What’s Changed: 2024 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Solutions Review’s Executive Editor Tim King highlights what’s changed since the last iteration of Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms and provide an analysis of the new report.

Analyst house Gartner, Inc. has released its 2024 Magic Quadrant for Analytics and Business Intelligence Platforms. Gartner defines the marketplace as being “Analytics and business intelligence platforms — enabled by IT and augmented by AI — empower users to model, analyze and share data. Analytics and business intelligence (ABI) platforms enable organizations to understand their data.” In this way, we can see that BI platforms, augmented by AI, are the market norm and should drive your vendor selection process.

In order to qualify for this Magic Quadrant, vendors must offer a generally available software product that met Gartner’s definition of an ABI platform. Platforms must also “enable less-technical users — including business people — to model, analyze, explore, share and manage data, and collaborate and share findings, enabled by IT and augmented by AI.”

And what features are commonly available in these types of products? Gartner leads with automated insights, saying: “The ability to apply machine learning (ML) techniques to automatically generate insights for end users (for example, identifying the most important attributes in a dataset).​” There are also metrics layers, data storytelling modules, NLQ (short for natural language query), collaboration, and composability features to be on the lookout for.

Mandatory features include, of course, data visualization, reporting, data preparation tools, data science integrations, and governance. In fact these capabilities are so embedded that Gartner leads the report with: “While integration with cloud ecosystems and business applications is a crucial selection requirement, buyers also need platforms to support governance, interoperability and AI.”

Gartner adjusts its evaluation and inclusion criteria for Magic Quadrants as software markets evolve. In this Magic Quadrant, Gartner evaluates the strengths and weaknesses of 20 providers that it considers most significant in the marketplace, and provides readers with a graph (the Magic Quadrant) plotting the vendors based on their ability to execute and completeness of vision. The graph is divided into four quadrants: niche players, challengers, visionaries, and leaders.

At Solutions Review, we read the report, available here, and pulled out the key takeaways.

Microsoft retains its leadership position for another year, according to Gartner analysts, and still with Salesforce (Tableau) in tow. Microsoft’s entrenched market reach and share through 365, along with innovation in its new Fabric tech and the continued success of Power BI make it an obvious choice for many reasons.

Salesforce remains known for its visual analytics tools through Tableau, which enable data prep and reporting. A recent augmented experience called Pulse (released in 2023) was a big addition for end-users, while newer white labeling options and usage-based pricing still make Tableau an excellent consideration.

Qlik retained its status as a leader as well, even moving up Gartner’s horizontal placement for its ability to execute. And boy has Qlik executed, making big AI bets and launching Staige in September of 2023. According to Gartner: “Staige combines a data foundation, automation and AI-based descriptive, predictive and prescriptive analytics to accelerate the delivery of decision-centric solutions.”

There are three new leaders for 2024: Google, Oracle, and ThoughtSpot; not much of a surprise for any of these major players in BI and analytics. Google is placed as a result of its Looker product line, and in 2023, the web giant integrated Looker Studio with the Looker semantic layer. Oracle recently enhanced its AI-based analytics into document understanding, according to the analyst, and now enables its customers to use GenAI to create data stories.

ThoughtSpot has been on this trajectory for years, disrupting the BI market at its launch in 2012. According to Gartner: “Customers frequently cite ThoughtSpot’s consumer-friendly UX focus on a search experience for data storytelling, its ability to handle complex analysis and its scalability to analyze large datasets as reasons for purchase.” 2023 saw the vendor launch ThoughtSpot Sage, a GenAI-enabled conversational analytics toolset.

AWS leads Gartner’s challenger chart, straddling the leader line along with noted providers Domo and MicroStrategy, the BI and Bitcoin company. According to Gartner, AWS’s extended natural language features (through Q): “enables business analysts to build (and refine) dashboards and create new calculations. Analytics consumers can use NLQ on their data beyond what’s in their dashboard — in particular to create executive summaries and autogenerate data stories.”

Domo is a top choice for the marketing analytics use case, though it also serves small and medium organizations that lack data warehousing foundations. Domo is unique in that it offers a complete architecture, as Gartner says it: “from data collection and ETL to BI, analytics and app creation.” MicroStrategy dropped its anticipated suite of GenAI tools last fall, giving it a jolt of energy in this space. Gartner also notes that “MicroStrategy excels at reporting, manageability and governance.”

While SAP and Pyramid Analytics lead the visionary vendors, according to the report, there remains a cluster of IBM, Spotfire, and SAS a stone’s throw below it on the graph. That is likely because IBM, Spotfire, and SAS have an entrenched base of users with less room for growth into the leader category than do vendors like SAP, though while in a similar position to the others, has reach and momentum approaching that of Microsoft in some circles.

Late last year Pyramid Analytics added GenAI features that leverage a multi-LLM approach. According to Gartner: “This means that its NLP can flexibly use Pyramid’s own internal portable language model or third-party LLMs.”

Incorta, Zoho, Sisense, and GoodData are all in niche positions supporting their top use cases. For Incorta, that’s fast data modeling in enterprise apps. For Zoho, its data prep and visualization and a marketplace of pre-built apps. For Sisense, its self-service and embedded analytics. It’s a similar story for GoodData.

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

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