5 Takeaways from This Year's Gartner Summit

We’re back in Palo Alto after another engaging week at Gartner BI & Analytics Summit in Grapevine, TX. Coming shortly after their release of this year’s radically different Magic Quadrant report, Gartner did a great job of continuing the conversation around why today’s BI leaders are operating in an entirely new world, and what we need to do to keep up.

Take the keynote, for example: Inspired by the work of Yale’s Donya Quick, Rita Sallam and Frank Buytendijk played two pieces of music for the audience, and we had to guess which was composed by Bach and which was generated by a computer algorithm. They pretty much had the entire audience fooled.

It's exciting stuff. But as a product builder or a BI buyer, it can be overwhelming to think about where to begin with so many new technologies, trends, and opportunities bubbling up in the market. Here are my top takeaways from the event that I’m bringing back to our discussions at ThoughtSpot:


1. The algorithmic business will be a reality sooner than we realize.

Gartner predicts that by 2018, more than 3 million workers globally will be supervised by a “robo-boss.” They also estimate that by 2020, 20% of all business content will be generated by algorithms, and smart machines will be a top five investment priority for more than 30% of CIOs. Bold predictions, right? Gartner has picked up on the increasing pervasiveness of AI and machine learning in our personal and professional lives.

In other words: Companies that want to stay ahead of the game should familiarize themselves with the leading AI/machine learning technologies and try out products that incorporate these features.


2. Modern BI needs to cater to widely different business needs.

More and more, companies are looking to consolidate their BI & analytics investments into products that can meet multiple use cases. This means that one product should be able to act as a data science lab (if I want to look the correlation between one variable and another, for example), as an analytics workbench (where I can go to run tests and get charts), and/or as an information portal (where I can simply log in and consume information) depending on who I am and what I’m trying to accomplish.

In other words: It’s not enough to offer a product that only benefits IT or one that only spits out pretty charts. The table stakes requirements for modern business intelligence platforms are much broader today than they were just a few years ago.


3. Search-based data discovery is officially mainstream.

By 2018, Gartner predicts that “smart, governed, Hadoop-based, search-based and visual-based data discovery will converge into a single set of next-generation data discovery capabilities as components of a modern business intelligence and analytics platform.” While we spent a lot of time explaining the term “search-driven analytics” last year, this year we spent more time diving into the benefits of the technology. People already know what it is, and they’re ready to learn exactly how it can help their business scale data-driven decision making. For example, our customer adoption anecdotes—like how hundreds of merchants at a Top 5 retailer run tens of thousands of queries per week on ThoughtSpot—resonated well with our booth visitors.

In other words: Search as the primary interface for analytics is gaining ground. Take the time to familiarize yourself with the leading vendors that Gartner calls out in their search-based data discovery category.


4. Self-service data preparation has got to be part of the package.

Many new BI products that have launched over the past few years fulfill one or more of the self-service data prep steps: data discovery and profiling, catalog and metadata, data structuring and modeling, data transformation, data curation, enrichment, and collaboration. This has allowed users to access not just structured data through IT, but also multi structured, open, purchased and cloud data as well, without the involvement of IT.

In other words: Everyone claims to offer “self-service” BI, but few can fully deliver on that promise.


5. Keep your eye on smart data discovery.

Smart data discovery, or the ability to automatically pull up key insights from data, is the next big thing to look for in a modern BI platform. This provides business users with the ability to pull in data from multiple sources and, with the click of a few buttons, analyze the data and present key charts and insights for the user to review. This could be followed by an exploratory phase in which the user can drill down further into any of the charts or metrics presented.

In other words: Why look for insights when insights can be delivered to you with the click of a button?


Overall, the summit made it clear that Gartner’s top priority is pushing a clearer definition and evaluation criteria around what makes a modern BI platform: how it differs from legacy technology, which features it should offer, and which stakeholders it should serve. You can read more about it in their research note on this topic, or check out our recent e-book comparing modern and legacy BI workflows.

Special thanks to Rita Sallam, Cindi Howson, Joao Tapadinhas, Josh Parenteau, Neil Chandler, Alan Duncan, Doug Laney, Thomas Oestreich and Lisa Kart for connecting with us in Texas. It was great to hear your thoughts on the industry, the product, and the future of BI and analytics.