More and more organizations today are turning to predictive analytics to gain a competitive advantage. Besides business, the analytics wave is embraced by government agencies and non-profit organizations as well, for public welfare and social well-being purposes. Big data analytics is serving a number of critical humanitarian needs, whether it’s helping fight cancer, preventing child abuse or saving endangered species.
Being the world’s favourite destination for IT outsourcing, India is today among the top 10 destinations for analytics as well. India’s analytics exports to major economies such as the United States (US), the United Kingdom and Australia are also growing significantly.
The revenue of India’s analytics and business intelligence (BI) software market will reach $304 million in 2018, an 18.1 percent increase over the past year, according to a Gartner forecast. By 2025, analytics, data science and big data in India is expected to become a 20-billion dollar industry.
The growth in this market is due to more and more Indian organizations moving from traditional enterprise reporting to augmented analytics tools that accelerate data preparation and data cleansing, said Gartner.
Generally, three types of analytics solutions are available in the market today: descriptive, predictive and prescriptive. Descriptive tells you what happened. Predictive tells you what will happen. And prescriptive analytics tells you what actions you need to take. While businesses are using all three types of analytics these days, it is machine-assisted predictive analytics, where customers see the most value in.
BFSI sector continues to be the largest buyer for analytics in India, followed by Marketing and Advertising, and e-commerce, retail & CPG, and has been rising in the Telecom, Pharma & Healthcare and Travel & Hospitality as well.
Some of the key players in the Big Data, BI and analytics market are IBM, Microsoft, Oracle, SAP, SAS, Tableau, Teradata, and Qlik amongst others.
SAS, which is a leading player in the analytics market said it will continue to focus on five areas of growth- Advanced Analytics, Data Management, Risk Management, Customer Intelligence, and Fraud Intelligence. Noshin Kagalwalla, MD, SAS India said, “Working with the government and analytically mature organizations to adapt to and embrace AI and Machine learning as part of their ecosystem will be a top priority for us. To this end, we see that a number of such organizations have already embarked on small-scale experiments to embed greater smartness in their systems in the areas of Chat Bots, Fraud detection, and so on. Some of these mature organizations have also set up smaller CoEs / labs to initiate work on pilot projects for smaller case studies before scaling up. Shifts in fraud patterns that require more sophisticated detection methods, like machine learning, has led to an over 50 per cent growth for us in the fraud and security solutions space. Modernization of anti-money laundering programs and a strong need from government agencies also contributed to this growth. Recent advances in IoT, machine learning (ML) and deep learning techniques will only accelerate the change in the dynamics of industries making this another top priority for us.”
Oracle, another key player in this segment has seen its Big Data and Analytics business growing at a healthy pace, with increased demand from customers hailing from several data-intensive industries like BFSI, Retail and Hospitality. Kiran Pradhan, Head – Business Intelligence and Analytics, Oracle India said, “On the technology front, Oracle is bringing AI into the product mix with the goal of helping customers make their analytics more effective and bring it into the hands of new users. Also, we believe that the future of IT is going to be the autonomous cloud. The autonomous cloud suite – helps businesses to eliminate key tasks and enable organizations to lower cost, reduce risk, accelerate innovation, and get predictive insights. We also recently announced the availability of Oracle Autonomous Analytics Cloud solution, which breaks down barriers between people, places, data and systems, fundamentally changing the way people analyze, understand, and act on information.
Sunil Jose, Senior Area Vice President and Country Leader, Salesforce India, said, “By 2025, analytics, data science and big data in India is expected to become a 20-billion dollar industry. The growth in this market is due to more and more Indian organisations moving from traditional enterprise reporting to augmented analytics tools that accelerate data preparation and data cleansing. There is no doubt that there has been a tremendous increase in the data at the individual and organizational level, increasing the need for tools that can analyse the data in real time. However, it’s the shift from traditional, tactical and tool-centric data and analytics projects to more strategic, modern and architecture-driven programs that are driving large-scale transformation in India. Salesforce Einstein helps you focus on what matters most, the customer. Einstein learns from all the data you have to deliver predictions and recommendations based on your unique business processes. Pair that with automation and you have the insights and time to truly connect with your customers.”
As organizations will look for more real-time insights in the days to come, it will require a quick processing of data as well. The increased computing power has already enabled computers to ingest more data and run bigger models with better algorithms. This, in turn, means machines can learn from patterns and anomalies they find in data on their own to deliver more accurate results – even on a large scale. Augmented analytics solution will not only help in better decisions, and more accurate business predictions but will impact the ROI and TCO positively with measurable analysis of product and service offerings, pricing, financials, production and other aspects of the business. Hence, solution providers will increasingly turn to AI and ML technologies to extract insights from the data faster.
But there’s a flipside also to this growing data phenomenon. Data is growing rapidly these days. Apart from traditional data sources, a large volume of data is also getting generated from social, mobile, and IoT today- A data deluge that makes it difficult for organizations to aggregate, visualize and analyze information efficiently. Hence, it’s very important for organizations to learn to select the right amount of data that not only saves money but also gives required, valued insights.