1. Magic Quadrant for Business Intelligence and Analytics Platforms (2017)
2. Critical Capabilities for Business Intelligence and Analytics Platforms (2016)
3. Magic Quadrant for Data Science Platforms (2017)
4. Market Guide for Enterprise-Reporting-Based Platforms (2016)
For a decision-maker, it is important to understand that Gartner has chosen to divide the BI portfolio into different verticals that in some respect relate to one another. Firstly they have made a distinction between “Enterprise Reporting Platforms” and “Modern BI Platforms”. This was implemented in the 2016 report and drastically changed the landscape wherein the number of retailers in the leader quadrant went from nine to three! The same three, Tableau, Microsoft and Qlik, are also found in the leader quadrant in 2017. The next division is the differentiation between “Modern BI Platform” and a “Data Science Platform”. This is worth keeping in mind when evaluating players such as SAS and IBM, which are both classed as visionaries within BI & Analytics but as leaders within data science.
The image below is taken from the Gartner report on Enterprise Reporting Platforms and indicates where the various products belong. I would like to point out that a good platform for enterprise reporting is extremely valuable when the time comes to start working with “modern BI” and data discovery.
To be able to focus on Gartner's BI platform report, this year’s editions for Critical Capabilities and Enterprise Reporting are out of scope in this blog post. The one pertaining to Critical Capabilities is of interest to those who wish to evaluate the various features of a BI platform.
The leaders in 2017
The image below shows this year’s Magic Quadrant together with the players’ position last year. For those who have a little time for a more in-depth analysis, I recommend a visit to Fredrik Hedenström’s gartner dashboard! Microsoft, Tableau and Qlik can once again call themselves leaders this year. Tableau is being promoted as the “Gold standard for intuitive interactive exploration” but many enterprise features also turn out to be a “work in progress” and not really in place yet, and that the product’s hallmark intuitive interface for exploration of data has become mainstream and is being offered by all major BI providers. It will be exciting to see what impact their acquisition of HyPer has on the product’s analysis engine!
Microsoft Power BI has succeeded in positioning itself furthest to the right on the scale of “completeness of vision”, which is attributed to them constantly acting in accordance with their roadmap and updating the product each month. Microsoft was ahead of the pack with search-based analytics and its Questions and Answers feature, and it has recently introduced the Quick insights feature as a simple variant of smart data discovery. At the same time, work is being pursued to integrate the statistical language R in the product and the work with machine learning is ongoing. What I personally find most interesting is how Microsoft is moving towards actionable BI with the integration between Microsoft Flow and Dynamics!
Qlik’s position in the leader quadrant is driven by a robust product, a positive customer experience and a strong network of global partners. Compared with both of the other leaders, their market performance has been impacted by a split focus between the established product QlikView and the slightly less mature product Qlik Sense. This, coupled with the fact that Qlik has not made any investments relating to smart data discovery and has a Cloud strategy that is under development, has resulted in them not receiving as high a score as Tableau and Microsoft.
To keep an eye on
There are two players outside the leader quadrant that I think deserve a mention: IBM and Salesforce. IBM dropped significantly when the quadrant was reformulated in 2016, but this year they have moved in a positive direction. I believe that we will see them in the leader quadrant next year. Cognos Analytics 11 was released at the end of 2015, providing a more contemporary user experience, while at the same time IBM’s second product, Watson Analytics, offers users the next generation of machine learning-supported user experience with automatic patter recognition and natural query language. On top of all this, there are two additional products with SPSS Predictive Analytics and IBM Data Science Experience (leaders in the data science quadrant). As you can see, there is great potential in IBM’s offering on the market and their challenge will be to focus and align their offers in a way that does not confuse the market.
Salesforce is a CRM tool, and their journey from niche player to visionary surprised me and motivated further research. Their BI product Salesforce Wave Analytcs (Wave) is sold separately as a modern point-and-click dashboard solution. What is more interesting is that Salesforce has recently acquired a number of AI-focused companies as well as the slightly more established BI product BeyondCore (visionary in 2016). Overall, this means that Salesforce is offering its customers automatic customer insights along with generated narrative and analytics. In 2017 Salesforce will put a lot of energy into selling independent analytics solutions, under the market name Einstein, optimised for its already large customer base. It will be very exciting to see how Salesforce develops as a BI player in 2017, particularly if they expand their offer to customers who do not already use their CRM tool or who want to mix their CRM data with other ERP data.
Overall trends for modern BI platforms
The exploratory analysis is today established as the modern complement to a business’ already existing fixed reports. Almost all medium and large businesses currently have a battery of fixed parament-driven reports that are used to varying degrees in the business. In recent years, this has been complemented with a tool that allows the exploration of data, which has cemented players like Qlik and Tableau as leaders in a class of their own. The first to catch up with them in this area was Microsoft with Power BI, which, owing to its breadth, has already to some extent passed the two others on their home turf. IBM, SAP and the other dragons have also developed their offering to include similar elements. The next paradigm shift was something called Smart Insights, which in short means that the tools produce their own proposals and present correlations, in addition to causation to the extent that this is possible. In this area, players such as IBM, SAP and Microsoft, but also Salesforce and Sisense, are well positioned, while Tableau and Qlik have thus far not presented any news. It will be exciting to see how these two disruptive players will act in the future to maintain their positions as leaders in the market.
Gartner has also noted that the maturity level regarding cloud solutions is gaining importance as the buyers have become accustomed to the idea of also using the cloud for their analytics solutions. Another overall trend is that the buyers expect the option of embedding their analytics in other contexts and the BI providers require sensible licensing models to support this area of use. Real-time analytics also extend the application range of BI to increasingly close in on the operational activities, with automatic decisions or proposals for activities based on the available data at the time.
To sum up, I look to the future of BI with confidence, and it will be exciting to see what those of us who implement these solutions can offer our customers in terms of smart insights in the future. If you have other insights from the report that you wish to share or discuss with me, please leave a comment below! If you need help navigating you way through the various tools, feel free to get in touch and we will guide you to the right tool for your activity!
Business Intelligence Consultant
Data & Analytics, Enfo