One tweet, one like, one comment is all that’s needed for you to make your social presence felt, but what happens when those millions around you do the same? Ever wondered how the Amazon recommendations are so fine-tuned to your liking and purchases? Or how the credit card companies are able to educate you of your own expenditure? How do you think this is possible? How do you think the science behind these functions? Well, the word is ANALYTICS and BIG DATA. It is nothing short of a magical tool that makes all of these remarkable feats achievable!
Analytics and Big Data is an interdisciplinary field about processes & systems that are used to extract knowledge or insights from both structured & unstructured data. This information that we are being bombarded with, is called ‘Big Data’.
Who are Analysts and Big Data Experts?
Big Data Analysts are the ones who fine-tune the statistical and mathematical models that are applied onto data. When somebody is applying their theoretical knowledge of statistics and algorithms to find the best way to solve a data science problem or to build a model to predict the number of credit card defaults next month, they are wearing the data scientist hat.
What do Analytics professionals do?
Analytics experts take a business problem and translate it to a data question, create predictive models to answer the question and story-tell about the findings. Statisticians that focus on implementing statistical approaches to data, and Data Managers who focus on running data science teams tend to fall in the Analyst role. These Big Data Scientists are the bridge between the programming and implementation of data science, the theory of data science, and the business implications of data.
Industry ( Demand Vs Supply – Global Context )
At present the divide between the demand & availability of Analysts is gaping wide.
- 2015 alone saw a 26% rise in demand of Data Analytics professionals (worldwide) & it is to reach a mark of 50% by 2019.
- According to McKinsey Global Institute survey – USA will face a shortage of around 1,90,000 Analytics experts & 1.5 million Big Data Analysts by 2018.
- TeamLease services predict 60% positions for analytics professionals to remain vacant in the USA.
Industry ( Demand Vs Supply – Indian Context )
In the Indian market, the scene is no different from the global stage, in fact, if anything, it’s even more happening. In fact, it has been proven that the demand is equal between Government agencies & Private establishments. And, the main reason behind this lays the fact that India is a country of ‘young population & organizations’ alike.
Currently, there are only 10, 000 to 15, 000 Data Analytics experts in India, which will definitely lead to a shortage of 2 lakh Data scientists in the ensuing years.- Srikanth Velamakanni, CEO – Fractal & Analytics Interest Group member.
‘Unlike large companies that pay 9.6 lakhs, Indian startups are willing to pay over 10.8 lakhs per annum to attract the best talent in the analytics industry.’*Source: Analytics & Big Data salary Report, 2016.
Types of Industries that use Analytics and Big Data
FINANCE | ENGERGY | TRAVEL | GOVERNMENT | INFORMATIOON TECHNLOGY | NGOs’ | SCHOOLS | COLLEGES | UNIVERSITIES | MEDIA HOUSES | AVIATION | SCIENCE | MEDICINE | PHARMACEUTICALS | HOSPITALITY | GAMING | RETAIL | BANKING | SOCIAL MEDIA | INSURANCE | INTERNET | HEALTHCARE | RESEARCH | STARTUP COMPANIES/ORGANIZATIONS | MOBILE | AD TECH INDUSTRIES | DIGITAL MARKETING INDUSTRIES and many more…
How does Analytics help the Industry
- Detect fraudulent behavior before it leeches out the organization.
- Determine consumer’s buying trends, thus helping in sales and promotions.
- Calculate risk-portfolios.
- Identification, image-recognition, statistics & logistics analysis.
- Analyze root-causes of failures and its effects, amongst others…
This in effect helps in ways of:-
- Time reduction.
- Cost reduction and better investment.
- Optimized offerings in terms of new products and/or services.
- Fool-proof decision-making.
- Effective management of resources, with minimum wastage.
- Match supply to demand, amongst others…
Who should study Analytics and Big data
Some of the most noted & desired qualities of a successful Big Data Analyst would be:-
- A strong mathematical mind-set.
- Ability to engage in abstract thinking.
- Vision & observation skills that help you look beyond the obvious.
- Solid scientific thinking and credentials to back the same.
- Ability to adapt, evolve & constantly reinvent to meet the growing challenges.
- Insatiable curiosity.
- Perseverance & self-motivation.
- Out-of-the-box thinking.
- Good communication and/or explanatory skills.
Remuneration and Benefits
According to Analytics India Report: (Pay scale)
- Analytics at entry level – 4 to 10 lakhs per annum.
- Professional level (3-6 years experience) – 10 to 20 lakhs per annum.
- Professional level (6-10 years experience) – 15 to 30 lakhs per annum.
- Extensive experience of 10-15 years – More than 1 Cr. Annual package.
Role and Designations
People aspiring to be a part of Analytics and Big Data industry they have various roles to fit into. They can become Statistical Analyst, Data Manager, Data Architect, Data Scientist, Lead Analyst, Big Data Analyst etc.
Analytics and Big Data is a Niche segment having overwhelming career opportunities. One has to realize his potential and go for it.