Is Augmented Analytics the Future of Data and Analytics?
When Gartner speaks, people listen. In July 2017, one of the most reputable research companies in the world proclaimed augmented analytics as “the future of data analytics.”
A lofty title for sure—but aside from the sweeping headline, a lot of people were left wondering, what the heck is augmented analytics, anyway?
At ThoughtSpot, we love data and – more importantly – ways to extract value out of data. Whether it’s augmented analytics or an all-in-one tool that encompasses the best of each, our sleeves are rolled up and constantly working to provide better solutions.
Let’s look at what augmented analytics is, how it can benefit companies and how it can be applied below.
What Is Augmented Analytics?
Gartner defines augmented analytics as, “an approach that automates insights using machine learning and natural-language generation,” before stating it “marks the next wave of disruption in the data and analytics market.”
Still with us? No!? No worries. That’s a rather abstract definition for most people to understand.
For a more contextual definition, let’s look at how augmented analytics can benefit companies.
How Can Augmented Analytics Benefit Companies?
Data analytics is obviously important, yet many companies can’t get their data initiatives off the ground, and it isn’t for a lack of trying.
So why is this?
It’s because data analytics is an extremely complicated process for companies to set-up and run. From integrating myriad data sources and cleansing them so they can be analyzed, to actually analyzing the data, developing insights and communicating those insights across an organization, there are a lot of steps to a successful analytics process.
So, instead of going through the steps above (and their various nuances), an organization can potentially go from data collection to actionable insights, meaning, instead of merely finding that customer subscriptions in the West region are down 5 percent over the last quarter, augmented analytics can tell you why and how to address the decline.
Gartner is spot-on; augmented analytics is the future of data and analytics and not only because it’ll allow more companies to run successful analytic operations; augmented analytics will save companies money, speed up decision-making, increase employee trust around data and allow companies to get a better ROI on the data professionals they do hire.
Companies using legacy analytics technologies are using considerable amounts of the data team’s time doing tedious tasks like report building and data cleansing. Augmented analytics can do it better, without requiring a large time investment from costly data hires.
Also consider that data professionals aren’t necessarily business experts. Just because they have the expertise of working with large amounts of raw data doesn’t mean they know how to look in a giant haystack for individual pieces of hay that’ll move the business forward. Augmented analytics, through the use of machine learning algorithms, can.
How Is Augmented Analytics Applied?
Augmented analytics is a young, developing technology, but solutions are emerging. For example, at ThoughtSpot, we’ve built a full-stack AI and search-driven data analytic platform that certainly would be classified as augmented analytics.
Using ThoughtSpot, any employee can search the platform with a question like they would in Google. Answers are instantly generated from the company’s entire database through interactive visualizations like charts, graphs and tables. There’s no need to put a report request into the data team. No need to wait for an answer for two weeks.
ThoughtSpot is continually learning and customizing its findings depending on each user, companies get the advantage of an all-in-one analytic platform that molds to fit each specific department, team and employee’s preference.
Augmented analytics is still in its early growth phase, but companies can realize its benefits now by leveraging the simple, smart, and enterprise-grade capabilities of ThoughtSpot.
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