The analytics and data science scene in India has seen a spurt of growth over the past five years. There are a lot of factors shaping the analytics landscape today and it can be hard to keep a track on the frenetic pace of innovations. There is a clear need for insights on a range of topics such as jobs, salaries, skills and tools and techniques used today to stay relevant.
Analytics India Magazine has pioneered in presenting a wholesome view of the industry for over half a decade. To add to its authenticity, it partners with premier institutions and collaborates with industry experts to help the aspirants and veterans alike.
Here we list down a few studies conducted by AIM that will help you get a better idea of the data science ecosystem:
In this study done by AIM in collaboration with Great Learning, is aimed at listing down key tools and techniques that are famous in the industry.
As part of the survey, samples were collected, which included various sub-topics such as data visualisation tools, preferred operating systems and programming languages, among others. This study also considered the opinions from all those who practice data science — from professionals with less than two years of experience to CXOs — to get a thorough idea of the working environment in this growing field.
- The favourite language for data scientists in today’s era is Python, as almost 44% of the professionals use it the most
- 72% scientists used Logistic Regression most at work.
- Pandas emerged as a clear choice for most data scientists at almost 41%
- More than half the respondents, 51%, preferred to use Tableau as a dashboard or visualisation tool.
- Amazon Web Services is more popular in the community garnering more than 45% of the votes
- 27% respondents use GitHub to find open data
- Almost 69% of data scientists use Windows OS
- Almost 38% prefer using RStudio
- 52% of the users said they used Hadoop the most
AIM and INSOFE joined hands in conducting this study on how analytics is being adopted in companies at the domestic level such as private and public banks, industries such as steel, power, telecommunication and refineries.
- The overall adoption of analytics & data science at large Indian firms is around 64% That’s a healthy adoption rate given most of these large firms are into traditional businesses like energy and utilities
- The average tenure of analytics professionals at Indian firms is 3.4 years
- The median experience level of analytics professionals with Indian firms is 7.5 years
- Public sector banks, even though with low adoption have the highest analytics tenure among India firms, at almost 5 years
- Almost 94% of analytics functions are based out of just three cities – Mumbai, Bangalore & Delhi/NCR
The rationale behind this study is get insights on the salary trends in the fast evolving analytics industry in India. This study brings a cumulative picture f salary trends across company type, skills, analytics tools, cities, experience level, education level etc.
- The median analytics salary in India for the year 2017 is INR 12.7 Lakhs across all experience level and skill sets
- 37.6% of analytics professionals in India command a salary of less than 6 Lakhs. This is lower than 2017 (39%) & 2016 (42%)
- Mumbai continues to be the highest paymaster in analytics at almost 13.3 Lakhs per annum, followed by Bengaluru at 12.5 Lakhs
- At the entry level, almost 78% of analytics professionals are under the 0-6 Lakhs salary bracket. There is an indication that more entry-level (fresher) professionals entered the analytics workforce this year, which is a good indication towards the maturing of the industry.
- Telecom industry pays the highest median salaries to its analytics professionals at 18.6 Lakhs.
- R Programming skills are most in demand with the highest salaries for R professionals at a median of 14.4 Lakhs.
- Big data professionals and data mining professionals get up to 14 Lakhs & 11 Lakhs on the median.
- Analytics professionals with a PhD command the highest salaries at a median of 22.7 Lakhs per annum.
As for the entry level jobs in analytics, the industry witnessed an overall decline in their salary structure, whereas the salaries for mid-level experience have remained relatively stable compared to last year.
This study delves deeper into the type of educational institutions offering data and analytics programs; how the educational landscape is changing in response to the heightened demand for analytics skills and what needs to be done to fill the skill gap.
This survey revealed respondents seek a career-focused analytics education augmented by classroom setting that prepares them for job functions in the data analytics space.
- 87 percent of analytics courses from private training institutes are self-paced learning models.
- On average, analytics courses by private institutes have 105 hours of instructor contact hours.
- 56 percent of all long-term analytics/ data science programs by B-schools/ institutes in India are part-time courses.
- In terms of degree awarded, 45 percent of long-term programs provide a Certificate in analytics, 31 percent provide PG diploma and 24 percent bestow a Masters degree.
- The average course fee is Rs 27,300. For long-term programs, the average course fee is Rs 4.8 Lakhs.
Analytics India Magazine surveyed 61 analytics leaders in India, ranging from Chief Analytics Officer, head of Data Science, Director & VP’s of Analytics. This study is aimed at getting an overall idea about the sentiments within the data science industry in India.
AIM asked the leaders to rate on a scale of 1 to 10, if they are confident on analytics being a key focus area for organizations globally and the results are as follows:
- 62% leaders gave a perfect 10/10 score. This is much higher than 36%from 2017 and 47% from 2016
- Net Sentiment Score among analytics leaders in India is at a four year high of 80%. Last year score was at 51%
- 70% decision makers believe that ‘Unavailability of Analytics Talent’ is the major challenge that they face
- 72% analytics leaders plan to collaborate with external partners
Analytics leaders claimed that in 2018, 42% of the analytics work is in the area of Advanced/ predictive analytics/modelling.
These studies have gained popularity over the years for two reasons- the authenticity they bring to the table and key insights that help practitioners and analytics service providers understand the landscape and stay relevant in the ever-evolving data science community in India. It also supplements the visions of our policy maker’s to make India a digital hub. The studies and surveys set a new benchmark and add great value both at the individual level and also for key stakeholders to understand where we stand in our ambitious pursuit to gain global relevance as an innovation hub.