BI and Artificial Intelligence go hand in hand

"The best is yet to come," the phrase marrying the bride and groom to many marriages also applies to BI and IA - the technologies that have joined forces to empower data-driven businesses. By helping to make business decisions and allow competition in the digital world for a few more anniversaries, the AI ​​must move beyond the boundaries of traditional BI and transform the tool that virtually delivers standardized reports into a solution for important business decision-making. based business.

The reason is that the BI and Analytics industries are undergoing a new wave of disruption because of Artificial Intelligence and Machine Learning, and this was highlighted in Gartner Data & Analytics Summits that took place in Sydney, Dallas and London. In the study presented last year, Augmented Analytics, or Augmented Analysis, as Gartner calls it, presented the future of data analysis, since in practice it is able to automate insights using machine learning and automatic generation of text. In the event, new and old companies have demonstrated that AI when influenced by such analyzes, such as the NLP, can recommend insights even in the form of text.

It is this natural processing language that allows users of BI and Analytics tools to create reports using voice commands, ask questions and even statements. The insights generated go beyond making 'pre-formatted' recommendations to users. It is possible to provide additional data, since such tools rely on the intelligence to answer important questions about the business and products, without requiring much of the user.

These narratives are automated and use natural language to provide a response based on data analysis. For example, for sales questioning, the BI system can add descriptive texts such as "This quarter revenue was X, a Y percent increase compared to the previous quarter. That way, next quarter revenue will be $ Z. "And there are already a large number of companies using tools that ask the machines to get the answers faster.

 

Jumping from the era of reports to that of insights

Even with so many impressive examples of these technologies, BI still has the old function of creating and reporting on enterprise, and the problem is lack of data analysis. Business users and executives do not have a lot of patience and want quick answers. One proof of this is that when they are talking on the phone they want to have access to strategic answers, almost immediately, such as: how many units you can request, how many professionals need to hire, expectation of revenue on certain products, and so on.

These questions are only an indication of how AI can address transformational changes in the BI world and analytics. By doing so, AI technology can make BI become truly intelligent.

In a recent survey called "IA unlocks BI business intelligence: break down BI gaps that enable IA," Forrester Research prescribes the way to use IA to improve BI. Boris Evelson, VP / Lead Analyst at Forrester, outlines six ways for companies to use AI techniques and tools to further leverage BI value, leverage data beyond storage, automate data preparation tasks, interact with computers more naturally, cogitously, democratize the use of advanced analytics, use machine learning to guide the discovery of insights and leverage all data - not just structured data for insights.

BI and Analytics solutions can deliver this ambitious list of well-positioned capabilities to meet the high expectations of business users, and definitely take the fame of BI as a tool for report generation only and turn it into something more predictive, capable up to 'prescribe' the future. Rather than offering analysis tools to generate reports, AI-enhanced analytics and BI platforms will enable executives to ask questions using the everyday business language, and receive recommendations for possible actions.

 

BI needs AI

In most companies, data access is a fact. 72% of the global data and analytics market say that you need to access the data for insight quickly. According to the 2017 Global Business Data and Analytics study.

However, even the most up-to-date BI tool that can make data more accessible still needs an expert on the subject to find the right model, ask the right question and interpret the results correctly in order to achieve tangible business results. The Global Business Survey survey states that most data and analytics decision makers are 52% of the business side and 63% of the technology and that they plan to hire people with advanced data skills to support companies in data-driven initiatives . But even with these data experts the challenge of navigating and interpreting data is already in place.

Forrester points out that accessing the data is not enough. It still takes the skills of experts to choose the right data and ask questions, and AI has an important role in identifying the right data and coming up with results relevant to all business stakeholders. This approach reduces the entry barrier to BI by enabling you to reach data-rich analysts and support a broader business audience.

There is no doubt, therefore, that AI-enhanced "intelligent analytics", which uses the data network together and allows insigths for users to be fast, is the next wave of disruption in the business intelligence industry. For business users, this trajectory of innovation is broad, and one proof of this is that, in fact, the best is yet to come.

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