Augmented Analytics to Recast Big Data to Smart Data for Improved Insights

by March 17, 2019

As the industry is realizing the growing importance of data, more and more data processing tools and next-generation technologies are coming out in the spotlight. Meanwhile, data analytics is also gaining much fame. Organizations, in order to thrive in the industry, need to adopt new data analytics innovations such as augmented analytics.

Recently, a market research company Frost and Sullivan discovered that augmented analytics being an advanced data processing tool is able to derive the real essence of insights from Big Data and push it towards Smart Data market summing up to $31.5 billion by 2022.

Basically, the tool automates the data-centric insights and facilitates with the refined information. This filtration of data at most saturated level is not possible using traditional analytics tools. Reportedly, Datameer, Xcalar, Incorta, and Bottlenose are already zooming into the development of end-to-end smart data analytics solutions. Such smart data solutions are designed to achieve valuable insights from Big Data.

Naga Avinash, Research Analyst, TechVision said – “Markets such as the US, the UK, India, and Dubai have rolled out several initiatives to use Artificial Intelligence (AI) and machine learning-powered data analytics tools to generate actionable insights from open data. Smart Data will help businesses reduce the risk of data loss and improve a range of activities such as operations, product development, predictive maintenance, customer experience, and innovation.”

It was depicted in the recent analysis brought to the table by Frost and Sullivan namely “Turning Big Data to Smart Data, that, Opportunities surfacing, key highlights of market developments and technologies are the key factors for converting big data into smart data, government-run programs and organizations employing data analytics. The report also shows the viewpoints of industry analyst and use cases on smart data.

Further, Naga Avinash added – “The evolution of advanced data analytics tools and self-service analytics endows business users instead of just data scientists with the ability to conduct analyses. Technology developers can ensure much wider adoption of their solutions by offering in-built security mechanisms that can block attackers in real time. They could also develop new business models such as shared data economy and even sell data-based products or utilities.”