With pure data analytics (DA) companies mushrooming rapidly over the last couple of years in India, a career in this line naturally becomes a choice for fresh engineering graduates. However, there is a burning issue as far as a career in the field of data analytics s concerned; and this problem has everything to do with lack of proper awareness with respect to multiple things including the skill-sets required to take up jobs in this sector.
Now, in a bid to guide fresh engineers towards the right data analytics career, we consulted multiple data analytics experts from even across renowned companies, to throw more light on the skill-sets required to land that dream DA job in India and the scope this sector offers.
Data Analytics is ever expanding in India
Experts advise engineers to opt for analytics due to the continuous growth and expansion that this sector is continuing to witness. The key reason for this trend has been the big data push which has seemingly been lapped up by all the major Analytics companies even across the world.
“The scope in the field of data analytics is ever expanding and is helping it become mainstream as companies of all sizes and analytics skill levels get into the big data game,” states Aman Yusuf – senior manager for global reporting and analytics at element14.
Aman also adds that companies are now coming up with decisions that are deemed ‘profitable’ only via efficient data analytics techniques by using big data in tandem.
As far as the Indian geography is concerned, Aman along with other experts believe that with the wide talent pool available here, along with its success in information technology (IT) adaption coupled with strong entrepreneurship skills and English language skills have put the country ahead of competition such as Eastern Europe and China with respect to the analytics domain.
Aman also believes that the current trends are increasingly positive for India due to big names outsourcing analytical operations/requirements to the country.
“India is extremely famous among the universal market which gives seaward administrations to a few companies in business analytics making them one of the countries that has a great data analytics future,” states Bastin Robin who is a chief data scientist at Bengaluru-based Hash Research Labs.
“Time and again, we have seen industry leaders, experts, and recruiters calling out the need for data science and analytics teams and how a skilled workforce is missing for them to truly make full use of the available data,” states Gaurav Vohra, co-founder and chief-executive officer, Jigsaw Academy that is today considered as a frontrunner in data analytics.
“The demand is high and supply is low, making for a classic case. This demand is going to surge in the next 5 years, and now is the time to skill up and stay ahead of the curve,” adds Gaurav.
I am in for DA what are my pre-requisites?
With experts opining that this is the right time to focus on a career in data analytics and big data related aspects, check out below some of the key skill sets that stand to give you an edge in data analytics:
- Statistical Knowledge
- You should be well versed with popular analytics tools viz. SAS, R programming, Python, Mathlab, and Structured Query Language (SQL)
- Theoretical domain knowledge of data analytics
- Data representation skills
- Data visualisation skills
- Storytelling skills
- Microsoft Excel expertise
At this point in time, it is worth remembering that data analytics is more than just simple number crunching. You should be able to apply the above skills such that informed business results become the order of the day.
You can become a data analyst right from the comfort of your home
Aman Yusuf (of element14) was also kind enough to offer insights on the easily available sources and reference materials that could serve as potential tools in your mission to become a data analyst. Check these out:
Books for reference:
- Lean Analytics — by Croll & Yoskovitz
2. Business value in the ocean of data — by Fajszi, Cser & Fehér
3. Naked Statistics — Charles Wheelan
4. Doing Data Science — Schutt and O’Neil
5. Data Science at the Command Line — Janssens
6. Python for Data Analysis — McKinney
7. I heart logs — Jay Kreps.
8. Naked Statistics: Stripping the Dread from the Data
Coding & Command Line:
Check out https://www.codecademy.com/learn/learn-the-command-line which is a free resource; can be used to learn coding.
Python is very popular in Machine Learning, predictive analytics and text-mining. Some of the greatest Big Data languages (like Spark) have their own Python layers as well.
Free course: https://www.codecademy.com/learn/python
Free book: https://learnpythonthehardway.org/book/
SQL is like Excel on steroids, but without the graphic interface.
Free course: http://www.sqlcourse2.com/intro2.html
Free course: https://www.codecademy.com/learn/learn-sql
In case you prefer to practically code, check out https://www.hackerrank.com/