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Qlik software is in a strong position among BI tools, but that doesn't mean its namesake vendor faces no challenges. In Gartner's 2018 "Magic Quadrant for Analytics and Business Intelligence Platforms" report, the analyst firm again named Qlik as one of three market leaders, but said it was a "distant third" among BI vendors on client-interest metrics during 2017, falling from its traditional place in the top two positions. Gartner also cited self-service analytics complexities and software migration issues as hurdles for Qlik.
In part two of our interview with Mike Capone, Qlik CEO, the newest member of the Qlik leadership team lays out his plan for rejuvenating the company's software offerings and reinforcing its position of prominence in the BI market. Capone sees several emerging technologies presenting big opportunities for the self-service BI and data visualization company.
What areas of the Qlik software do you need to work on?
Mike Capone: Continuing our push into the cloud. We have a product today, but we're going to continue to invest there, and we're going to continue to invest into the partner ecosystem.
The thing that I'm most excited about is what we call hybrid. Today, customers are forced into pure cloud or pure on premises. With our hybrid offering, we give customers a choice. You can run it on our cloud, you can run it in your own data center or you can do both, which is totally unique in the marketplace today.
That allows customers to do business with us the way they want to. If they want to get to the cloud, but they need time doing that, we can help them do that. Think about a world where wherever your data is, you'll be able to access it with our toolkit. That's what we're solving for.
How do you, Mike Capone, Qlik CEO, view your position against your competitors? A lot of people, when they think self-service analytics and visualization, think of Tableau first. Do you have plans to make up that ground?
Capone: Tableau -- certainly their strength is it's easy to use and quick to stand up. With our Qlik Sense product, we've closed that gap. If you talk to people who use Tableau but also Qlik Sense, they would say our latest versions are very competitive. And we feel that we've kept our market leadership in the enterprise class. That still is our big differentiator. And the Associative Engine is something that's our bread and butter.
Tableau just announced its new Hyper data engine. The Associative Engine was always one of the main selling points of Qlik software, so do you view Hyper as a threat to your core value proposition?
Capone: I'd be crazy as a CEO not to be keeping an eye on it. It was an announcement, and we'll see what happens from here. We've got a big lead; it's new to the market. We're going to continue to invest in our product, and our goal will be to continue to keep space between us and them. It's clear that that announcement was a response to what we do. In many ways, our Qlik Sense product was a response to getting to the more casual, self-sufficient users that Tableau traditionally has had.
Do you plan to continue developing Qlik Sense and QlikView indefinitely?
Capone: There's no plan to sunset QlikView. We love those customers; we're very loyal to them. Over time, you're going to see Qlik Sense evolve and become more feature rich. [But] there is a public letter to all of our QlikView customers saying that that product is not going to be end-of-lifed.
Why keep both of them?
Capone: We like to do business with customers the way they want to do business with us. I never want to be the type of software company that says, 'You have to move off this product or we're cutting you off.' I know that's a practice some software companies do because they don't want to spend money supporting a product.
The reality is we have a very loyal QlikView base who have been around for a while. Over time, they'll migrate toward Qlik Sense, and with our cloud strategy, we'll create ways for them to preserve things they built in QlikView. So there's really no reason for us to ever want to jam those customers.
There are some companies that don't have the wherewithal right now to migrate, and we're going to continue to hug them. They pay us maintenance; they should get something for their maintenance payments. I was a CIO for a long time, and I know the vendors that come at you and say, 'We don't care if you pay us maintenance, this product is end-of-lifed.' And that usually puts the deal on the street.
It doesn't seem like a lot of users migrate from QlikView to Qlik Sense, and if they do move, it might open up the possibility of looking at different platforms. What are you doing to keep them from moving to a rival platform, while also encouraging migrations to Qlik Sense?
Capone: We've got a large number of users who have both. That said, as we've added functionality to Qlik Sense, we are starting to see the same users on both platforms, and we're seeing people quiesce their QlikView development but keep running the apps, and then do all their new development in Qlik Sense. We're investing in our customer success organization, and as part of that, we're going to continue to give all of the Qlik customers a good experience.
So the customer success initiative is all about helping users understand what product is right for them and if they're using it optimally?
Capone: I think the organization has been very clear on what the benefits of both products are. We'll engage customers the way they want to be engaged. If they're happy in QlikView, that's fine. If they want to move their apps to Qlik Sense, we'll help them do that.
It sounds like you're going after the self-service customers who can easily access data through your application. Is that your target market, or are you looking to get more data scientists?
Capone: We want it all; we're not shy about that. We have the small business covered -- that is, people who want to build apps and use the tool. We've got the enterprise-space users who want to do it themselves.
For data scientists, there are two approaches. We have APIs to R and SAS so people can build routines. If you really want a hardcore statistical function, we wouldn't build that -- we would just build an API to R or SAS and let them do that. It covers the real sophisticated data science use cases.
But then we are building more cognitive algorithmic capability into our platform as well, and those would be things that are proprietary to us. Things like how do you make associations beyond our engine today and make suggestions? Those are the types of things we're building.
So you do see room to improve the Qlik software products?
Mike CaponeCEO, Qlik
Capone: There's always room to do enhancements. With IoT [internet of things] and the data sets that are coming out there, and the ability to start to manage large data sets and build algorithms around them, I think it's huge. And I think we're just scratching the surface in terms of what's going to happen with data.
The enhancements I'm talking about, being able to scale massively, taking advantage of Linux containers inside of AWS, they're not deficiencies in the product today, but it's going to get us ready to catch this next wave in analytics. It's going to be crazy. The amount of data we're capturing, there are things that we don't know today that we're going to discover because we start looking at data differently.
What's on the roadmap that people should be excited about?
Capone: The three major things: hybrid cloud, cognitive capabilities that start steering you toward the types of visualization you want and what you should do next, and the Big Data Index. That's the ability to handle massively large data sets in a seamless way. If you've captured data somewhere, you don't want to have to move that data somewhere else. So the ability to use our Big Data Index to get that data, build metadata around it and use our tools on it in place is what's coming.
Some industry analysts say the tools of today's BI leaders don't necessarily translate to the big data world. What's your take on that? Do the tools translate, or do you have to translate them?
Capone: We are building capabilities that I think will start to translate. We don't have a closed architecture, and we have interesting partnerships with [big data platform vendors] Hortonworks and Cloudera so you can use our product in conjunction with another technology that might be able to handle big data sets different if that's your choice.
There'll never be one size fits all to these problems. We want to be able to get you the outcome, and we do think there will be use cases where you have a really large data set and you can use Qlik to go out and get it.