Modern Business Intelligence Platforms Enable Citizen Analysts

Top analytics and business intelligence platforms have been making it easier for end users to get self-service insights. The next step in their evolution is augmented analytics, according to market research firm Gartner.

Jessica Davis, Senior Editor

March 21, 2018

3 Min Read
<p>(Image: ismagilov/iStockphoto)</p>

Does your IT organization still keep tight control over access to the company's business intelligence tools, or are more of your end users across the organization gaining insight because those BI tools have been become part of the tools they already use every day? Increasingly, companies are moving to the second option.

More enterprise organizations are looking to spread the value of business intelligence insights to all their users -- not just data professionals or data scientists -- and that's driven a change in the BI tools themselves. According to market research firm Gartner, "modern" BI tools spread easy-to-use analytics with visual data discovery capabilities to users across the organization.

The change is part of what drove Gartner to redesign in 2016 how it evaluates BI and analytics platforms and vendors.

"The multiyear transition to modern agile and business-led analytics is now mainstream, with double-digit growth; meanwhile, spending for traditional BI has been declining since 2015," Gartner wrote in its 2018 Magic Quadrant report for Analytics and BI Platforms. (You can download a copy of the report from one of the three companies in the Leaders quadrant this year: Microsoft, Tableau, and Qlik.)

So if these new modern BI platforms are now mainstream then what is next? Gartner says that something called "augmented analytics," will define the next big change and improvement to enterprise business intelligence platforms going forward.

It was among the trends and predictions that Cindi Howson, Gartner BI expert, shared during a session at the Gartner Data and Analytics Summit in Texas this month.

Howson said that by 2020 augmented analytics will be a dominant driver of new purchase of business intelligence, analytics, and data science and machine learning platforms, and of embedded analytics. She describes augmented analytics as "a paradigm that includes natural language query and narration, augmented data preparation, automated advanced analytics, and visual-based data discovery capabilities."

Augmented analytics continues the evolution that began with visual analytics, and continued with more self-service analytics and BI -- two changes that have made insights more accessible to the masses within the enterprise. Howson said that trend will continue.

Gartner has created a series of strategic planning assumptions that point to significant changes and improvements to analytics and BI platforms in the next two years, making them even easier for end users.

Some of them include the following:

  • By 2020, the number of users of modern business intelligence and analytics platforms that are differentiated by augmented data discovery capabilities will grow and twice the rate and deliver twice the business value of those that are not.

  • By 2020, natural-language generation and artificial intelligence will be a standard feature of 90% of modern business intelligence platforms.

  • By 2020, 50% of analytics queries will be generated via search, natural language processing, or voice, or be automatically generated.

  • Finally, through 2020, the number of citizen data scientists will grow five times faster than the number of expert data scientists.

That's good news for organizations that have been struggling with hiring highly paid data scientists or considering adding these professionals to the team.

Another big plus for enterprise organizations is that these platforms are experiencing downward pricing pressures for their analytics and BI platform.

All these factors will make the BI platform of the future more affordable, easier to use -- two things that should also make it easier to justify to those who approve the business budgets.

About the Author(s)

Jessica Davis

Senior Editor

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: @jessicadavis.

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