Be Right Faster
Reltio's mission is to help both business and IT teams be right faster.
Reltio Cloud delivers enterprise data-driven applications together with a modern data management Platform as a Service (PaaS), guiding customers to take the right actions, based on the right insights, to achieve the right results.
Reltio was founded upon the belief that organizations need reliable, relevant access to information at their fingertips. We help companies turn their data into information and knowledge assets in the most efficient way, shattering the traditional notion that IT must combine multiple technologies to manage different types of data, and that business users must purchase standalone tools to do their own analysis.
Reltio manages all data types including multi-domain master data, transaction and interaction data, third party, public and social data. Data is fused into a new breed of data-driven applications that business teams love to use every day. By combining operational and analytical silos teams can continuously collaborate to improve the reliability of information, receive recommendations relevant to their goals, and take immediate action, all within the same application. Information flows in a closed-loop cycle that continuously assesses and publishes outcomes to demonstrate value and refine recommendations for better results.
How Does Reltio Compare to Other Technologies?
- Master Data Management (MDM) Only Tools - MDM tools which have been around for 10+ years such as Informatica MDM (formerly Siperian) and even a new group of cloud MDM offerings continue to see MDM as a separate siloed discipline, requiring complex IT infrastructure, processes, leading to months and years of design and implementation, before reliable data can be made available to business users. Often the delivery latency of the information leads to stale data. Meanwhile business users typically have access to more up to date information as a course of their day-to-day operations. Legacy MDM tools do not allow them to provide feedback in a collaborative and controlled manner, effectively wasting valuable intelligence and competitive advantage. Business users and IT teams become equally frustrated, viewing MDM as a promise unfulfilled.
- BI and Analytics Tools - Today's powerful and sophisticated visualization tools empower certain business users to get faster access to information on their own. Convergence of data at scale from multiple sources is now possible, however the data is not guaranteed to be clean and accurate prior to analysis. Looking at unreliable data may lead to wrong conclusions. Although many of these tools are designed for non-data scientists, they are still beyond the skill of field teams for their day-to-day operations. Additionally, these tools still require action to be taken in separate siloed operational applications, and do not automatically correlate results back to the analysis performed.
- Horizontal Packaged Business Applications - Applications such as CRM, ERP, HR and financials are widely deployed for core business processes. However legacy design and process-driven nature of such applications provide a ridged structure that is hindering business agility. Many end-users question why in the age of consumer apps such as Facebook and LinkedIn, they are still stuck with enterprise applications that required labor intensive manual data entry, jumping between applications to get the complete view they need, and having to sift through complex patterns of information. A new breed of enterprise data-driven applications can offer relevant insights and recommended actions specific to their daily operations, allowing them to significantly improve productivity and outcomes.
- Big Data Infrastructure and Tools - Hadoop, HBase, Cassandra, Graph Databases, MapReduce, Spark and the continuous stream of new technologies designed to handle ever increasing volume, variety and velocity, have changed the way data can and should be managed. However stitching together all of the pieces required to have a complete end-to-end offering is a complex undertaking. Creating a data lake, integrating master data management, relationship discovery, and other disciplines, to support a wide variety of business needs across an enterprise is a multi-year endeavor. Not everyone has the resources, skills or budget to integrate, deploy and maintain applications, while keeping up with an evolving technology landscape.