It's all about augmented analytics, according to Gartner.
While once data visualization capabilities were a critical differentiator for business intelligence vendors, now vendors need to deliver the augmented intelligence and machine learning capabilities that enable ordinary business users or risk becoming irrelevant.
Gartner, a research and advisory firm founded in 1979 and based in Stamford, Conn., published its Magic Quadrant for Analytics and Business Intelligence Platforms on Feb. 15. The report, released annually in February, rates analytics vendors on their completeness of vision and ability to execute, then uses those two measures to place each vendor on a graph with completeness of vision representing the X axis and ability to execute the Y axis.
Each of the four resulting quadrants are named, with to the top right quadrant titled the Leaders Quadrant.
This year, Gartner rated just Microsoft, Tableau and Qlik strong enough in both completeness of vision and ability to execute to be ranked Leaders. Among the three, however, Microsoft's Power BI was rated best in both measures, and as a result stands on its own on the graph, far higher in the top right quadrant than even its closest competitors.
Recently, Rita Sallam, a distinguished VP analyst at Gartner, discussed the 2021 Magic Quadrant for Analytics and Business Intelligence Platforms.
In an interview, she explained how the criteria for ranking vendors has evolved over the past few years to emphasize augmented analytics capabilities and what separated Microsoft, Tableau and Qlik from the rest of the pack.
In addition, she spoke about one vendor -- AWS -- whose QuickSight platform is relatively new but has the potential to grab market share, as well as the challenges smaller vendors may face given how quickly the more established vendors now are able to react to new innovations and incorporate them into their own platforms.
When Gartner put together this year's Magic Quadrant, how did the criteria for rating analytics vendors evolve from last year?
Rita Sallam: Each year we tweak the criteria for the Magic Quadrant to be consistent with what we're seeing in the market. For the past couple of years, we've been seeing what we call augmented analytics -- which is essentially machine learning and AI-assisted insight generation to augment a less-skilled user, certainly an analyst as well but also an information consumer -- expanding across most of the BI/analytics vendors that we cover. Five, six or seven years ago, interactive visualization was the main differentiating feature along with data preparation. Now, we're seeing those capabilities become more commoditized with basically all the vendors doing dashboards and common types of charts, and they can do that on a broad range of data sources. Where the differentiation is now is around the extent to which these vendors are incorporating augmentation, using it not only in terms of insight generation but also data preparation. We're seeing differentiation in the extent to which vendors are incorporating natural language as a way to facilitate easier ad-hoc analysis, and along with automated insights as a way to explain findings to users with the goal of making it easier and easier for a broader range of people across the enterprise to benefit from insights they would otherwise have to rely on an analyst or a more skilled user to get for them.
Rita SallamDistinguished VP analyst, Gartner
How is Gartner seeing that manifest itself in terms of analytics capabilities?
Sallam: Over the past five years, we started to introduce this idea of augmented analytics in the Magic Quadrant, initially assessing those capabilities from a vision perspective. Now, you see that the critical capabilities that we highlight really do emphasize things like automated insights, natural language query and natural language generation. We also see, in combination with that, this idea of data storytelling. Increasingly, we're seeing automated data storytelling where it's a combination of automated insight generation, anomaly detection and natural language query and generation such that you're able to develop automated, dynamic data stories. We're even seeing more manual packaging of interactive visualizations with narration to make it more compelling and easier for information consumers to make sense of insights presented to them. We've obviously been talking about cloud for some time as a major criteria that we assess from a product perspective, and we've certainly seen an acceleration over the past year as a result of COVID-19 in organizations' intentions to move their analytics and BI into the cloud, as well as their data management.
Those are the key changes. We've been assessing those things for the past several years, but I think the emphasis really has shifted, in terms of differentiation from a product capability perspective, to what we're calling consumer-oriented experiences that help an information consumer become more important. Those vendors that have those capabilities are more differentiated. In the end, if people can't access insights and use them, the business impact from deploying any of these platforms is going to be lower.
Among individual vendors, what does Gartner see from Microsoft that has separated Power BI from the rest of the group of analytics platforms?
Sallam: It's a combination of things. The ability-to-execute axis measures things like market momentum, perceived differentiation, overall execution and customer experience in addition to the product itself. Microsoft has just been stellar in all of those areas. Also, Microsoft has really benefited from the global pandemic. I hate to say that any vendor has actually benefited [from the pandemic], but there have been winners and losers during this global disruption. We see that Microsoft continues to close feature gaps in Power BI. Microsoft, historically, has always competed on being good enough, but their 'good enough' is very close to the other best-of-breed products on the market. Microsoft is even introducing capabilities that leverage its broader Azure data management and data science/machine learning stack to create a really strong end-to-end workflow for companies that are okay buying into an Azure stack. They have very strong capabilities for going from data management to analytics and BI to data science/machine learning, all with capabilities that we've been talking about like natural language query and natural language generation.
And then, of course, you have price/value. In times of economic downturn, companies look to rationalize the tools they have and consolidate onto fewer tools, and price/value becomes a more important buying criteria, and Microsoft almost has reset the expectations of the market in terms of at least license pricing. They've become very attractive for companies that either own Power BI through Office 365 licenses or they have an enterprise license through Microsoft. In addition, as we see more and more people working remotely during the global pandemic, you see many organizations living in Teams, and Microsoft has made an accelerated effort to integrate Power BI with Teams. That's been another positive driver of increased momentum for Microsoft.
Regarding the other two Leaders, while Gartner doesn't have Tableau and Qlik as highly rated as Power BI, what separates first Tableau from the other analytics vendors in the Magic Quadrant?
Sallam: Tableau still is the gold standard for visual exploration. They still have a strong installed base of users who typically are quite attached to Tableau and are very enthusiastic about using Tableau. They are benefiting from a much more expanded Salesforce sales force, and they continue to enhance their data preparation capabilities and data management capabilities, which enhance the end-to-end set of capabilities that Tableau can offer. They still have one of the better analytics user experiences for analysts that want to do deep visual exploration, and even though those capabilities are becoming increasingly commoditized, I would say Tableau's still differentiate it. And usually, when we see [organizations' short lists of potential vendors], we see mostly Microsoft and Tableau, and then Qlik to a lesser extent. Tableau still is one of the major vendors that get considered most frequently. Its analytics user experience is perceived to be the gold standard; customers love it. Salesforce has expanded its market opportunity, and they continue to enhance the product and add some of these augmented features.
Versus Microsoft, though, it's still perceived to be premium-priced.
And what about Qlik?
Sallam: Qlik continues to have some significant differentiators around its associative engine, which has been core to the product since the very beginning. They've extended that with some AI augmentation, with natural language query. They offer very powerful context-aware insights, suggestions and augmented analysis. I think they've been very early with offering multi-cloud capabilities so can manage your Qlik deployment across multiple clouds. They're building and pushing their SaaS offering, which is a relatively new thing. We've seen them make some innovative acquisitions by acquiring a bot vendor, they've expanded into data management -- that's a key trend we've seen driven by some of the cloud vendors like Microsoft where you have this end-to-end workflow -- they made an interesting acquisition in a company called Blendr that will potentially allow them to extend their ability to build workflow into applications that can be built with Qlik. On the plus side, they continue to have a strong end-to-end product, flexible deployment, and of the things they've been a thought leader on is emphasizing data literacy and making investments in education as a way to help customers be successful with their data and analytics initiatives.
Some of the challenges are that it's hard for any vendor whose name isn't Microsoft or Tableau to get consideration in this market. A challenge for Qlik -- and most of the other vendors -- is to get even considered in this market where we're seeing the trend toward consolidation and price/value. And what doesn't help is that Qlik, relative to the resetting of the price/value expectation that Microsoft has set, is seen to be more expensive.
One analytics vendor which Gartner didn't include in last year's report but which this year made its debut as a niche player is AWS -- what is it about QuickSight that changed?
Sallam: QuickSight has been on the market since 2015, so it's not a new product, but similar to Microsoft, Amazon's endgame is to get more data and compute into AWS. They've been building out QuickSight since 2015, increasingly trying to close feature gaps, but importantly in this market that values price/value, they have a pricing model that is very compelling. It's on par, or potentially even less, than Microsoft. As more and more organizations potentially move their data into AWS, looking at QuickSight as a native AWS analytics solution, we just see them coming up more in consideration on short lists. There's lots of potential opportunity for them given those combination of things. Amazon has potential, but it still faces some challenges. One of them is that they are still missing some areas of core functionality, like data prep manageability, relative to certainly leaders and other competitors. They don't have the benefit of things like business application integration that a Microsoft has with Office 365 or even Looker might have with the Google Office Suite. But like Microsoft that is Azure-centric, QuickSight is AWS-centric, so for organizations that have standardized on AWS, we see them coming up for consideration much more than we have in the past.
They're also another vendor that has benefited from COVID, and that's why we see them on the Quadrant this year.
Who were some of the vendors who made the biggest positive gains in terms of their completeness of vision and ability to execute?
Sallam: Honestly, the vendor that made the biggest jump is Microsoft, as we've been discussing. That really is the one that has benefited the most from the macroeconomic conditions plus continued to execute in a stellar way in terms of current functionality and having a strong vision. Google, with Looker, continues to improve. They've added things like natural language query, and similar to Tableau, I think Looker is benefiting by being sold to Google Cloud Platform. They have a much bigger sales force than was available when Looker was a standalone company, and now that the acquisition has been closed that integration is starting to show benefits. They've had a net-positive benefit. And I think we've seen Domo really make a positive move. We've seen really strong improvement in the augmented capabilities within Domo, and we've seen them have some resilience even given the push toward price/value because customers really value the package of capabilities that they're offering and are willing to pay a premium for those capabilities.
Those have been some movers.
Are there any vendors who slid back and were rated significantly lower in 2021 than in 2020?
Sallam: We're seeing all the companies in the Magic Quadrant build out these augmented capabilities and continue to execute on interesting roadmaps to differing degrees, but most of them are facing significant headwinds and the price/value pressure we've been talking about in the wake of the global pandemic and at a time when the core functionality around basic visualization is increasingly commoditized. To really justify premium pricing requires some delivery of some pretty significant value.
Are there startup vendors Gartner did not include in this year's Magic Quadrant that have the potential to break through?
Sallam: This continues to be a really interesting space. There are a number of smaller vendors that are startups that aren't on the Magic Quadrant that maybe offer some interesting user experiences around dynamic data storytelling, and I think it will be interesting to see how smaller vendors like that are able to fare over the new two or three years given the tough environment. In the past, companies like Tableau and Qlik were able to go from being very small vendors and challenge the entire market, change the entire market and become big companies, but I think it's tougher for these smaller companies now. It will be interesting to see how innovation actually happens in this space. Does it come from smaller vendors that become big companies, or is it that these incumbent vendors that are going to be fast followers of innovation, which is what we've seen with them not sitting on their laurels but seeing the disruptions and quickly onboard those innovations? That tends to suppress the ability for these smaller vendors to get big.
It will be really interesting to see how innovation continues to manifest itself, and who drives it. I think it's still coming from smaller vendors, but who actually wins is an open question, and that's why it's such an exciting market to continue to follow.
Editor's note: This Q&A has been edited for clarity and conciseness.