Self-service analytics emerges as key driver for organizational performance
Tableau in partnership with IDC released a report on ‘How Culture and the Right Analytics Drive Success for Leading Organizations in Asia-Pacific’. The report highlights importance of the use of analytics, how to foster its use in organizations and importance of meeting the analytics needs of the business user to improve organizational performance.
The report is based on the findings of a survey of 207 respondents in IT and line-of-business roles, spread across India, Japan, Australia, and Singapore. The organizational benefits, both quantitative and qualitative, that self-service analytics provide to decision makers at various levels within the organisation are defining the next big trend in data analytics.
Craig Stires, Associate VP (Big Data, Analytics and Software), IDC Asia Pacific, said, “Of the countries studied in Asia/Pacific, Indian users are the most likely to feel their analytics needs are met. However, self-service analytics and mobile capabilities still hold the biggest gaps in user needs today. In India, users indicate higher frequency of usage of analytics tools, with 60% increase in daily and weekly usage over other countries studied. This is very important, as daily use of BI/analytics results more frequently in 50%+ improvement of business outcomes.”
Deepak Ghodke, Country Manager India, Tableau Software, added, “Instead of confining access to critical data to an exclusive group of data scientists, we’re seeing that self-service data analytics is now on the rise with more organizations embracing a culture of data-driven decision making. With Tableau, domain experts across lines-of-business are able to conduct their own analyses, ask the right questions and benefit from rapid-fire insights from their own data sources.”
The overall business analytics software market is forecast to grow in India at 9.6% YoY through 2019, reaching USD 583 million, compared to 6.8% across Asia-Pacific. Users in Asia-Pacific have cited shortcomings in ad hoc analysis, visual analysis, and mobile access to information as inhibitors to broader and more effective use of analytics.