India Analyzes Big: Data Science and Analytics Market in India

Analytics, data science and big data industry in India is currently estimated to be Rs 17,615 crore annually (FY18) in revenues (Dataquest estimates), growing at a healthy rate of 33.5% CAGR. Of the annual inflow to analytics industry, almost 11% can be attributed to advanced analytics, predictive modelling and data science. A sizeable 22% can be attributed to big data. Analytics, data science and big data industry in India is expected to grow seven times in the next seven years. It is estimated to become a Rs 1,30,000 crore industry in India by 2025.

The analytics and business intelligence (BI) software market revenue (the starting point really) in India is expected to reach Rs 1980 crore in 2018, an 18% year-on-year increase. Indian organizations are increasingly moving from traditional enterprise reporting to augmented analytics tools that accelerate data preparation and data cleansing.

Analytical Trends

The data analytics market in India is growing at a fast pace, with companies and startups offering analytics services and products catering to various industries. Different sectors have seen different penetration and adoption of analytics, and so is the revenue generation from these sectors.

Indian organizations are shifting from traditional, tactical and tool-centric data and analytics projects to strategic, modern and architecture-centric data and analytics programs. The ‘fast followers’ are even looking to make heavy investments in advanced analytics solutions driven by artificial intelligence and machine learning, to reduce the time to market and accuracy of analytics offerings. There is a rapid shift to the cloud and hybrid data management through focused data management offerings, including integration platform as a service (iPaaS) tools for cloud integration and data preparation tools for self-service integration. There is also the emergence of data lakes and data hubs, as a new way to ingest and manage multistructured data. However, unavailability of talent will continue to be a major inhibitor toward their adoption.

In India, CIOs, chief data officers (CDOs), and data and analytics leaders are increasingly focusing on business outcomes, exploring algorithmic business, and most importantly building trust with the business and external partners. In particular, they are experimenting and adopting smart data discovery, augmented analytics, in-memory computing and data virtualization to stay ahead of the curve.

Analyzing the Analytics

In terms of geographies served, almost 64% of analytics revenues in India come from analytics exports to USA. Indian analytics industry currently service almost $1.7 billion in revenue to USA firms. The analytics revenue from USA increased by 45% year-on-year in FY18. UK comes on a distant second at 9.6% of the revenues. Analytics revenue from these countries more than doubled from last year – Romania, UAE, Belgium, Poland, New Zealand & Spain. However, overall the revenues generated from these countries is quite minuscule when compared to USA. Indian domestic market serves as a significant market, with almost 4.7% of analytics revenues coming for Indian firms.

In terms of Sector type, BFSI continues to be the largest sector being served by analytics in India. Overall, 38% or $1 billion in revenues to analytics industry in India comes from BFSI. Marketing & advertising comes second at 24%, followed by e-commerce sector generating 15% of analytics revenues in India. In comparison to the last year, travel & hospitality saw the biggest jump in analytics revenues, from $34 millions to $54 millions, a jump of 61%. Pharma & healthcare saw a jump of almost 50% vis-à-vis last year. BFSI saw an increase of 31% vis-à-vis last year.

28% or $ 759 million in market size for analytics industry comes from Delhi and NCR region. This is closely followed by Bengaluru at 27%. The highest increase in year-on-year analytics revenues for an Indian city comes from Bengaluru, from $539 million in 2017 to $ 739 million this year; an increase of 37%. Mumbai ($483mn), Hyderabad ($236mn), Pune ($219mn), Chennai ($189mn) and Kolkata ($88mn) are the following cities with highest contribution to analytics.

The average work experience of analytics professionals in India is 7.9 years; up from 7.7 years from last year. Around 16,000 freshers were added to analytics workforce in India this year; up from 12,000 freshers last year. Fresher hiring has increased by 33%. Almost 40% analytics professionals in India have a work experience of less than five years, which is down from 42% last year. Analytics professionals with more than 10 years experience increased by more than 28,000.

Market Players:  Analytics Platforms and Data Science Players

So which are the top self-service analytical and BI platforms that help to converge to data-driven decision-making and improve their business acumen?

Tableau offers interactive data visualization products based on business intelligence. The software offers color, animation and cartography expertise to make data visualizations as easy as possible. Tableau connects a wide range of data sources, from established sources like Excel to recent additions like Amazon Aurora, Microsoft Azure SQL Data Warehouse and MapR Hadoop Hive Connectivity for Mac.

Qlik breaks its products according to how much support users require. Customers can choose from a self-service solution called Qlik Sense, the original guided analytics QlikView, a guided and analytics option called Qlik Analytics Platform or external data feeds through Qlik DataMarket.

SAS provides a graphical point and good user interface for non-technical users and more advanced options through the SAS language. Being in the era of automation, SAS has an analytical platform called Viya which can be updated and integrated with artificial intelligence. Viya is a huge platform of capabilities for all expertise levels, from Visual Analytics for reports and dashboards to event stream processing and complex model management.

Looker is a data exploration app that provides an intuitive approach to data. It gives a web-based interface that business users can utilize to tap into the expertise of their data analytics team. It can build and share reports and other functional groups can benefit from the questions they’re asking and the knowledge they’ve created.

Microsoft Power BI is a set of business analytical tools to deliver insights to the organization. It provides interactive visualizations and self-service BI capabilities where end users can create reports and dashboards by themselves. Power BI delivers data warehouse capabilities including data preparation, data discovery and an interactive dashboard. Power BI also has an additional service embedded on its Azure cloud platform.

Domo works by allowing any data source to be plugged into the platform out-of-the-box and enables users to prepare data for analysis without knowing how to code in SQL. It also helps to automate regular reports for the organization to collaborate on.

Teradata includes SQL with embedded analytics functions, a machine learning engine that provides pre-built analytic functions and a graph engine that discovers relationships between people, products and processes. “4D Analytics” is a process that combines geospatial data with time series data to support the constantly evolving time and location variables.

IBM Watson Analytics offers advanced data analysis and visualizations solutions in the cloud that guides through the analysis of the data. The prevalence of machine learning helps IBM for smart data discovery, natural language queries, automated predictive analytics and cognitive capabilities out of the box for your own data. IBM Watson Analytics for social media which tracks customer sentiment across millions of data and social media sources helps to deliver meaningful insights.

Salesforce Einstein is an artificial intelligence technology that had been developed for the Salesforce customer success platform. Einstein encapsulates all the machine learning capabilities in Salesforce product portfolio with automation and smarter insights. The product involves predictive analysis for forecasting data to help users find and explain insights from data and using automated analytics to find the most crucial insights.

SAP Analytics Cloud is an all-in-one cloud platform for business intelligence, planning and predictive analysis. It provides end-to-end BI platforms with dashboards along with machine learning built into key insights and integrated planning features. The product provides real-time analytics and collaboration tools in the cloud. It can be used on-premise or cloud data sources for past or live data from SAP or any other external sources.