‘Automated Data Science’ to offer a competitive edge to enterprises
(Authored by Srinivasan Rengarajan, VP & Global Head – Data Science and Analytics, 3i Infotech)
According to a recent Indian jobs study, data science is one of the topmost and fastest growing field in India and its relevance is increasing in almost every sector. Reports from NASSCOM suggests that India’s data industry would reach $16 billion by 2025 from the present level of $2 billion. At the core of it, data science is the science of examining raw data and applying statistical techniques for the purpose of drawing business related conclusions and predicting business outcomes. In every organization, there are opportunities to implement data science and transform the way business is carried out.
Leading analysts like Gartner and Forrester have quoted 2018 as a milestone year for organizations, with over 70% of them expected to leverage data science for Business Optimization. It is one of the most talked about topics in the CxO community.
In today’s era, all small and large corporates are sitting on a gold mine of data, however, the biggest challenge they are facing is to use these data to get business insights which they can implement to make effective business decisions and optimize their business. In the Indian context, below are the industries adapting data science to gain the competitive advantage: Financial institutions are optimizing price, improving customer satisfactions, predicting risk of defaults, optimizing underwriting process Hospitals are increasing diagnoses accuracy, providing physicians with accurate sickness’s causes for individual patients, preventing patient readmissions, predicting risk of infections Retail chains are increasing occasional and loyal customer satisfaction, optimizing campaigns, offering the right price for products, preventing inventory shortage Manufacturing organizations are predicting machine failures, providing predictive safety alerts, building accurate pro-active maintenance plan
However, applying traditional data science methods to real-world business problems is time-consuming, resource-intensive, and challenging. It also requires experts in the several disciplines, including data scientists.
Enterprises leveraging Automated Data Science to achieve efficiencies:
Automated data Science represents a fundamental shift in the way organizations of all sizes approach machine learning and data science. Automated data science platforms are bringing the advanced AI techniques into reach for the mainstream. Organizations are finding that with automated data science they can make progress in AI without hiring new data scientists or embarking on expensive, time-consuming training for their employees. Instead, almost anyone with domain experience and a familiarity with data can build predictive models without writing a single line of code or having deep knowledge of machine learning algorithms.