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SaaS adoption, real-time BI among top analytics trends

More enterprises using SaaS and the need for data in real time are among the top trends in analytics, according to Dan Sommer, senior director and market intelligence lead at Qlik.

More SaaS and real-time data consumption are two key trends currently driving the evolution of analytics, and all the major market trends are in some way a result of the ongoing pandemic.

That was the message delivered by Dan Sommer, senior director and market intelligence lead at Qlik, in his take on the top 10 business intelligence and analytics trends at QlikWorld 2021, the vendor's virtual user conference.

COVID-19 was the catalyst for what Sommer called the great digital switch. Digital transformation was already underway, but the pandemic accelerated the need for digital technologies -- including analytics -- and what was expected to evolve over perhaps five years instead changed in just one.

"Digital transformation, with data and analytics a critical component, is no longer something that can be pushed out to a later date," Sommer said. "Companies need to address it. Some are doing it well and some are struggling, but every company needs to make the switch."

In fact, Sommer continued, they need to make two switches.

Dan Sommer, senior director and market intelligence lead at QlikDan Sommer

First, they need to position themselves to react amid ever-changing circumstances. That involves developing a modern data pipeline so data is up to date and available to make informed decisions.

But that's not enough. They also need to prepare for the next crisis -- which is inevitable -- and be ready to act whenever it arrives. Preacting, as Sommer called it, means identifying possibilities with scenario planning and what-if analysis. And it means amassing active intelligence that enables change in real time, rather than what he called passive intelligence.

Each of the major ongoing trends in analytics enable organizations to better react and preact, according to Sommer.

"Data and analytics are the raw materials for these two switches," he said.

Cloud-based analytics platforms, unlike on-premises analytics tools, enable organizations to tap into the latest innovations as they are developed and benefit from their capabilities. In particular, organizations can quickly adopt the augmented intelligence and machine learning capabilities they need to react quickly at a given moment and prepare for what may be coming.

SaaS analytics platforms, therefore, are becoming more popular.

SaaS platforms currently account for about 25% of the analytics tools currently in use, according to Sommer. By 2024, SaaS platforms will make up about 50% of the market, he predicted.

"For many businesses, the increased use of cloud providers and online services has been essential to keeping the lights on [during the pandemic]," Sommer said. "This has prompted companies to overcome the red tape surrounding SaaS and other as-a-service products. People also want to tap into the innovation happening in data and analytics, and that's happening first in the cloud."

Digital transformation, with data and analytics a critical component, is no longer something that can be pushed out to a later date. Companies need to address it. Some are doing it well and some are struggling, but every company needs to make the switch.
Dan SommerSenior director and market intelligence lead, Qlik

Just as organizations need to stay current with respect to their technology stacks, they need their data itself to be as current as possible.

Without real-time data, they're reacting to conditions that existed days or even months ago, and the current conditions could be completely different.

At the start of the pandemic, some supply chains were badly disrupted while the demand for other supplies suddenly spiked. Hospitals were struggling to provide patients and staff with proper personal protection equipment. Meanwhile, store shelves were bereft of toilet paper.

"This accentuates the need to be more prepared, to have up-to-date data that you can react and preact on more quickly," Sommer said.

With technologies such as Spark, Kafka and 5G, there's an attempt now to make business-ready data -- data that has been not only curated for analytic consumption but had logic and context applied to it -- available more quickly and subsequently delivered to the end point where it can be used to inform decisions.

"If we have that in place, that will be a big factor in helping enterprises preact," Sommer said.

In addition to enterprises using SaaS more and the need for real-time business intelligence, the remaining eight trends Sommer said are shaping the analytics market include:

  • the evolution of self-service BI to self-sufficient analytics via more intuitive software -- including insight delivery -- given that more people are working remotely and no longer able ask for help from someone sitting nearby;
  • mass consumption of shared data such as COVID-19 case information stored in data catalogs to enable collaboration;
  • a new look to advanced analytics that prepares for disruption by focusing in on outliers rather than ignoring them, introduces unexpected inputs and includes what-if analysis;
  • capturing and synthesizing alternative data such as automobile traffic data near hospitals and keyword searches by internet users in specific locations to identify potentially catastrophic occurrences such as the pandemic more quickly, or using satellite images to predict retail sales;
  • reengineering business processes to make analytics the priority with processes such as sales and marketing feeding analytics rather than analytics feeding business processes;
  • a recalibration of the public's acceptance level of surveillance and data security technologies after governments intruded more into citizens' private lives as a result of the pandemic, as well as a recalibration of what it means for enterprises to be competitors after vendors such as Google and Apple collaborated to build a contact-tracing application during the pandemic;
  • collaboration taking place earlier in the analytics chain given the inability to coalesce in person; and
  • a generational shift in analytics from passive to active intelligence resulting from each of the other trends.

"It's all about your ability to reposition yourself to create a new future," Sommer said. "The pace of change has been accelerating and we see disruptive anomalies becoming more common. In the short term, the switch from physical to digital operations is a matter of survival.

"In the long term," he continued, "switching from being a reactive to a preactive enterprise will become necessary to thrive."

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