Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we look at the rise of augmented analytics and how it tackles the ever growing need for intelligent, data-driven insights.
Picture this: Your department head asks you to perform in-depth analysis on consumer subscription data from the past two quarters, and you find that there’s been an inexplicable decrease in the number of subscribers from the West Coast of the U.S. Wouldn’t it be great if you had a tool that could compile data from disparate sources, take all possible factors into account, including those that are often overlooked, and tell you the cause of the decrease and how to address it?
Enter augmented analytics. Gartner defines augmented analytics as “an approach that automates insights using machine learning and natural-language generation,” and claims that it “marks the next wave of disruption in the data and analytics market.”
Business intelligence (BI) and analytics tools have evolved in stages over the past decade. Traditional, first-stage BI tools require the skills of a data scientist to make meaning out of otherwise indecipherable data. Second-stage BI tools can be readily used by end users who don’t need advanced technical skills. Now, third-stage, augmented analytics tools incorporate AI and machine learning to further simplify and automate analysis.
As organizations become more data-centric, the need for easy-to-use, intelligent analytics tools is paramount. Augmented analytics enhances the speed, capability, and accuracy of the process. It employs machine learning to provide contextual awareness across the entire data analytics workflow. Algorithms look for patterns, or they focus on otherwise overlooked factors. Further, natural language processing enables BI and analytics tools to present insights and visualizations in a clear, understandable format.
With augmented analytics, end users can interact directly with analytics solutions by asking questions and receiving instant answers. Further, analysts won’t have to work on repetitive, manual tasks and can take up more critical projects. To understand the advantages of augmented analytics better, let’s take a look at five interesting articles from across the internet.
What You Need to Know About Augmented Analytics: The real strength of augmented analytics lies in its ability to provide relevant insights. It takes into account a number of factors that traditional analytics tools usually ignore, such as the user’s role and group, and what the user has searched for in the past.
Augmented analytics: The future of data and analytics: With the deluge of data increasing by the day, augmented analytics marks the next wave of disruption in the BI space. Augmented analytics solutions will slowly build their way into enterprises as organizations strive to empower employees during digital transformation.
Will Augmented Analytics Be The Future Of Data Revolution? Though the growth of augmented analytics is still in its early stages, many industry use cases are already available. From healthcare to smart cities, the possibilities of this disruptive technology are endless.
How Can Augmented Analytics Benefit Your Role? One of the most interesting facets of augmented analytics is that it can benefit a host of employees in an organization. From data scientists and analysts to marketing and sales folks, everyone can benefit from this next wave of data and analytics.
Is Augmented Analytics A Threat To Business Intelligence? Augmented analytics will definitely change how data analysis is conducted in organizations today. However, rather than a threat, augmented analytics stands to complement existing BI solutions as it brings in the added capabilities of machine learning, automation, and natural language processing (NLP).
A survey reports that 70 percent of business leaders use some form of data analytics to drive business decisions. With the implementation of augmented analytics spanning innumerable industries and roles, it’s only a matter of time before we start seeing full-scale adoption of this new trend on the block.