Insight by Qlik

Rev up cloud data analytics using software as a service

Agencies benefit when they move their applications to commercial clouds. If nothing else, agencies free themselves from the effort and cost of hardware planning, acquisition and maintenance. But remote hosting doesn’t absolve federal IT staffs from the burden of patching and updating applications. Those tasks remain regardless of where an application resides.

Andrew Churchill, vice president for federal at Qlik, says even greater benefits accrue when agencies move software as a service...

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Agencies benefit when they move their applications to commercial clouds. If nothing else, agencies free themselves from the effort and cost of hardware planning, acquisition and maintenance. But remote hosting doesn’t absolve federal IT staffs from the burden of patching and updating applications. Those tasks remain regardless of where an application resides.

Andrew Churchill, vice president for federal at Qlik, says even greater benefits accrue when agencies move software as a service (SaaS) applications certified by the Federal Risk and Authorization Management Program (FedRAMP).

Speaking specifically of data analytics applications, the time and effort agencies must spend on maintenance means they can have less time available for analytics and strategic thinking, Churchill said during a session at Federal News Network’s Industry Exchange: Data.

With SaaS, “they’ve got this service, totally self-contained, managed by the vendor, allowing them to move resources that were doing security patching, upgrades and managing the system over to analytics work,” Churchill said.

Agencies often have two or three full-time employees just dedicated to managing a system, he said. By contrast, nearly all of the cybersecurity and other compliance controls are the vendor’s responsibility in SaaS, Churchill added.

How SaaS can ease integration

SaaS has other, if perhaps less obvious, benefits too, he said.

Chief among them is that SaaS apps are typically engineered in what he called an API-centric way. APIs, or application programming interfaces, let apps talk to one another and to data sources more easily, sparing agency programmers from having to hand code each integration task.

“Some of the challenges of performing integration come from the policy and controls that exist — for good reason — within that enterprise,” Churchill said.

But APIs to services with authority to operate (ATO) can be inherited by the resulting, new services, Churchill said, speeding deployments.

The ease of integration, he added, extends to other third-party, SaaS tools beyond an analytics platforms such as Qlik. Analytics might be interesting, but it’s more valuable when it results in actionable information, he said.

“Qlik itself, or any analytics vendor itself, is not going to be the method by which an agency then takes action,” Churchill said. “That is going to be a third-party tool.”

Therefore, beyond integrating applications, Churchill advised agencies to automate alerts or other analytic outputs that lead to action. Automation can extend to the action itself, using robotic process automation tools also integrated into the analytics.

“You can now run an analytic that says, ‘If x is between these two values, take this action’ and automate that process,” Churchill said. “You are now really taking out some of that need for a human.”

Using SaaS to consolidate data for analysis

By the same token, Qlik works to logically consolidate data that typically resides in multiple clouds and in legacy mainframe applications.

“Making sure that data is holistically available to applications, to analytics and to business processes is going to be a big challenge,” Churchill said. The implication is that agencies must tie their data strategies to their analytics needs and then acquire the technical services to support it all, he said.

He cited the Defense Department’s Advana, which stands for advancing analytics, as “probably one of the greatest success stories of an enterprise data strategy that you’ll find out there, both policy and technology.”

Churchill summed up the collaborative nature of working with data this way: “Data in general is a team sport. It’s not an IT function. It’s not a business function alone. It’s about building cross-functional teams that come together and tackle a problem at a time.”

To listen and watch other Industry Exchange: Data sessions, visit our event page.