Reltio Cloud Brings Continuous Data Organization to Enterprises
Talk about automation: Reltio Cloud constantly rearranges itself, reports on the condition of a company’s data and even offers suggestions on ways to be more efficient.
As cloud services become more sophisticated, they also become more granular and specialized. As of Feb. 21, add another smart cloud to a growing list of options for enterprises.
Reltio, known for developing something called the Self-Learning Data Platform, launched Reltio Cloud 2018.1, a new version of the native cloud platform that organizes enterprise data for continuous learning and updating. It constantly rearranges itself, reports on the condition of a company’s data and even offers suggestions on ways to be more efficient.
The release includes the next evolution of Reltio IQ–formerly Reltio Insights–which uses advanced analytics and machine learning for day-to-day operations and applications. A key feature of Reltio IQ, the company said, is the ability to derive IQ scores or recommendations for efficient data organization and for business insight, and to embed them back into customer, account or product profiles for easy segmentation and operational execution.
You can view a video here showing how marketing professionals and data scientists ostensibly can all benefit from this.
The platform offers continuous data organization, recommended actions and measurable results. Five key things it does are:
- make data the heart of every decision;
- organize data of all types at unlimited scale;
- unify data sets while providing unlimited personalized views;
- infuse analytics into operational business processes; and
- continuously learn about customers, products and their relationships.
Reltio Cloud 2018.1 continues to organize billions of multi-domain profiles, relationships, and interactions at petabyte-scale, and is being used for day-to-day operational activities by thousands of IT and business users globally, the company said.
This new release includes:
- Seamless analytics and machine learning: Reltio IQ processes data, organized and consolidated within Reltio Cloud and the Reltio Self-Learning Graph to provide a trusted foundation of reliable data for analytics and machine learning. An on demand Apache Spark environment allows data scientists to spend their time tuning algorithms via their tools of choice, rather than aggregating and cleaning data. Reltio IQ then seamlessly synchronizes IQ attributes and recommendations back to profiles for use in operational Data-Driven Applications. IQ scores can also be benchmarked anonymously across industry segments to give companies greater insight into where they stand relative to their peers.
- Advanced master data management and reference data management: Match IQ provides advanced statistics together with new Proximity, Cross-attribute, and Groups/Household rules to improve profile consolidation. Reference Data Management, included as core Reltio Cloud functionality, has a new UI for mapping and translation from multiple sources.
- Increased platform agility and performance: Export IQ, an ultra-fast export, now supports flexible filtering and billions of high performance API calls per day, for real-time business operations.
- Continuous compliance: Enhanced General Data Protection Regulation (GDPR) compliance has built-in features to execute “right to be forgotten” requirements through audit and history of contributing source indexes, as well as deletion of data on demand.
- Actionable statistics and simplified configuration: Reltio Console supports the ongoing management and health of the Reltio Cloud environment, and the underlying data assets being organized. The Console has improved statistics, and configuration validation to proactively recommend and enforce best practices, as well as an upgrade to the Reltio UI Modeler to further customize data-driven application profile pages.
The latest version of the Reltio Self-Learning Data Platform will be showcased Feb. 26 and 27 by customers and partners at DataDriven18, the Modern Data Management Summit in San Francisco, one of the largest gatherings of data management and machine learning experts.