Gartner’s 2016 BI Magic Quadrant: Insights from Tableau, Qlik and Logi

Every year, Gartner assesses the market for business intelligence software. Its annual analysis has become a valuable go-to source for anyone researching this buying space, especially outsiders.

With the release of Gartner’s 2016 BI & Analytics Magic Quadrant report, it seems the market is resetting itself in order to reach a common goal: Empower the average business person.

Gartner 2016 BI Magic Quadrant

That’s why we’ve called on Logi Analytics, Qlik and Tableau for more on where this market is headed. Each vendor experienced a significant shift, so we got their thoughts on Gartner’s assessments and larger BI trends.

But first, let’s recap the context of this report in layman’s terms so we’re all on the same page.

Key Business Intelligence Trends

Self-service has been the buzzword leading up to this report as a push for employees outside of IT to take the reins with analyzing data.

Historically, BI has fallen to the responsibility of data scientists and IT specialists. As a result, business end-users have become frustrated by limited access to data.  Vendors have reacted by adapting their solutions to allow for more self-service from non-IT roles, and continue to develop more intuitive and user-friendly features.

A growing challenge with self-service is that when more users have access to creating their own data insights, this opens up holes in a data governance strategy. Frustrated end-users in the past have felt pushed to deviate from their organization’s data policy. Shadow IT is the term for when a department or team uses a solution without IT’s direct approval. A lot can go wrong when a company’s reporting strategy cuts corners to supplement self-service. It’s usually expensive and complicated to fix, all while things seem OK to the average user.

On the topic of crossing self-service with data governance, there’s a new concept that’s growing more popular called a data lake. It’s the practice of gathering all of a company’s data into one place for BI tools of any kind to connect with. This helps organizations choose best-of-breed solutions rather than settling for an all-in-one package. Data lakes work well with self-service tools, but create much greater challenges with properly categorizing and securing data for a dependable governance strategy.

While data lakes are distant for most, companies such as Google, Twitter and Facebook are early adopters. For example, each Tweet is categorized by metadata. This metadata makes it easier to organize a data lake.

With these trends in mind, the core challenge for vendors in 2016 is to help businesses wise up to the value of their data. The price of these solutions becomes another minor challenge as vendors aim to be as a well rounded as possible, as Tableau has shown when compared to similar software. The tools vendors are developing, the services they’re offering and the users they’re targeting must all come together to support a secure data governance strategy together with a highly accessible reporting strategy.

This is important because the individuals with the highest potential for solving business problems aren’t data scientists or statisticians, but the average users facing their problems head on.

Gartner’s 2016 Report

Gartner’s latest BI & Analytics Magic Quadrant took a different approach in evaluating vendors.  Responding to the shift in buying decisions from IT to business stakeholders, Gartner’s 2016 report focuses on products that align with the criteria of a modern BI and analytics platform.  Enterprise solutions not meeting these new standards are going to be covered in Gartner’s new Market Guide for enterprise reporting-based platforms.

Gartner’s BI & Analytics report is now based on the following five main use cases:

  • Agile Centralized BI Provisioning
  • Decentralized Analytics
  • Governed Data Discovery
  • Embedded BI
  • Extranet Deployment

Here’s how Gartner’s latest report compares to 2015:

Gartner MQ BI 2015


Gartner MQ BI 2016


Tableau and Qlik have remained rivals over time. Tableau’s lead, however, has dropped significantly due to a few reasons behind Gartner’s methods for ranking and other market challenges. With only three Leaders and no Challengers in this year’s report, it’s said the market has moved toward Visionaries to reset itself for major changes.

As for Logi, this vendor has taken the typical path of an up-and-coming player, from Niche, to Challenger, and now Visionary. Taking a closer look at Logi’s focus on features and functions, it’s no surprise it’s part of the general shift into this quadrant.

What do the Vendors Have to Say?

All three vendors care deeply about enabling self-service, and they have very distinct qualities. We were able to interview Tableau Director of Analyst Relations, Ajay Chandramouly, Qlik VP Global Product Marketing, James Fisher, and Logi Analytics VP of Product Management, Brian Brinkmann.



Logi icon“We’re innovating very rapidly, particularly in the last 3-4 yrs on the products, to stay ahead of our customers’ needs.

“Logi Vision introduced ‘social’ techniques to communication. Where traditional BI sharing was publishing and subscribing to scheduled reports, modern BI is answering a cultural change in the way people think about information. We don’t homogenize the market. The best way to success is to recognize that there are different sets of people with different sets of skills at every company.

“Where crowdsourcing comes in: What better way to do that than by mirroring the collaboration/crowdsourcing experienced with Facebook, Twitter, Instagram and applying it to internal communications? The more people who like/comment/share data and analysis, the more people make better decisions. What you want is people to look at it, think about it, how it impacts them and others. This has a far better impact for overall organization. Logi is an early innovator in this area.”

Brian Brinkmann
Brian Brinkmann
VP of Product Management
Logi Analytics

Bottom Line: Embedded within Logi Analytics is a Facebook-style vision for collaboration. When the average business person is able to bring data insights into daily conversations, there’s greater influence to make data-backed decisions across an organization.


Qlik icon“Qlik’s innovative and unique associative model enables users to probe all the possible associations that exist in their data, across all of their data sources. This means the user is not limited by predefined hierarchies or preconceived notions of how data should be related, but can finally understand and explore how it truly is related. The result: they see the whole story that lives within their data.

“We are focused on business scenarios and delivery solutions to meet these needs. Making data and our platform accessible, addressing all analytics use cases and empowering users across the enterprise are central to our thinking. Qlik today has tens of thousands of users of our Qlik Sense Cloud offering, which is available in free and paid versions. This allows users to create and share fully interactive applications with co-workers and friends via a public cloud offering, which includes rich collaboration and storytelling features and full responsive design that supports all mobile devices.”

James Fisher
James Fisher
VP Global Product Marketing

Bottom Line: Qlik’s focus on self-service allows users to tell a story with their data, then lets them share and interact with the story. Qlik was once behind on mobile and cloud capabilities, and now it has these functions front and center to make data more accessible.


tableau icon“Regardless of the competition, Tableau remains committed to our mission of helping people see and understand their data through modern, self-service visual analytics at scale. To continue this mission, over the next two years Tableau plans to spend more on research and development than in the previous 10 years combined.

“We will stay ahead by continuing to embed our core beliefs into our products, including: The people who know the data should be empowered to ask questions of the data, people are smart & computers are tools to augment their intelligence & creativity, and flow, flexibility, & freedom are key to creative thinking.

Our priority for supporting our growing user base is first and foremost product innovation – we strive to create a product that is easy to use and that our customers enjoy using day in and day out.”

Ajay Chandramouly
Ajay Chandramouly
Director of Analyst Relations
Tableau Software

Bottom Line: For a long time Tableau has been the gold standard in many regards, empowering users who understand their data to create their own predictive insights. By continuing its mission and sticking to core beliefs, Tableau is positioned to extend usability as a front-end tool, but has also been criticized for not bringing enough self-service to data preparation on the back-end.


We were also able to ask a bit about how these vendors view the challenges of data governance in reference to the future of enterprise data lakes.

Data Governance and Data Lakes:


Logi icon“The premise of a data lake is alluring: Put all your data of any variety into one place and let the computer resources pull it out for you when you want to analyze it. But beware: Michael Stonebraker, the 2014 Turning Award winner (also known as the Nobel Prize of computing), refers to a ‘Data Lake’ as a ‘Data Swamp.’

“At this point, a data lake is largely a dumping point for data and still years away from broad adoption and maturity. A good analogy is the state of data warehousing and business intelligence circa 1996. It took a decade to truly mature.  If you are looking to take advance of data lakes, Logi offers data access, preparation, and caching to help create useful analysis and governance from your data lakes. At the same time, it’s important to recognize there will be manual effort needed to understand and curate the data – otherwise you run the risk of having an anoxic data lake.

Brian Brinkmann
Brian Brinkmann
VP of Product Management
Logi Analytics

Bottom Line: Logi’s vision for sharing and discussing data across users fits with social media platforms going the route of managing data lakes. While it’s admittedly years away, as the market resets trends such as this one require the right strategy deep within the solution’s architecture.


Qlik icon“For Qlik, data lakes represent the natural evolution of the same challenges organizations have faced for decades – how to handle increasingly voluminous and diverse data. Qlik is very well positioned to handle the ‘data lake’ phenomenon because ultimately Qlik’s platform approach and associative model strikes the balance between data access/agility and ensuring trust around who can access the data, and when. In addition, ‘data lakes’ don’t always contain all of the data needed to find answers to business problems. Qlik’s associative model is designed to quickly add new data sources when needed, without a time-consuming remodelling of data or creation of new queries, something other tools in the market require.

“Governance is key for all and Qlik provides agility for the business user, with trust and scale for IT. We support data sourcing and preparation, visualization and analytics, collaboration and reporting, all within a governed framework that empowers users to consistently make trusted data driven decisions.”

James Fisher
James Fisher
VP Global Product Marketing

Bottom Line: While organizations collecting data in bulk have advantages, the tools and expertise for organizing and mining the data require extensive forethought. Qlik has a record of prioritizing governed frameworks, but views their development as fitting with the end-goals of data lakes.


tableau icon“We absolutely support and enable our customers to connect to data lakes if they choose that as part of their storage strategy to store data in its native format without having to define a schema beforehand. Tableau provides the broadest and most flexible way to connect to the most widely used data sources, both in the cloud and on premises. In a sense, Tableau is the ‘Switzerland’ of data, by allowing our customers to connect natively to over 45 data sources (and counting) so that customers can leverage the data source investments they’ve already made

“This enables our customers to choose best of breed solutions that work for them, rather than settle for inferior components and lock themselves into a proprietary vertical solution stack.”

Ajay Chandramouly
Ajay Chandramouly
Director of Analyst Relations
Tableau Software

Bottom Line: The latest report highlights how Tableau runs the risk of cornering itself as an expensive front-end tool, but if incorporating enterprise data lakes become more popular, this plays to Tableau’s advantage by simplifying preparation further and keeping Tableau a best-in-breed for visualizations. All the while, Tableau is the “Switzerland” that works with many data sources.


Now that Gartner has placed BI & Analytics solutions into their own user-focused category, it’s time for vendors to take on the challenges of self-service. This means eliminating myths about who self-service is meant for and the expectations of those users’ technical skills. Improvements to many vendor’s customer service and user communities are in order, as well as further research and development for the user experience.

However, these are improvements that vendors have always kept on the backburner. The difference now is that the playing field has been leveled, bringing a spotlight to vendors such as Logi Analytics for Facebook-style communication and pushing Tableau to spend more in the next two years on R&D than the last ten combined. Surviving in the current climate requires adaptation for broadening the usability of BI solutions.

IBM is another vendor worth noting as its own products including IBM Watson have begun to cannibalize the company, causing their own disruption before the competition moves in. The concept of Artificial Intelligence is in sight for some big name vendors, but much like the concept of data lakes, there’s not a clear vision on how to get there. This has pushed development for many vendors to take unpredictable turns. Compared with Tableau’s steady vision, IBM has taken a much riskier route. This may have poised them ahead of the market as a visionary, but has also significantly cut into itself and worries investors.

2016 is a big year for the business intelligence market. With the underlying goal to make insights more accessible and empower average business people, everything seen through the user’s perspective is a reflection of the market reacting to disruptive advancements.

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