data

Karthik Shashidhar [@karthiks] at — Author at Mint and data scientist with particularly careful analysis of Elections Commission and polling data

Here are some slick sites that provide a nice way to visualize political data: — Provides analysis and nice visuals. See the maps on tainted MPs and rallies! — One of the most beautiful sites out there, provides fantastic interactive data visualization