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Inside Qlik’s data management playbook

Qlik CEO Mike Capone talks up the company’s transition into a data management company, its traction in APAC and what it is doing to put data analytics into the hands of more workers

The acquisition of business intelligence and analytics software firms by technology giants in the past decade or so has cast a shadow on the future of standalone companies that develop tools to help enterprises make sense of heaps of data.

Yet, the interest in these companies by bigwigs such as Salesforce, which closed its $15.7bn acquisition of Tableau in August 2019, underscores the growing importance of data analytics tools as more companies warm to data-driven decision-making.

These tools, however, no longer just ingest data from data sources and serve up fancy data visualisations to help workers make sense of data. For one thing, those from Qlik now tout a slew of data management capabilities, from data curation and cataloguing, to tracking data lineage.

During his visit to Singapore, Mike Capone, CEO of Qlik, talks up the company’s transition to data management, its traction in the Asia-Pacific region and what it is doing to put data analytics into the hands of more workers.

Tell us more about Qlik’s traction in Asia-Pacific. Being here in Singapore, you obviously see a lot of potential for growth in this region, right?

Mike Capone: This is an incredibly strong part of the world where we have a strong presence. With our focus on data and analytics, we’re in the right place at the right time.

As you can probably tell, there’s no senior executive in the world who isn’t looking at data and analytics to make their company better. In the past couple of days, I’ve been meeting with government ministries, big banks and universities, so the interest is pervasive, not only in Singapore, but across Asia as well.

While Qlik is a pioneer in visual analytics, the world has changed a lot. Our vision now is not just visualising small sets of data but pulling together massive sets of data from disparate sources, curating it, and then leveraging analytics tools and machine learning to help users make sense of data. It’s a ground-breaking time for us and as you’ve probably seen, we’ve done some acquisitions over the past 18 months to augment our capabilities.

What are some of the hotspots for Qlik’s growth in the region?

Capone: Singapore is clearly one of the leading markets. Based on our data literacy study, Singapore is at the top of the list of countries when it comes to corporate use of data to make informed decisions.

Japan is another market where we see growth and have a strong presence. China is also up and coming – it might have started behind everybody, but it is catching up very quickly. There’s not a country in Asia where we’re not doing business, but those three are probably the hottest markets right now for us.

Can you talk about the adoption curve for data analytics here in Asia? Depending on the maturity of an enterprise, some might start with traditional business intelligence tools and build on them, while others might jump straight to tools like Qlik.

Capone: There are three waves to this. The first wave was IT driven reporting, which was what the likes of Cognos and BusinessObjects delivered. Those companies got acquired by bigger companies, and the innovation sort of trailed off there.

The next generation was more user-driven as companies sought to empower employees with data analytics tools. The problem, however, was that data was still locked up in operational systems, and IT was still involved in processing requests to get data out of those systems.

The most recent wave, which is what we’re seeing right now, is about unlocking all the data with newer tools such as change data capture technology, the data catalogue, as well as tools from companies that we partner with, such as Snowflake and Amazon, to democratise access to data. IT just becomes an enabler to get the data out and then empowering users with analytics tools to access data on their own.

That said, companies are still struggling to make sure their data is clean. We’ve been talking about this for the longest time and it’s still a problem today. Do you see that as an ongoing challenge?

Capone: Yes, that’s still a problem. There are lots of operational systems out there with multiple sources of data. They could be even be consumer platforms where the users like me and you are putting in information that is not always accurate.

My message to customers, which seems to resonate very well, is there’s no lock-in. We’re completely agnostic. We do business with you the way you want to do business with us
Mike Capone, Qlik

The good news is that the tools now enable much faster ways to clean data, check the veracity of data and secure the data. About a year and a half ago, we purchased a company called Podium Data that offers a technology that enables IT to set up data catalogues, and for users to ascertain if their data is accurate and clean. It’s almost self-policing, because people can highlight that a data source is missing certain fields, for example. This provides a continuous feedback loop on the data, something that didn’t exist before.

Is that part of a bigger plan to go deeper into the data management space?

Capone: That’s right. We spent $560m on the acquisition of Attunity, a data management company, so we've gone from just an analytics company to a full data platform, with data curation, data cataloguing and data lake management capabilities, along with machine learning and artificial intelligence (AI) on the other side.

Our platform now has a product called Replicate, which brings data out of operational systems in almost real-time. It captures changes so it's easy to manage without agents, so you don't slow down your operational systems.

Along with that, we have a product called Compose, which is a data lake management tool, giving you the ability to conform data models and create analytics-ready information for end-users.

Then, there’s the Catalyst data cataloguing tool I talked about, and Qlik Sense, our flagship product. The cool part on top of that is we did another acquisition called Insight Bot, basically an NLP (natural language processing) product that allows users to ask questions about the data in natural language and get not only answers, but also suggestions about what they should look at.

What you’ve described sounds like the perimeters of your data management strategy. Are you going one step further, into areas like disaster recovery and backup and recovery which some data management vendors do?

Capone: That won’t be us, at least in the short run. Though you’d never say never, it’s not part of our strategy right now. There are plenty of infrastructure providers who can do that type of work. Our differentiation is clearly in our ability to help make sense of data.

Let's talk about the competition. Do you think the sizeable investment on the part of Salesforce to acquire Tableau is an affirmation of the market you’re in? Do you think companies like yours would be able to deliver more value as part of a bigger platform, perhaps down the road?

Capone: I can only look back in history. I was a CIO for many years, and I was around during the transition of Cognos and Business Objects. That generation ultimately didn’t end well, with the innovation trailing off when that happened. I'm not going to speculate on what Salesforce is going to do with Tableau or what Google is looking to do with Looker.

What I will say though, is that the Tableau deal is an affirmation that we’re in a good space and I’m certainly very happy about it. And look, it’s a different approach. Those are big cloud platform players, and their strategy is going to be to get your data on their platform. That’s what they do. It’s their business strategy and it creates some stickiness. That's not our strategy though, so that creates differentiation for us.

If you look at what Google and Salesforce are doing, Qlik is the largest independent analytics vendor at scale at this point. Our strategy is your data is your data. We’re completely agnostic. We sit on top of Salesforce and GCP (Google Cloud Platform). We run on Amazon and Azure and in your datacentre. We also have our own cloud. My message to customers, which seems to resonate very well, is there’s no lock-in. We do business with you the way you want to do business with us.

You can leverage cloud and we fully embrace cloud. That said, we’ll do it at the pace you want to do it. Some companies are just not ready yet. Our customers can move at their own pace, which is very different from what the competitive set is preaching right now and that’s an advantage for us.

How does Qlik’s AI capabilities compare with the built-in AI capabilities that are increasingly being baked into business applications?

Capone: We take a very open approach to our technology. We have open APIs and great partnerships with companies like DataRobot. If you have a very bespoke AI application, or you want to write some R code or Python code, we can accommodate that. For sophisticated use cases where you've got very strong data science capabilities, you can continue with that.

What we bring is embedded AI and machine learning to help our users make sense of data. We call it our cognitive engine. For example, if you bring in two disparate data files, we will not only look for patterns in that data, but also suggest reasons why a certain pattern exists and lead users down a path.

I'm not going to name any names, but some companies may have oversold their AI capabilities. When we draw an inference from the data, we tell users why
Mike Capone, Qlik

Now, what’s different about us compared to some of the previously hyped technology? I'm not going to name any names, but some companies may have oversold their AI capabilities. When we draw an inference from the data, we tell users why.

On top of that is the NLP capability. You can start typing questions about the information, and it’ll give you answers and suggest some visualisations along with that. We call it augmented rather than artificial intelligence, because we’re trying to help our users make sense of the information rather than replace them.

How flexible is the Qlik platform in accommodating customisations that enterprises may want to make to address specific needs?

Capone: What we’ve tried to do, particularly now that we’re moving to more of a cloud architecture, is to make sure we can maintain and upgrade the software continuously. We don't have a lot of customers that want to customise the core engine of our product.

What we have is something called Qlik Branch, our developer platform that people can use to build extensions of our technology. The extensions are walled off so that when we do upgrades, they’ll still work. If you look at some of the Gartner reports, our developer friendliness is one of our key strengths. We have a community where developers exchange ideas and share code and we contribute to the open source community as well.

Are you seeing more internet of things (IoT) use cases, particularly streaming analytics performed on data collected from the edge of the network?

Capone: Yeah, we see that a lot. We work with a company called mesur.io, which instruments crops and soil around the crops to see how much water they need or if the crops are too dry. We also work with police forces to stream data from drones. The ability to do that in real-time at a high velocity is super important.

What is your infrastructure footprint like to support that kind of workloads? Do you ride on top of the cloud providers or do you have a combination of public cloud infrastructure and your own datacentres?

Capone: We use Amazon as our cloud hosting platform for our cloud product, but we generally we work with whatever the customer wants to work with. Usually, the sensor data is streamed into some data warehouse on Amazon or GCP, and then customers run our analytics on top of it to draw conclusions from the data.

To address data sovereignty and security concerns, we let our customers deploy our technology wherever they want. Our Data Catalyst product has a robust security model and sophisticated capabilities around data lineage, so customers will know who accessed the data and where it went. So, if a user is outside of a certain region that can access the data, he or she can’t see the data. As you know, data protection is an ever-changing landscape so all we can do is be flexible.

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