Written by GoodData Author |
A Review of the Vendors in the 2016 Magic Quadrant for Business Intelligence Platforms
I’ve always loved the brashness of sports talk show host, Jim Rome’s rule to callers, “Have a take, and don’t suck!” His instruction to offer an intelligent point of view to his audience is a great lesson to today’s analytics vendors. Vendors who understand their audience and the value that they bring to this audience will survive and grow, while those that chase all audiences with mixed messages and murky points of view will thrash.
Know your value, know your audience and don’t suck. That’s my initial take away after reading the freshly published, 2016 version of Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms.
The vendors that understand themselves, their offer in the market, and the needs of their audiences will be the survivors, while those that try to serve every use case across the entire market will face a bloodbath of competition, that ultimately results in customer confusion and mis-set expectations. From here, let’s look at this MQ from the following standpoint, does the vendor serve their audience with an intelligent point of view? Or rather, does their take suck?
Gartner cleaned out the Leader’s quadrant this year, leaving only three survivors, Microsoft, Qlik and Tableau. The other SIX leaders from last year have been dispatched to other boxes, or off the grid entirely (Vendors removed were Oracle, Actuate, Prognoz, Salient and Targit). The same nightmare holds true for the two vendors in last year’s Challenger square, Birst and Logi Analytics, who have been moved below the fold. This year twenty-one vendors fill the “Niche” or “Visionary” boxes. Of the Leaders, Microsoft obviously understands their Excel-based market, while Qlik struggles to tell the difference between its two enterprise data-discovery products and currently Tableau just lost half its market value because their offering that departmental users love is “almost enterprise.”
The evaluation criteria for this year’s MQ is heavily factored towards two sets of high-level processes. The first is around the process of ensuring the integrity of the data while you mix data sources—kind-of like trying to mix paint and not end up with a crappy looking brown color—and the second is the self-service analysis process, or does the vendor help the user find an insight? While this is an oversimplification, it will help to describe the remaining vendor’s areas of focus. So we’ll loosely bunch them across a spectrum of data blenders, data governors, self-serving discovery, dashboarders and guided analytic providers.
Alteryx, ClearStory, Pentaho, Platfora, Pyramid Analytics and Sisense and are all focusing on big-data blending activities. Alteryx preps data for Tableau—a potentially expensive combination, while Pyramid Analytics preps data for Microsoft PowerBI. ClearStory and Platfora are keen on big data of all types, while Pentaho is splunking into IoT, and Sisense’s promotion of in-process architectures to business users is like explaining particle physics to them. For these data blenders, Alteryx, who focuses and sells to the business buyer audience, seems to have the best take, with new-comer ClearStory as runner up as they are matching user needs to their target audience. Meanwhile, the other vendors are either selling the wrong thing to the right people, or the right thing to the wrong people.
Move down the data pipeline to the vendors who are trying to appeal to the enterprise need for IT-centric data governance—one truth—while also purportedly offering flexibility to end users who want agility to find “their truth.” Here we’ll see Birst, Information Builders, Logi, and Microstrategy. IBI, Logi and Microstrategy are all trying to shake off their dramatic re-positioning in the MQ, along with their legacy baggage, while trying to evolve into business-user friendly vendors, while Birst moves to displace these legacy vendors and others like Oracle. Birst’s message gets confusing fast, though, as they are ‘hybrid-everything.’ (Eg. in the cloud and on-prem; 2-tier data; middleware for Tableau; embedded and internal; SMB and enterprise) They beg the question, how many takes does it take to suck?
Getting into the self-service discovery and analysis processes, we have a whole slew of business-centric audience pockets like executives, sales and service managers, scientists and everyday users. Some audiences are built-in, for example SAP and Salesforce, like Microsoft, have captive communities who will readily agree with whatever point of view they offer, but their willingness to expand beyond their source base makes their points a little stale. Specialty tools like Datawatch, SAS and Tibco are trying to reinvent their legacy products for new use cases like unstructured data and data science, but these are still old dogs for these very narrow audiences.
The dashboard and storytelling portal vendors, Domo, Board and Yellowfin are catering to executive audiences using collaboration and visualizations as their value. The challenge here is that they are still lacking functionality that will keep these important audiences engaged. So while their take is interesting, it may not be sustainable as visualization tools become increasingly commoditized.
Smart Analytics Vendors
Interesting vendors are the ones with suggestive and machine-intelligence technologies like BeyondCore and Watson Analytics, but Beyond IBM’s advertising, they have not yet caught the mainstream.
A Unique Point of View
What’s interesting about Gartner’s take on GoodData’s, is that we are helping enterprises and ISVs identify ways to securely deliver analytic value to under-served audiences. We call it unlocking the value of your data investments with our analytics distribution platform. We help service-centric industries like retailers, restaurants, hospitality, financial services, healthcare, life sciences, media and technology deliver tailored analytics to audiences with whom they work—their business units, stores, partners, customers, agents and providers. We bring analytics to people of any skill level through our guided experience, and we actually measure the engagement levels of users, so you know what they like. We treat every engagement like we are helping you build a data product - even if you don’t charge for it, it will still impact the bottom line.
We have spent a lot of time helping the analyst community understand our point of view. Happily, they were listening, not only does Gartner understand it, but so does Forrester, where we were named a leader in both their Waves for Agile BI and Cloud BI and Analytics. But a favorite write up of mine is the recent note from Blue Hill Research on our customer success in unlocking the value of their data and impacting revenue. You can read it here.
Written by GoodData Author |