It’s that time of year again. The worst of winter is behind us; spring is just around the corner; there’s magic in the air. That’s right, it’s Magic Quadrant season! The Oscars of data analytics just dropped like a new album.
I, for one, was salivating to read Gartner’s latest update to their “Magic Quadrant for Analytics and Business Intelligence Platforms” in it’s entirety, all 30k+ words, at least a few times through. Yes, I’m painfully aware of how pathetic that sounds. You probably have better things to do with your time, so I’m going to boil it down to the key points for you so that you don’t have to spend a Saturday night curled up with your tablet. (If you’re a nerd like me and still want to read the full report, and it’s worth the read, you can purchase a copy through Gartner. Or if you just want an overview from the researchers involved in the report, you could sign up for Gartner’s free webinar on March 12.)
Magic 8 Ball – Gartner’s Predictions for the Future of BI and Analytics
Before I get to the main event, the part of this report that I always find the most fascinating is Gartner’s predictions for the future of BI and analytics based on the responses received from the engaged BI users responding to their survey. While it’s interesting to see where individual platforms are rated, my favorite part of the report is the insight into trends in the market and user opinions and needs as well as predictions on future innovations.
Fast and Furious – Increasingly Rapid Innovations
Gartner observed rapid progress in implementation of “augmented analytics”. This includes machine learning-enabled analytics, NLP-based queries, and NLG based visualization interpretation. While they don’t see users currently fully adopting this next iteration of analytics, they predict that typical early adopters will set the ball rolling for augmented analytics to rapidly become standard practice.
Scale Model – Accommodating Data Volume and Complexity
Multiple factors are driving the need to for BI platforms to accommodate an increasing volume of data and more complex data structures. Clearly the primary driver is the growing availability of data, from numerous data sources, and in multiple formats. The sheer volume of data and complex relationships between various data sources has led to innovations in data storage models and a rise in the use of data lakes. Additionally, end users are becoming increasingly sophisticated in their data inquiries and analytic needs. While some firms are already leading the way in anticipating ever increasing analytical needs (MicroStrategy, Tableau, Oracle and Pyramid Analytics), all will need to make this a priority moving forward.
Embedded Evidence – Embedded Analytics for Increased Functionality
Whether embedding visualizations in internal platforms for communication of information within an enterprise, or embedding dashboards in customer facing platforms for value add or monetized data, this use of analytics platforms is one to keep an eye on. Gartner notes Logi Analytics, Sisense, Salesforce and Qlik as being on the leading edge of this trend.
Market Forces – The Race for Competitive Pricing
Microsoft is driving a downward pricing trend, essentially eliminating barriers to entry. The market has responded with a number of pricing models to fit the needs of virtually any firm. Vendors are offering low initial costs through per-user subscription-based plans, long-term savings through unlimited perpetual licensing at a higher up-front investment, and any number of hybrid options between those two extremes. Niche players offering unique capabilities continue to demand a premium, but competition amongst most platforms has resulted in better value for end users.
Cloud Convergence – A Watershed Moment in Cloud-Based BI
Cloud usage nearly doubled amongst respondents since last year’s survey following advancements allowing for customized cloud usage that integrates seamlessly with on premises storage. The cloud has become so ubiquitous in the market that some advancements have initiated in the cloud and some products are only, or primarily, cloud capable. The paradox noted by Gartner is that despite this storm surge in cloud usage amongst Magic Quadrant respondents, they observed a rather dry reception amongst their general client base, with cloud adoption below 10%.
Odds & Ends
Other noted trends include expected innovations to support the increasingly available real-time data generated by the IoT, innovations to the market as a whole through significant capital investment—both by current vendors and disruptor startups, and a broader exchange of plug-ins that increase functionality from data transformation to visualization. If Gartner’s predictions come to fruition the next few years will be a wild ride!
Now that I’ve covered my favorite part of the report, here it is folks, Gartner’s 2018 Magic Quadrant for Analytics and Business Intelligence Platforms.
Figure 1: Magic Quadrant for Analytics and Business Intelligence Platforms – Source: Gartner (February 2018)
So first off, the necessary qualifiers: 1) To fully understand what’s represented in the visualization, you have to take it in the context of the full reporting of the research conducted by Gartner. 2) Gartner doesn’t endorse or support any of the platforms or firms included and discourages use of this report as a sole source for making decisions about purchasing a particular BI platform. 3) The research is a snapshot in time. Analytics and BI platforms, and the marketplace, can evolve rapidly. The take home here is that you can’t base a decision on which platform will fit your organization best on a single scatter plot. (Side note: If you are looking to use the information from Gartner’s report as one factor to inform your decision on purchasing a BI platform, paid subscribers have access to slicing and filtering of the data behind the quadrant based on criteria relevant to your organization.)
As a refresher for those who have seen it before, and an overview for those who haven’t, the results are based on survey responses from users of the various platforms reviewed. (This version had 1,526 respondents.) Generally speaking, ratings for ‘Completeness of Vision’ are derived from responses to topics related to business planning and strategy, which includes areas like: awareness of user needs, responsiveness and innovation in development plans, and effectiveness of sales, marketing, and communication strategies. Ratings for ‘Ability to Execute’ are derived from responses related to the how well those plans and strategies are translated into deliverables, which, of course, includes functionality of the platform.
You can see that there was no noteworthy change in the ‘Leaders’ quadrant since last year. Microsoft, Tableau, and Qlik maintain their dominance and remain rated fairly similarly to the previous survey. While several platforms reviewed last year were excluded for various reasons, the only newcomer to this year’s report was Looker, with a solid spot in the ‘Niche Players’ quadrant. Several vendors received significantly lower ratings in ability to execute compared to last year’s survey, including: IBM, SAP, Tibco, Birst, and Logi Analytics. Sisense was rated more favorably in both completeness of vision and ability to execute, moving it close to the border of the ‘Leaders’ quadrant; it will be interesting to see whether it can maintain that momentum going forward. The most notable change, however, was MicroStrategy. The firm was rated lower than last year for completeness of vision, but significantly higher for ability to execute, moving it into the ‘Challengers’ quadrant as the sole platform occupying that space.