Augmented Analytics

Following closely on the heels of self-service business intelligence is the next disruptor in data and analytics called Augmented Analytics. It marks an evolutionary shift in the field of data and analytics where human intelligence is supported and supplemented with insights that are automated using machine learning and natural language.

What is Augmented Analytics?

While automated insight generation through data visualizations, visual analytics, clustering, forecasting, dashboards, etc is not a new concept, the rise of natural language generation, machine learning, progress in augmented reality and artificial intelligence have paved the way for a new level of automation in insight generation.  Augmented analytics just takes it to the next level by delving deeper and applying automation to deliver insights at unparalleled speed.

Augmented Analytics vs Analytics

Not just data insights, the entire process of preparing, cleansing, sharing the data is automated. With automation, feature engineering is applied on this profiled data to scan for hidden patterns and crucial insights. While traditional analytical tools investigate millions of variable combinations at moderate speeds, automation speeds up this process often throwing up new insights. The results are then interpreted using artificial intelligence algorithms to offer objective, unbiased alternatives and recommendations on how the insights can be best utilized to drive positive outcome.

However, that is not to say that augmented analytics will replace data science, enterprise, and self-service BI, if anything, it complements the existing BI landscape and can be integrated with business applications to improve business performance.

Three key benefits of Augmented Analytics

According to Gartner, in its report called “Augmented Analytics is the Future of Data and Analytics,” augmented analytics is expected to grow at a tremendous rate. Early users are already gushing eloquent about its unprecedented speed, competitive advantage and access to sophisticated data tools for confident decision-making and improved productivity. Augmented analytics presents unbiased, actionable, accurate insights from data. Three of the key benefits are:

  1. Businesses can focus on ROI and TCO due to advances in smart data discovery, sophisticated data solutions and augmented analytics
  2. It lends greater confidence and accuracy to business forecasts, measurable analysis of offerings, financials and decision-making
  3. It drives data literacy and has a positive impact on user adoption, data integration techniques and social business intelligence
Conclusion

While there may be some initial resistance and skepticism as is usual with every disruptive market trend, it is hard to deny the obvious benefit of augmented analytics in increasing business value. Moreover when human intelligence is combined with augmented intelligence, it can deliver optimized outcomes without the baggage of skewed analysis.