Hortonworks, provider of global data management solutions, has launched a new version of its platform to promote greater regulatory compliance.
The company launched Hortonworks Data Platform (HDP) 3.0 to deliver new enterprise features including containerisation for faster and easier deployment of applications, and increased developer productivity. The new version enables customers to more quickly, reliably and securely get value from their data at scale to drive business transformation according to data business.
HDP is a secure, enterprise-ready, open source Apache Hadoop-based platform. The new enhancements include enhanced security and governance, agile application deployment via containerization, support for deep learning applications, and a real-time database.
It now promotes greater regulatory compliance, including GDPR, through full chain of custody of data as well as fine-grained auditing of events. These new features offer the ability to track the lineage of data from its origin to the data lake. It also enables auditors to view data without making changes, have time-based policies and audit events around third parties with encryption protection.
The platform also delivers improved query optimisation to process more data at a faster rate and allows customers to run workloads such as machine learning and deep learning. It also enables apps to be launched quickly, allowing users to save time and resources.
Hortonworks is a provider of enterprise-grade, global data management platforms, services and solutions that deliver actionable intelligence from any type of data for over half of the Fortune 100. It provides is solutions to range of industries including financial services, healthcare, insurance, manufacturing, energy, and advertising.
Following the implementation of GDPR, Hortonworks recently launched a new service to allow enterprise to find, identify, secure and connect data.
It launched Data Steward Studio (DSS) to give enterprises ‘consistent security and governance’ for data assets across big data repositories. DSS aims to allow businesses to derive better insights from more of the data living in all of their data lakes, whether they are located in on-premises data centers or in the cloud. Customers get a comprehensive view of their data across data lakes that aggregates critical data assets, reducing the time it takes to understand key data aspects while reducing risk.
Copyright © 2018 RegTech Analyst
Copyright © 2018 RegTech Analyst
