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Qlik exec discusses AI and its role in the future of BI
The next major trend in business intelligence will be the increasing impact of augmented intelligence and machine learning, Qlik's VP of product marketing Dan Potter says in a Q&A.
The future of BI is augmented intelligence and machine learning, and much of it will be in the cloud.
Vendors are already producing analytics products that feature voice recognition capabilities enabling users to vocalize a query and get their desired feedback, and many already have predictive analytics features built into their software.
Next-generation analytics platforms will feature even more of what's only just beginning.
The future of BI will be more conversational. Through AI and machine learning, it will feature tools that understand what a user wants before the user even asks for it, and it will feature platforms that don't merely tell the story of the past but, based on what's already happened, will also be able to deliver a reasonable idea of what will happen going forward.
Qlik, whose BI products are among the most popular data visualization tools on the market, aims to remain innovative as BI advances.
In this Q&A, Dan Potter, vice president of product marketing at Qlik, discusses the future of BI and how Qlik plans to meet the needs of users in the next phase of the analytics revolution.
He also discusses the data management and data cataloging capabilities Qlik now possesses due to its acquisitions of Attunity and Podium Data over the past 14 months.
Potter joined Qlik as part of the acquisition of Attunity.
As you look ahead, what do you see as the future of BI?
Dan Potter: There's definitely a lot of momentum around artificial intelligence and machine learning and how to help augment the intelligence of data consumers – how do we help them wade through the ever-increasing volumes of data and the velocity in which that data is moving and help to surface insights faster without having to be a data scientist? How do we get smarter? We call it augmented intelligence.
This is all about using the power of this vast amount of compute that we have, especially now in the cloud, and bringing that vast amount of data that's available to help surface insights in a more automated way in order to increase data literacy throughout the organization. The real goal here is making an organization smarter by using the right data to make better decisions faster -- that's what data literacy is all about.
What is Qlik's roadmap as BI continues to evolve?
Potter: Qlik's strategy is to provide an end-to-end platform -- really the only independent end-to-end platform that spans enterprise data from how to get the data, get it analytics-ready, catalog and govern that data and make it available to business users and provide the analytics visualization in a way that really helps through augmented intelligence to surface those insights much faster.
Qlik's strategy is to be independent of the cloud platform providers and be completely agnostic about where the data lives, how it's being managed, where it's being managed, how it's being processed and how it's being consumed. People are looking for an independent data strategy that can be delivered not just to one cloud but to multiple clouds, and not just consumed by one tool but consumed by anything they need to.
What about with respect to technological innovation?
Potter: On the analytics and visualization side, it's about how Qlik can help business users surface insights very quickly. There's no longer just a business analyst sitting at a tool and looking for insights, so it's now about pushing insights, embedding insights into applications -- it's the notion of analytics everywhere. Responding to the way that analytics are going to be requested and consumed is changing dramatically. Bot technology and natural language technologies can empower business users to ask queries in natural language or right within tools like Skype.
A sales rep can to go to an account, ask everything this account has purchased, whether they're happy customers and what the forecast looks like for this customer. To be able to do that with their mobile phone five minutes before a meeting and surface important insights is an example of the kinds of non-traditional analytics applications that are about being everywhere, being pervasive and opening up the avenues for business users to be pushed analytics and to make queries in ways that are more natural to them.
Now that it's been about seven months since Attunity was acquired, what data management capabilities have the acquisition brought to Qlik?
Potter: The Attunity value proposition is to be able to unlock data from core enterprise transactional systems, make it available in real-time where it's needed and make it analytics-ready without any scripting. We unlock data and we move that data in real time so that as transactions occur on big mainframe systems we send the changes in real time over the network so that the data is constantly being updated. We move it into data lakes and data warehouses where we automate the creation and management of those structures so people can query real-time data directly where and when they need it. Contrast that to how data has been integrated and managed over the last 20 years when there would be teams of people writing scripts and moving the data -- it was time-consuming, very expensive. … Attunity can automate what used to be scripting, so if you want to add new sources and new data you can do it with a couple of mouse clicks and not wait months, or even years.
And what about Podium Data in the summer of 2018 -- what new capabilities did that bring to Qlik?
Potter: What Qlik acquired with Podium is a business-ready data catalog. Data cataloging is very interesting right now – a recent research report from Gartner said that organizations that have a curating catalog of data will realize twice the business value from that data in their analytics investment. There's a huge emphasis right now as organizations are understanding that data is strategic to them, but they still need to present the data to business users so they can find it and have trust in it – understand where it came from and when, how it was manipulated, and who else uses this data. All of that gets exposed through a powerful catalog.
But a catalog also does the other side, which is the governance. From an IT perspective, it's making sure that the data provided to business users has an access control, it's secure, it's in compliance with regulatory issues, and personally identifiable information is masked. With Qlik Data Catalyst and the catalog that came from Podium, the needs of both sides are met -- the governance and control of IT, and for the business user, an application where they can shop for data much like they shop for products on Amazon.
Are there any more features along that line of progression from data collection through insight that Qlik is looking to add?
Potter: There are lot of interesting things that we're doing organically around AI and machine learning. That's a big part of the emphasis for us. You see that from the data side -- applying more cognitive capabilities, continuing to automate the shaping of that data, surfacing data to business users based on AI and machine learning, understanding the user of the data and the relationships that they and others have to that data.
That's really the emphasis from a development perspective.
Editor's note: This interview has been edited for clarity and conciseness.
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