Gartner Data & Analytics Summit in London ended yesterday, and before I’m wheels up and back to my home base in New York, I wanted to write a little something about the keynote I attended that highlighted a big theme of this year’s Summit.

By this point, it probably comes as no surprise that machine learning and artificial intelligence are all the rage in the analytics and BI space. It’s important to note, however, that these are not just buzzwords that will soon fade into the background. On top of this year’s Magic Quadrant, nothing proved this more than Rita Sallam’s keynote, “Augmented Analytics: Key Trends in Next Generation Analytics and BI Platforms You Need to Know.”

Why Augmented Analytics Now?

Rita began by pointing out that ten years ago we struggled to find even ten machine learning and artificial intelligence enabled business applications. However, she believes, and I agree, that in 10 years the opposite will be true – we will struggle to find applications that don’t use ML and AI.

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But why? Well, there are a couple of clear reasons. First, data is becoming more and more complex. There are now a growing number of variables to analyze and understand, which makes it harder – not to mention more time-consuming – to rely on human intuition to search for the answers.

Speaking of time-consuming, businesses are now demanding faster time to insight and don’t necessarily have extra time to wait to make critical decisions. Introducing ML and AI to the full stack of analytics can enable a speedier time to insight from the moment the data enters the system.

The Future is Full Stack Augmented Analytics

Imagine a world where your business operates in the following four steps:

  1. Data preparation is augmented by advanced algorithms that seamlessly integrate with data catalogs, suggest schemas and recommend meaningful data enrichments.
  2. Natural language querying and algorithms find relevant patterns in the data. Features and models are autoselected, and code is auto-generated.
  3. Insights are shared with business users in natural language via Amazon’s Alexa and chatbots; visualizations are supplemented and enhanced by natural language processing and generation.
  4. AI and ML boost prescriptive analytics inside your dashboards and recommend what you should do to meet your KPIs and move your business in the right direction.

Sounds pretty great, right? Well, it’s not that far off from becoming a reality. Augmented Data Science and Augmented Data Discovery will not only increase speed to insight, but they’ll also increase report accuracy and reduce bias. According to Rita and Gartner, “In 2021 AI augmentation will create 2.9 trillion dollars of business value and 6.2 billion hours of worker productivity.”

Those are some pretty huge numbers. So, if you haven’t started thinking about how to integrate next-generation analytics into your business, it’s probably time you start.

See you at next year’s Gartner Data and Analytics Summit in London!

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Former Sisenser Guy Levy-Yurista, PhD, is an executive leader and entrepreneur with over 24 years of experience in Fortune 500, startup, and venture capital environments.

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