We live in a world of data. Everything that one does under sun is being noticed and recorded.
Have you ever observed this? You go to Flipkart, browse the site to buy a product, you see the top recommendations in Flipkart, then go to Amazon, look for the same product. However the top products in Flipkart and Amazon didn’t match your expectations.
Finally, in exhaustion, you log into Facebook to get updates on what’s happening in the world around. This time, all the advertisements, those small ones in the right corner of the page, would contain the products that you just browsed through or other products related to that category.
Ever wondered how this happens? A lot of these things happen at the click of the mouse (the epicenter of all analytics activity)
The system makes note of the different products you browse. It sees where you spend most of your time, analyses the buying pattern, finds out the exact item or category that you are looking for and displays advertisements related to that.
As you start using Facebook, these picture will ensure that they catch your attention and drive you back to the website. This concept of getting data from Flipkart and using it to create customer-specific advertisements is a simple example to demonstrate the power of analytics. There are so many things that happen around us that we don’t even realise.
Even the smallest piece of data is captured and used to influence decision making. A lot of accidents, frauds, manufacturing defects, etc. can be prevented with the proper handling of historical data.
That is the potential of analytics in today’s world.
With the advent of the internet and new technologies, a lot of data handling issues have been removed. Earlier there were two main problems which have been addressed now.
One, it was difficult to maintain records, as there did not exist much memory space.
Two, companies didn’t realise the importance of historical data, they didn’t know why they had to capture all the details.
Now though things like Big Data have opened the door to a world of opportunities. Voluminous data can be handled and analysed without much difficulty.
This field is blooming (and booming) because it predicts things and reduces the risk involved in decision making. It helps to forecast things with higher precision.
Analytics is not a new term, it has been in use for years now. Our grandfathers, and their grandfathers before them have all used their gut feel to take business decisions. This gut feel came from previous experiences.
Consider the simple example of a fruit seller who has been selling fruits in your area for years now. As time passes by, he will know who purchases frequently and what items that person buys. He will be able to add or remove fruit varieties to suit the needs of his customers. He comes to this conclusion in a few months as his product range is relatively low.
Now, extend the same to a business like Walmart which operates in different part of the world. The number of products that they handle is insane. Sales in California and sales in New York may not be the same. Products that sell well in an area close to schools may not sell the same way in a residential community. So, there is a need to store data based on a lot of variables.
If we are able to record the data about purchases for a year or two in all the Walmart stores across regions, we can easily find out the products which sell well in that particular area.
If 100 customers come to a shop per day, it is 3000 customers per month and 3, 60,000 customers per year. A retail shop will have close to 150 different products. Multi-speciality stores handle double or triple the amount of products. So the amount of data handled is huge.
A lot of data analysis goes into studying the customer behaviour pattern in a particular store and predicting what products to add and what to remove.
If you closely notice Coursera has recently added a course section called DATA SCIENCE. A lot of courses are being offered for free by some leading universities like MIT, Stanford, and John Hopkin’s University. Make the best use of these platforms, do some free courses to explore the growth and development in this field.
Begin with a basic statistics course as basic understanding of statistics is necessary for analytics. These websites also have a lot of courses on basic statistics. Then move on to the applications and case studies.
Here’s a quick list of online courses:
The next few years will be a high-growth period for analytics and Big Data. Internet of things is also a major driver for this trend.
The basic qualification needed to get into the analytics sector is to a have the relevant degree. However, having 12-24 months experience in a domain helps to absorb concepts better.
Business schools such as the IIMs and ISB run courses on Business Analytics. Work experience is a pre-requisite in these Institutions.
SP Jain has started their own business analytics program quite recently.
While all these programs have been 1 year part-time or 6 months full time programs, IIM Calcutta has started offering 2 year full time program in Business Analytics with a 6 months internship in the last semester.
The top colleges in India have already started responding to the trend of analytics. The trend is likely to continue. A lot of colleges will redesign their programs to cater to the needs of the industry. There is that much demand.
Spend an hour searching on Naukri or other top job search websites, you will definitely agree with me on this.
A combination of love for numbers, domain knowledge and willingness to learn technologies used in the industry is all it takes to start a career in analytics.
A number of companies are coming up nowadays in the Analytics sector. One of our Professors who handles Data Visualization often mentions there are a lot of openings for Data Visualization consultants in Australia. Countries will need more data analysts as most of the decisions will be driven by data in the days to come.
Almost all industries today need analysts to scale up their projects.
Let us see the top companies under different industries:
Analytics pay might be less when you start your career in this field, but once you get a year or two of good experience, your compensation package can get a spike.
My friend’s sister was working with one of the best data companies in India for 2 years as Data Scientist and when she quit her job for MS she was offered a 10 lakh package by one of the companies in Bangalore. Such is the demand for Data Scientists and Analysts in the market today.
Average starting salary package for someone who is new to this field (freshers) is 4.5 lakhs – 6 lakhs (minimum).
For someone with minimum of two years work experience, inspect the demand for analysts in your domain, you will be amazed to see the numbers.
For freshers who are right out of college! Breathe! Go easy! Though this industry requires fresh blood, it needs some business understanding as well.
Image source: Exalytics
Author Bio: Anusha Reddy is an Electrical Engineer currently pursuing her Post Graduate Certificate Program in Business Analytics.