Data Analytics and E-Learning Opportunities in Pune

If you are a devout follower of tech news, you must be aware of several reports published by influential think tanks, such as Deloitte, Harvard, McKinsey and IBM predicting that the demand for data analysts would surpass the supply. Jobs in the field of Big Data and data science is evolving each day and in the past 2-3 years this sector witnessed astonishing growth and is set to intensify further.  

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How Much Do Big Data Professionals in India Earn?

India is not lacking behind when it comes to the prevalence of professionals properly trained in Big Data and analytics and there is room for more. If you are thinking of choosing this field as your career option, this is a must view presentation as we bring to you the pay packages of Big Data professionals working in India.

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Should you seek a SAS training institute or look to Python?

Probably the most talked about debate in the analytics industry has been the undeclared war of SAS vs. Python. Both these courses are mostly similar in features but still worthy competitors that put aspiring students in an unsolvable dilemma, “Should I go for SAS training institute or Python training?”; if not met with the right direction. So, in order to offer students with a clear direction here is a blog comparing both these courses, discussing the advantages and disadvantages associated with both them.

Why this review and comparison is necessary?

It is evident that a lot has already been said about this topic, but there is still ample reason to support the need behind this debate.

1. The analytics industry is a dynamic one with things changing and updating every day, a comparison that stood valid even a year ago could be outdated right now.
2. All this while Python was mostly left out of such debate topics while priority was given to R and SAS only. Hence, this might be a good time to give Python the centre stage.
3. While taking global trends into account about these two languages, we will also provide India-specific information based on the domestic analytics industry. This is an entirely different genre at a completely new standard of evolution. 

A glimpse into the backgrounds of the two language ecosystems along with pros and cons:

SAS:

This language has been the undeniable leader in the industry of analytics this is so because, the program has a top-notch array of statistical functions on offer, in combination with good GUI (Enterprise Guide and Miner) and offers efficient technical support that further works as the icing on the cake. But on the downside, it does not always offer the latest technical features and can pose to be a very expensive option for many.

Cost: highly expensive commercial software, even difficult to afford for professionals.

Ease of learning: it is very easy to understand with the availability of PROC SQL, especially for those who already have skills in SQL.

Python:

This initially began its journey as an open-source program for scripting. But its usage has significantly grown over-time. Presently, it houses several libraries for e.g. numpy, matlotplib and scipy, and is equipped enough to take care of any statistical model one may want to do.

Cost: Python is an open-source program available to download for free. Hence, most students prefer this language. 

Ease of learning: while not as structured as SAS but still quite easy to learn and understand, with a few handy documentation and sharing features.

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