Smarter Decision-Making Via Augmented Analytics

After many years and cycles of hype followed by diminished hopes, artificial intelligence (AI) and machine learning (ML) have started making real progress. Even so, these “smart” technologies are not magic bullets. At present, and for the foreseeable future, many AI-powered solutions are most useful and valuable when paired with human expertise, experience, and perspective in ways that deliver “augmented intelligence.”

That’s absolutely the case when it comes to analyzing and leveraging the vast amounts of business-relevant data now available to organizations. In fact, AI and ML aren’t just helping data scientists better analyze and exploit oceans of data—these technologies are making it easier for everyday workers to do the same.

The use of intelligent technologies to enhance and democratize data analysis is referred to as “augmented analytics.” Gartner has identified augmented analytics as one of the top trends driving the evolution of analytics and business intelligence. According to Gartner:

“[Augmented analytics] will deliver analysis to everyone in an organization in less     time, with less of a requirement for skilled users, and with less interpretive bias than current manual approaches. As the technology develops, there will be more citizen data scientists.”

Furthermore, augmented analytics is not a pie-in-the-sky or distant prospect. AI-powered data analysis tools and services are available today—and gaining rapid adoption. In fact, Gartner predicts that in 2020 “citizen data scientists will surpass data scientists in the amount of advanced analysis they produce, largely due to the automation of data science tasks.”

Helping Overcome Data Literacy Issues

One of the most important benefits of AI-enabled tools is helping companies overcome their data literacy problems. Many employees remain uncomfortable working with data, and studies show that that aversion can cause procrastination, stress, and lost productivity.

To see how AI and ML can help tackle this problem, consider conversational analytics provided through products such as Qlik Insight Bot™. This tool leverages natural-language understanding and other AI technologies to deliver a conversational analytics experience. When using this, employees can simply ask questions of their data and get immediate answers, with no data analysis expertise required.

Beyond simplifying data interactions and analysis, AI and ML are augmenting additional data management activities. AI-enabled tools, for example, can: help organizations identify information that may be worth collecting and analyzing, spot anomalies within data sets, and automate the cleaning and transformation of data.

In these and other ways, AI and ML are quickly becoming central players in the world of data management and analytics. By both augmenting and democratizing data-driven tasks, these transformative technologies will help organizations extract maximum value from their growing volume of data.

For information about how Qlik delivers augmented intelligence and analytics– and how these and other solutions can help improve corporate data literacy – see here.