Forecast: 2018 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Forecast: 2018 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Each year enterprise technology professionals look forward to the release of Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms. As the premier report in the marketplace, data and analytics leaders base many of their yearly initiatives and purchasing decisions on Gartner’s advice. Featuring a proprietary research methodology, the analyst house’s annual release garners hype unparalleled in the enterprise, and on par with that of Apple’s keynote events in the consumer technology space.

Set to be released on February 16th (according to the company’s release schedule), it’s interesting to note that Gartner flipped the two key terms in the title, and the 2018 version will be called the Magic Quadrant for Analytics and Business Intelligence Platforms. This is interesting to note given the market’s shift toward end-user autonomy and self-service tools.

At Solutions Review, we share in the excitement as we near the eve of Gartner’s newest release. It’s in this spirit that our editors have compiled this list of the three things we expect to see once the report becomes available.

Tableau and Microsoft will continue to dominate the marketplace

We’ve been thinking it for a few years now; Tableau and Microsoft need to have their positioning handicapped a bit in order for there to be any level of parity among the included vendors. The two providers hold an impressive spread of the market share, leaving the others to fight for the table scraps. Both companies are supremely popular in enterprise settings, and both innovate just as fast, if not faster than the startups in the space.

Tableau is in a unique situation because it’s not considered a legacy provider, although it’s been in business for more than 15 years. The Seattle-based BI vendor has really made a name for itself as a result of what is probably the best set of data viz capabilities in the marketplace. Microsoft’s Power BI suite is just plain expansive, offering a variety of deployment methods and features for virtually every possible use case in the field.

Saturation will reach a fever pitch

In last year’s report, Gartner explained: “The crowded BI and analytics market includes everything from longtime, large technology players to startups backed by enormous amounts of venture capital.” Data and analytics leaders have a wealth of tools with which to choose, as startups and disruptors have injected new technologies, practices, and buying options into a marketplace once dominated by large, legacy vendors.

Market saturation is a great thing for those looking to buy a new product. Sure it provides business stakeholders with options, but it also bodes well for end-user organization in that line-of-business folks will gain access to a far greater number of capabilities than they otherwise would have. It also can’t hurt that extreme levels of maturity breed price competition among the vendors, right?

New and emerging providers will displace traditional BI companies

In 2016, Gartner updated its research methodology to reflect the growth of agile BI tools and practices, making them the new industry standard. While the analyst house still included centralized BI provisioning as a critical capability, both decentralized analytics and data discovery made debuts as well. This signals a fundamental shift in how Gartner views the space.

Many of the up-and-coming BI and analytics providers are including forward-thinking technologies like artificial intelligence and natural language processing in their products. This is a major development, and one that figures to grow increasingly popular in the years to come. We also expect Gartner to include providers that offer capabilities once assigned to horizontal software markets moving forward (see Gartner’s Market Guide for Data Preparation).

Read Gartner’s 2018 Magic Quadrant for Analytics and Business Intelligence Platforms.

Timothy King
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