Data World

techerati.com | September 26, 2019

While machine learning has transformed many industries over the past decade, one area that is still playing catch-up is insurance. It’s a sector used to finding itself trailing behind other industries’ tech adoption, where high running costs of legacy systems squeeze budgets to such an extent that it’s hard for firms to stump up the cash necessary for driving innovation. While online comparison services have proliferated in recent years, signing up to and managing the policy in...

| June 06, 2016

Data Governance represents a set of processes that ensure corporate data assets are formally managed throughout the enterprise. Data Governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient…...

https://analyticsindiamag.com | January 14, 2020

AutoML or automated machine learning has witnessed an exponential rise when it comes to being adopted by the organisations. AutoML can be said as the next wave of machine learning which helps to bridge the gap between talent landscape and complex workflows. Previously in one of our articles, we had discussed the functionality of AutoML and how it solves data science problems. Building complex deep learning models from scratch can be said as one of the most time-consuming and challenging tasks in...

analyticsinsight.net | January 14, 2020

The field of data science and analytics has been quickly growing. All from new-age tech-driven startups to settled conventional organizations have started utilizing data analytics in enormous numbers. With business sectors getting increasingly competitive and the business environment progressively unpredictable, data science and analytics (specifically augmented analytics) present firms with a more noteworthy advantage.Its capacity to predict and harmonize decision making by giving significant e...