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.
The world of business analytics has changed dramatically in the past few years. If your business is looking to upgrade BI tools or to begin implementing an analytics solution, the solution must be user friendly for business users. The tools exist today for augmented analytics, augmented data discovery, self-serve data preparation and other features and modules that provide sophisticated functionality and algorithms in an easy-to-use dashboard and environment that is designed to support business users, as well as data scientists and IT staff.
Have you ever noticed that when you give someone something, they often want more? This is especially true when they really like what you gave them! As the concept of business analytics becomes more main stream and business users embrace the possibilities, they (and their managers) want and expect even more tools and more potential. They want better solutions. BUT, don’t make the mistake of interpreting the need for more sophistication and detail as a need for more complexity. Business users are still business users and, as organizations pursue the natural progression of business analytics, the emergence of Advanced Data Discovery enables those same business users to enjoy the benefits of more sophistication, more possibilities and more data sharing without the need for IT staff or data scientist involvement.
ElegantJ BI, an innovative vendor in Business Intelligence and Augmented Analytics, is pleased to announce that ElegantJ BI is named as Representative Vendors in the Gartner ‘Market Guide for Traditional Enterprise Reporting Platforms‘ report published September 28, 2017.
Oh, the confusion of advanced analytical terminology. Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Add to that, the sophisticated concepts of auto-suggest, auto-recommend, time series forecasting, causation and prediction and classification techniques and you may feel that you need a degree in data science to do your job.
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.
