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Gartner: Augmented analytics, ecosystem for BI now key

While AI capabilities are now a must for BI vendors, it is becoming increasingly important that their capabilities fit into a larger ecosystem for users, according to Gartner.

Capabilities remain crucial for analytics vendors, but how those capabilities fit into an overall analytics ecosystem is increasingly taking on importance.

Each year, Gartner, a research and advisory firm founded in 1979 and based in Stamford, Conn., publishes its Magic Quadrant for Analytics and Business Intelligence Platforms, a report that rates leading BI and analytics vendors based on their ability to execute and completeness of vision.

Based on those two measures, Gartner places each vendor on a graph, with completeness of vision representing the X axis and ability to execute the Y axis. Four quadrants result, with the top-right quadrant titled the Leaders Quadrant.

This year's report was released in late March, and as in recent years, augmented analytics capabilities such as natural language query, natural language generation and automated insights were primary considerations.

Considerations evolve, however, and unlike in previous years, how the vendor's analytics platform fits into a larger ecosystem for analytics was also an important consideration, according to Austin Kronz, a director analyst at Gartner and one of the authors of the 2022 report.

An analytics ecosystem is an environment where business intelligence is part of a larger whole.

Instead of a separate BI environment sitting on top of a database, in which data needs to be moved back and forth, one example of an analytics ecosystem is symbiosis between a BI platform and database that enables query and analysis.

Another is to embed analytics applications into the everyday workflows of users, whether in collaboration tools or applications like CRM, ERP and HR systems. And still another is to make BI part of an end-to-end analytics platform, from data capture through insight and action.

In a recent interview, Kronz discussed this year's Magic Quadrant, including how the criteria for rating vendors has evolved and what separates the Leaders from the rest. He also delved into the trends influencing the market and those that might play a role in the near future.

As you evaluated the different vendors this year, what was some of the criteria you used to rate them?

Austin KronzAustin Kronz

Austin Kronz: Any Gartner Magic Quadrant still follows the two axes. There's the vertical one, which is the ability to execute, and the horizontal one, which is the completeness of vision. There are about six or seven criteria that make up each of those axes.

In terms of ability to execute, we're looking at the product itself -- the overall viability in terms of how it fits in the market, how they're executing their sales, their customer experience, their operations, their responsiveness to trends in the market and their ability to pivot as customer needs shift. In terms of completeness of vision, we look at marketing and sales strategy, their product roadmap, how they're innovating, and how well they understand the market and perceive the future of the market.

You mentioned market trends -- those evolve from year to year, so what were some key trends that were important for vendors to be in on this year?

Kronz: Over the past five years or so, augmented analytics has been front and center, and augmented analytics is definitely still a factor.

Originally, [technology] was trying to augment the analyst persona, and now it's trying to better augment the decision-maker, the frontline worker. It's about contextualizing [data], with augmenting being machine learning/AI-enabled functionality like natural language query, natural language generation and automated insights. From a forward-looking perspective, we're looking to see how vendors shift from just augmenting the analyst persona to how they're focused on the analytics consumer. One thing that rose to the top was ecosystems, whether it's an application ecosystem, a personal productivity suite or just a broader [end-to-end] data and analytics ecosystem. That was absolutely one of the key considerations this year.

Augmented analytics and having an ecosystem are really important: ecosystem from a buying perspective, and augmented analytics from a capabilities perspective.

For the second straight year, Microsoft, Salesforce (Tableau) and Qlik were the only three earning the top designation of Leader -- what separates those three vendors from the rest?

Augmented analytics and having an ecosystem are really important: ecosystem from a buying perspective, and augmented analytics from a capabilities perspective.
Austin KronzDirector analyst, Gartner

Kronz: It goes back to that ability to execute and vision.

Microsoft continues to not only be present in a very high percentage of conversations [with clients] because of how it's part of Office 365 but also because of its price/value. It definitely benefits from the ecosystem it's part of. Tableau has been the gold standard for data visualizations and visual data discovery, which is the bread and butter of analytics and BI platforms. It also has a ton of customer traction and is now benefiting from the Salesforce ecosystem and pulling in a lot of different capabilities from Salesforce. They have a lot of presence still from the initial disruption that was visual data discovery. We've said for the past two years that visual data discovery is an expected feature set now, but when anyone is looking at an analytics and BI tool, Tableau is still in conversations.

Among the three Leaders, Microsoft is off on its own, rating higher in both ability to execute and completeness of vision -- what characteristics separate Power BI from rest of the field?

Kronz: They're in a lot of conversations because of the ecosystem they're part of, but they're also not playing catch-up when it comes to analytics functionality. They're pulling from different parts of the Microsoft Azure environment, whether that's machine learning capabilities or the ability to embed analytics. Not only is it a present product in the Microsoft ecosystem, but, functionally speaking, it's rich in capabilities.

With platforms like Power BI, Looker, QuickSight and Tableau -- part of giant corporations that come with built-in ecosystems -- are independent analytics vendors at a disadvantage when it comes to being part of a larger whole?

Kronz: I've been emphasizing the importance of an ecosystem, but there are still a lot of independent analytics vendors that are in the Magic Quadrant, and an important part of their story is that they can deploy anywhere and connect anywhere. That's a powerful message to tell customers that they have flexibility to deploy where they need to. There's still value in being agnostic.

Were there any vendors that made significant gains in terms of their completeness of vision and ability to execute?

Kronz: It's a very mature and crowded market. To be among the 20 vendors that make up a Magic Quadrant is challenge in and of itself. There are hundreds of vendors out there that are doing analytics and BI. So, one thing you'll notice is that this year's Magic Quadrant is pretty similar to prior years in terms of the positioning of vendors. I think everyone has started to lean into the augmented analytics story, and they have some kind of ecosystem. There wasn't any one vendor that made a meteoric rise or fall. It's a pretty mature space.

Maybe the storyline is that there were a few new vendors.

Let's touch on those -- what made Incorta, Tellius and Zoho worthy of inclusion this year?

Kronz: We have inclusion criteria that is based on market fit and a series of momentum metrics like how often they come up in conversation with Gartner analysts and search data. We try to use a blend of internal and external information to figure out the 20 vendors to include. They're three vendors that met the inclusion criteria, but they're three vendors doing slightly different things from one another.

At a high level, Tellius comes in based on its augmented analytics and data science. Zoho has a lot of different applications that it offers, so it hits on the analytics ecosystem trend, and Incorta offers those end-to-end capabilities within one tool. Each of them, in their own right, have elements of where we see the market going.

Is there anyone on the rise that maybe fell below the threshold for inclusion but might break through in the next few years?

Kronz: There are definitely a lot of startups in the analytics space that we track. It's really challenging to enter into the analytics and BI market and grow to the level of the vendors that are currently included in the Magic Quadrant. The reason is that as a lot of the established vendors move to the cloud, there is so much consistent improvement and not a lot of meteoric shifting.

A vendor used to be able to come into a space and be able to differentiate itself for a number of years, but as cloud becomes the backbone for a lot of platforms, innovation cycles are so much faster. Three years of differentiation is now three months, at best, before someone else copies the innovation and comes along with something similar. That makes it really challenging for startups. If you're a large company that has the ability to invest in your own product and innovate, you can do it a lot faster now.

While perhaps not on the verge of challenging tech giants like AWS, Google, Microsoft and Oracle -- or even established independent vendors like MicroStrategy and Sisense -- what are you seeing from startups that you find interesting?

Kronz: As far as trends we're seeing from startups, there's a lot of augmentation. I definitely think that's where the product side of BI and analytics will continue to evolve. But there needs to be some sort of specialization as well from startups in order to stand out. From a lot of them, I see one of three things happening: some vendors do augmented analytics for a particular domain like supply chains or marketing; others do augmented analytics, but their specialization is outlier detection; and others are very specifically an analytics chatbot. They can still do other things -- develop dashboards, build visuals -- but in the startup environment there's a hyperfocus that's a necessity.

If a startup enters the space today and just says they do analytics, Microsoft, Tableau, Qlik, Sisense and any of the other vendors in the Magic Quadrant already have that space occupied.

Are there trends bubbling below the surface that a year or two from now might become part of the criteria as you examine and rate analytics vendors?

Kronz: It's getting harder and harder to say what's going to happen three years from now, but I think there will be an emphasis on interoperability.

As few as four years ago, we would get questions about Power BI versus Tableau, or any two vendors. Now, we get a lot of questions about how Google Cloud and Azure do analytics, and that points to how users' cloud provider or application provider of choice works with the rest of your data ecosystem. That's going to influence buying decisions when it comes to analytics and BI tools. That's why we see a lot of vendors talking about interoperability. Even if they're associated with a particular cloud, they're being very clear that they're completely cloud agnostic when it comes to data connectivity.

Going forward, the ecosystem will be front and center. Augmentation is here to stay, and there's definitely going to be a lot more of that. Optimization will also be important. There will be a lot more direct query where, as databases move to the cloud, the BI tool live-connects to the database and leaves the data where it is.

Editor's note: This Q&A has been edited for clarity and conciseness.

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