Augmented Analytics and augmented data discovery is a form of advanced data discovery that automates data insight using machine learning and natural language generation. It automates data preparation and makes it easy for business users to enjoy data sharing.
There are so many new terms in the business intelligence and advanced analytics domain. So, what is augmented data discovery, and why is it important for your enterprise? Augmented Data Discovery (aka Smart Data Discovery), takes the enterprise beyond data monitoring and helps users discover the more subtle yet crucial factors that affect business success. It identifies hidden issues and patterns within the data so the organization can address challenges, capitalize on competitive and market advantages and plan for the future with more confidence. There are a couple of components to the augmented data discovery continuum.
The concept of Augmented Analytics may sound complicated (and it may, in fact, be a challenge for a software vendor to accomplish), but the new augmented data discovery tools are quite easy to use. Unlike the data discovery tools of old, business users do not need to look to the IT staff or data scientists to perform advanced data discovery.
Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist. Advanced Data Discovery ensures data democratization and can drastically reduce the time and cost of analysis and experimentation.
If your role in business demands that you stay abreast of changes in business analytics, you are probably familiar with the term Smart Data Discovery. You may also have read the recent Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics’, Published 27 July 2017, by Rita L. Sallam, Cindi Howson, and Carlie J. Idoine, highlighting the importance and benefits of augmented analytics, augmented data preparation and augmented data discovery.
Gartner recently released a paper on Augmented Analytics which is described as “An approach that automates insights using machine learning, and natural-language generation.”
So as a gyani disseminating free gyan on the internet, I have chosen to write a few words on this.
This blog post of mine is an extremely biased and opinionated post. This is because any attempt to be fair and unbiased would not be thought provoking. We believe in clickless analytics and path to that includes learning and responding, predicting and suggesting, warning and solving. So, some of the points in this article may sound contrary to these but are not.
