After using a lot of R for analytics projects believing that it was the best language for Data Scientists, I recently had the chance to pick up Python. R does seem a bit cumbersome when dealing with interfaces to other languages or to the web such as oauth. That was my motivation, to use Python to get text from the web and later process it in R, which was, I felt the "best" tool to go about.

However, Python surprised me not only with it's web interfacing abilities, but also…

In this post, I've tried to capture some of the common aspects of working in the analytics industry. While we occasionally hear about India growing fast into this space, there are a lot of things happening in India that might transform this field further. While some of these aspects are specific to what I've observed in India, a lot of them are generic.

As in previous posts, I try to classify these aspects under different heads:

1. The "cost" reduction trap…

While everyone talks about Data Scientists and there is extensive discussion on who a Data Scientist is, I've experienced one factor being overlooked while creating an analytics project. Essentially, that the Data Scientist isn't a person... it is rather a team.

Now, I have been busy with Sensor Data analytics for the last few months. I might have missed reading up what some people have been talking about on this aspect. However, what I am writing here is more from specific experience…

I have been following trends in Data Science since long, more from a research perspective ~ Trying to analyze what technique fits in where and what are the new developments in new fields and the bunch of new tools that have been cluttering the market. 

However, I soon realized that every field had it's own modifications and techniques as well as jargon. I encountered Financial Analysts talking about Black-Scholes model as if it's something you learned in primary school. Having…

   Marketing analytics has been around for so long that people have now started talking about sub - areas such as CRM analytics, forecasting, marketing supply chain, perishable retail analytics and so on. However, before you discredit this to be another blog reiterating the importance of analytics, I would like to clarify that this is rather about the challenges an analytics company faces in marketing analytics solutions. 

   On the surface, selling analytics seems to be simple... who…