Skip to main navigation Skip to main content Skip to social media links Skip to footer navigation
Sign In

Top 10 Highlights: Gartner Data and Analytics Summit 2017

Jay Wilder

This past week at Gartner’s 2017 Data and Analytics Summit, 3000 registrants converged on Grapevine, TX to share and learn how to make data more accessible, useable and meaningful at scale.  Through the week, different perspectives revolved around a central theme that we are now living in the ‘Age of Infinite Possibilities.’  The mood was one of urgency– to challenge oneself, to shake off the limitations of the past and think bigger about transformation through democratized data and analytics.  

Top 10 highlights:

  1. Opening Keynote – “Abundance and Scarcity”:  Gartner’s Kurt Schlegel and Deborah Logan kicked off the conference with a comparison of data literacy today to reading literacy before the printing press.  Smarter technology opens information to the masses and transforms society. It allows reading literacy and data literacy to flourish.  Kurt and Deborah urged everyone to rebalance the abundance of data and scarcity of insights across organizations. 
  2. “By 2020 50% of analytics queries will be generated by NLP, NLG, search and automated Insights”: Rita Sallam shared how modern analytics are getting more human.  NLP (natural language processing) and Search are letting us speak with our data (see Datorama’s Alexa integration) while NLG (natural language generation) turns graphs and charts into paragraphs of insights that anyone can read.  What’s most interesting? Machine-generated insights that help us find the biggest needles in our data haystacks.  (See what it means for marketers)
  3. “Your next product is in your data”:  Gareth Herschel talked customer analytics and showed how your next big product may be sitting in your data.  You just need to look.  Some of my favorite examples were Coke’s use of digital products to learn more about their customers, L’Oreal’s use of YouTube to develop new products based on DIY ombre videos, Netflix’s ISP data sharing with consumers to point the finger on performance problems, and social listening’s ability to bring together unlikely collaborations like Martha Stewart and Snoop Dogg (people love to DIY while listening to gangsta rap.  Who knew!?). 
  4. “Ford prepares for massive amounts of data”:  Alan Jacobson shared an update on data science at Ford.  What was most interesting was the massive amount of real-time streaming data Ford is getting ready for. Why?  Autonomous and connected vehicles.  Did you know Ford has more than 500 data scientists and is planning to hire 1200 more?  Maybe that’s why data scientists are so scarce in the market (jk).  
  5. “Why social analytics fail”:  Jenny Sussin broke down why social analytics don’t always work for companies. Her advice?  Go where your customers are.  That’s not always just Facebook or Twitter.  It could be Instagram, Snapchat, Pinterest, Reddit, WhatsApp, LinkedIn, WordPress or newer sites like Product Hunt.  Don’t just listen for your brand either, get more specific.  How are people talking about your pricing?  Your availability?  That’s where you’ll learn from your customers.  Don’t measure social in a silo either.  Social needs to be analyzed in the context of all your marketing– from its impact on your messaging to its performance in comparison and correlation with all your other channels and customer journey stages.  Get your social connected.  (we can help)
  6. Mr. Robot creator Sam Esmail talked culture, hacking and stories:  This was a great way to break up the sessions.  Sam Esmail created the popular series Mr. Robot (USA Network) and explored flawed characters in stories, our modern sense of “curated identity” in the digital world, and the modern loneliness of a hacker that new everything about everyone, but knew no one at all.  
  7. “Get to the point with domain-specific ‘analytics apps’”:  To a packed room of IT and business intelligence professionals, Gartner’s Jim Hare made a call to the room.  Look beyond the traditional business intelligence tools for your business users.  Look at “Analytics Apps.”  For marketing, sales and customer data this couldn’t be more true. Jim defined these as platforms that focus on their space, know their customer and innovate against the key challenges faster and more deeply.  (See how we do this for marketing)
  8. “Surprise results in the analytics maturity curve”:  Despite years of working with data, when it comes to analytics maturity, companies rate themselves for predictive and prescriptive analytics with very low scores.  In fact, 74% of companies identify as being at the descriptive reporting state, while only 34% identify as being diagnostic. 11% and 1% round out the two advanced categories.   I was surprised that the numbers were so low, but chats outside the sessions supported this, with some saying they’re still just trying to get their data connected in a more efficient way so they can move up the curve.
  9. “Get agile with your data preparation”:  With all the focus on analytics to this point, this might have been the most important session of the show–because good analytics rely on the right data being connected, cleansed and organized. Rita Sallam urged the room to rethink this critical foundational layer of your data and get out of the “waterfall” mentality of traditional BI (a term borrowed from traditional software engineering projects) .  Business users need fast iterative access to data and they need new data on a frequent basis.  Just like self-service analytics, the business needs self-service data prep and it needs to be easy.   If you haven’t checked out Datorama’s intelligent AI powered data integration and harmonization, you can learn more in Gartner’s Cool Vendor report on Datorama.
  10. AI and machine learning stole the show:  AI and machine-intelligence was everywhere and on everyone’s lips.  That’s great to see as Datorama has pioneered AI machine learning for marketing intelligence and analytics and will continue to lead the way.  The present and future is clearly “An Age of Infinite Possibilities” and AI and machine intelligence will be the enablers of our new data literacy, just as the printing press kicked off the democratization of the written word and reading literacy nearly 600 years ago.
    Texas BBQ (Honorable mention):  Texas BBQ is amazing and Grapevine, TX will not disappoint.  While there were too many items on the highlights list, an honorable mention must be included.  If you’re in the area, Hard Eight BBQ is the local favorite.


To see what made other people’s highlight lists check out #GartnerDA on Twitter or LinkedIn.


Make sure you stay up-to-date with all the latest AdTech, MarTech, Data and Datorama-related news by following us on TwitterFacebook and LinkedIn.

Marketing Intelligence Report

Marketing Intelligence Report

Explore the first edition the Marketing Intelligence Report for an inside look into how the new growth imperative is affecting marketers across every industry.

Download Now