Global revenue in the business intelligence (BI) and analytics market is forecast to reach $16,9-billion in 2016, an increase of 5,2% from 2015, according to the latest forecast from Gartner.
According to Gartner, the BI and analytics market is in the final stages of a multiyear shift from IT-led, system-of-record reporting to business-led, self-service analytics. As a result, the modern business intelligence and analytics (BI&A) platform has emerged to meet new organisational requirements for accessibility, agility and deeper analytical insight.
“The shift to the modern BI and analytics platform has now reached a tipping point,” says Ian Bertram, managing vice-president at Gartner. “Organizations must transition to easy-to-use, fast and agile modern BI platforms to create business value from deeper insights into diverse data sources.”
Gartner says that, as analytics has become increasingly strategic to most businesses and central to most business roles, every business is an analytics business, every business process is an analytics process and every person is an analytics user.
“It is no longer possible for chief marketing officers (CMOs) to be experts only in branding and ad placement,” says Bertram. “They must also be customer analytics experts. The same is true for the chief HR, supply chain and financial roles in most industries.”
To meet the time-to-insight demanded by today’s competitive business environment, many organisations want to democratise analytics capabilities via self-service.
The most significant difference between a modern BI and analytics platform and a traditional, IT-centric reporting and analysis platform is the amount of upfront modelling required, as well as the skills needed, to build analytics content (see Table 1). Creating analytics content via IT-centric reporting platforms starts with IT consolidating and modelling data in advance. By contrast, a modern BI&A platform supports IT-enabled development of analytics content.
“To get the full benefit of modern BI and analytics platforms, leaders must rethink most aspects of their current IT-centric, centralized analytics deployments, including technology, roles and responsibilities, organizational models, governance processes and leadership,” Bertram says.
