Recently I started answering on Quora. It caught my attention that people pursue a lot of interest in the Analytics domain. Being a blogger, it is my utmost responsibility to cater to the educational needs of the masses, hence this blog will be related to basics of analytics and where to learn, some misconceptions around analytics and career scope. I have 3 years of experience in the Analytics industry, and I would leave this discretion to the readers to decide if they find my blog useful.

Data analytics is the new buzz in the market. As IT companies are laying off a lot of professionals, Analytics seems to be the next big spot. This article is dedicated to anyone who wishes to launch their career in this field and extends to college sophomores, graduates or even someone who wishes to switch.

1. What needs to be done to be a Data Analyst/Scientist: As you might be still in college, you might have very little knowledge about this position of a data analyst. I am not sure about other colleges but in my college, there was hardly any forum where we could discuss these things. We had one subject “Statistics” and that too we took because of grades. But after joining Anheuser-Busch Inbev and seeing a couple of students from other colleges my perception changed. A lot of colleges have already started taking this course seriously. I am giving reference of IITs, IIMs, and some top private colleges. So what are the basics:
   • Probability: What we were being taught in class 9, I guess, is the base of analytics. We can distribute analytics in 4 broad categories:
     • Descriptive analytics: Where we want to access what is happening
     • Intuitive analytics: If something is happening you will like to know the reason, so why it is happening
     • Predictive analytics: Based on the past you want to forecast for future so what will happen
     • Perspective analytics: Now you have a situation, so how will you optimize the resources means what you should or will do
   • So you can start studying basic of these 3 kinds of analytics in your college. I started with Ken Black’s book which starts from very basic (probability distribution) and covers few important things like Z test, Chi-square test, Time series, Regression etc.
   • When you join any company fresh out of college nobody will expect these techniques from you until you are from Stats or Economics background or lateral hire (MBA, M. Tech or Ph.D.). So don’t worry and just work on your aptitude, reasoning, Microsoft Excel (VBA), C/C++/Python (basic will work) and database.
   • Some useful sources you can refer to learn basic stuff:
     • Regression Analysis
     • Forecasting Methodologies
     • Time series analysis in R
     • Ken Black book
     • Analytics Vidhya
     • Coursera
2. Career growth in analytics: When I talk to my seniors they mention that 6-8 years back, there was hardly any role for data analytics in India or any boom, unlike today. People were afraid of taking this course as the main goal after graduation is a secured job. There were only colleges in India which used to teach statistics. But now you open any job portal websites and check yourself how many openings are there in the industry. This is a booming industry and every company wants to utilize their data to give some fruitful outcome. The pay scale, however, depends on your qualification, experience and the company itself.
3. Some misconceptions:
   • Python will digest R/SAS very soon: Every company has its own preferences. Most of the traditional company maintain their data more securely and they only trust SAS though it is paid software. Some companies which are new to analytics or doesn’t require big data platform prefer R. Python is the most sought after language as it is very powerful. But a company won’t reject you on the basis of the language known. You should just know C basic and RDBMS. So Python in near future won’t bite R or SAS.
   • Big data is too big to handle: As I wrote one answer on Quora, big data is not the beginning or end of data analytics. You can start your career without knowing these terms and slowly learn like I am doing.
   • Analytics is just IT work: No and never! IT people maintain data. They don’t know how to use it, how to get insights from the data or how valuable it is. They are just miners and dig rough gemstones but you make them precious by applying analytics techniques to find some insights. So be proud of what you do.
   • Every company doesn’t do analytics. You should understand the difference first. Few companies provide the same designation but most of the time you will end up doing same work i.e. reporting, or roll up the data to get revenues. So don’t stick to such profile. There is a vast sea to surf outside reporting work.

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Source: @kzawadz via twitter, MarketingDistillery.com

There can be a lot of things to discuss. I want to keep this blog open and please comment below your thoughts and questions if any.

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Deepesh Singh