Indian organizations are increasingly moving from traditional enterprise reporting to augmented analytics tools that accelerate data preparation and data cleansing, said Gartner, Inc.

This change is set to positively impact the analytics and business intelligence (BI) software market in India in 2018. Gartner forecasts that analytics and BI software market revenue in India will reach US $ 304 million in 2018, an 18.1 percent increase year over year.

Gartner analysts are examining the key issues facing the data and analytics market in front of over 750 attendees at Gartner's annual Gartner Data & Analytics Summit 2018 that recently held in Mumbai.

"Indian organizations are shifting from traditional, tactical and tool-centric data and analytics projects to strategic, modern and architecture-centric data and analytics programs," said Ehtisham Zaidi, principal research analyst at Gartner. "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."

"We are witnessing 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," said Mr. Zaidi. "We are also seeing the emergence of data lakes and data hubs, as a new way to ingest and manage multi-structured data. However, unavailability of talent will continue to be a major inhibitor toward their adoption."

There is avid demand from Indian organizations to integrate and manage unstructured data, and some are also experimenting with data science on real-time streaming data. As a result, data management software market revenue in India is on pace to total US$950 million in 2018, a 13.2 percent increase year over year.

"In India, CIOs, chief data officers (CDOs), and data and analytics leaders must evolve their traditional approaches," said Mr. Zaidi. "They need to focus on business outcomes, explore algorithmic business, and most importantly build trust with the business and external partners. In particular, they need to start experimenting and adopting smart data discovery, augmented analytics, in-memory computing and data virtualization to stay ahead of the curve."