Gartner (2017) was the first to introduce the concept of Augmented Analytics; A notion that goes hand in hand with Big Data Analytics which consists of examining, sorting, processing and transforming massive amount of raw data in an effective way. This process will not only extract value and meaningful insights from those data, but mainly improve their performance.
In other words, Augmented Analytics through the use of machine learning (ML) and artificial intelligence (AI) algorithms makes the data scientists’ role more efficient by automating it.
This therefore makes it possible to improve data governance and accuracy and promote its democratization by making it accessible by all, and before all else non-technical people.
Why is Augmented Analytics the future of Business Artificial Intelligence ?
As a result of its process acceleration, Augmented Analytics provides a key competitive edge in today’s fast moving market.
With the use of Augmented Analytics running through advanced automated features, many businesses including small, medium and large institutions will use data efficiently. This will facilitate the identification of valuable insight, discover more information and point out possible changes in the business which will allow for immediate decision-making without the involvement of a data scientist.
Moreover, Augmented Analytics allows the outcome of the study to be communicated through a simple report using written language, understandable by everyone.
This simplifies and speeds up the interpretation and the transmission of the analysis to the team members by removing the previously indispensable third party: the data scientist; essential to the analysis and understanding of the data.
The not-so-good news concerns all data analysts, who before the emergence of Augmented Analytics were very much in demand yet rarely available.
By 2024, the American market only will experience a shortage of approximately 250,000 data scientists (McKinsey Global Institute, 2021).
In fact their role will be partially replaced by Artificial Intelligence but to a certain extent.
With the use of Augmented Analytics, data scientists will no longer be bound to the mechanical and time-consuming process of collecting, cleaning and analyzing data. They will also no longer need to review the research outcome, and then communicate the right approach required to improve revenue to the rest of the company.
By taking a part of their work load, Augmented Analytics will also allow the IT community to take the analysis to another level and focus on more tactical and creative matters.
Data scientists will now identify new ways of collecting more precise and relevant data, thus continuously speeding and improving the overall process and decision-making. Their role will also consist of establishing more accurate business forecasts, be able to give a more strategic interpretation on the insights, provide a quantitative review of price estimation, as well as product and service proposition.
Organizations are spending tons of their budget to harness the data collected to keep up on a market that is continuously changing.
Knowing that data moves the world, and is extremely valuable, Augmented Analytics opens up innovative ways of exploring and interpreting them.
Augmented Analytics will forecast emerging business trends and anomalies, create projections and make prediction to develop more effective strategies all while creating additional value for customers which will allow companies to act faster, invest wiser and be ahead of competitors.
At Leogrid, we strongly believe that decisions and improvements should be DATA driven nowadays. It is clear that Augmented Analytics is the future of Business Artificial Intelligence for the time being barring that it is necessary for companies to stay up to date, as cutting edge technologies are emerging at a very fast pace in order for them to be one step ahead of competition.
Examples of why different industry use Augmented Analytics
- Retailers use it to forecast inventory requirements or design store layouts
- Airlines use it to set ticket prices
- Hospitality firms use it to predict guest numbers