Indian organisations are incorporating a more algorithmic and data backed methodology into their operations, thanks to the keen awareness of data analogy and understanding that is streamlining business functionalities like never before. 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, creating a positive impact on the Indian analytics and the business intelligence software market. Additional data analysis will be facilitated by Gartner analysts at the Gartner Data & Analytics Summit 2018, taking place June 5-6 in Mumbai and June 14-15 in Tokyo.

"Indian organizations are shifting from traditional, tactical and toolcentric data and analytics projects to

strategic, modern and architecture centric data and analytics programs," states 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."

The demand is facing an all time high that can help Indian organisations easily integrate and manage unstructured data while dabbling with data science on the real time streaming data. Consequently, 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. The global scenario has already picked up pace, placing the baton in the hands of business in line leaders from IT leaders who can use the technology and their business insight to bring in more productivity, agility and efficiency into their global operations while staying in vogue of the industrial ideations.

"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."