Self-service analytics capabilities coupled with expanded functionality for implementing data fabric initiatives provide business users with unparalleled access and exploration of distributed enterprise data
InterSystems, a creative data technology provider dedicated to helping customers solve the most critical scalability, interoperability, and speed problems, announced the latest release of its InterSystems IRIS data platform, which includes Adaptive Analytics capabilities and additional SQL extensions for analytics to improve the process of implementing an enterprise data fabric architecture.
Announced last year through its partnership with AtScale, Adaptive Analytics within InterSystems IRIS provides business users with superior ease of use and self-service analytics capabilities to visualize, analyze, and interrogate live data from multiple sources in a consistent format. This empowers users to get the information they need to make timely and accurate business decisions, regardless of the source, format, velocity, or age of the data, without needing to be experts in data design or data management.
The latest release of InterSystems IRIS speeds up and reduces the complexity of implementing enterprise data fabrics, a modern architectural approach to data management that integrates and harmonizes dissimilar, distributed data from across the enterprise and makes it available on-demand.
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Self-Service Adaptive Analytics Capabilities
Adaptive Analytics extends these capabilities further, making the fabrics ‘smarter’ to enable business user self-service and making data usable for a large number of applications to meet a wide range of critical business requirements, including risk management, business management reporting, decision support, and regulatory compliance.
A core component of smart data fabrics, InterSystems IRIS also provides faster time to value and powers intelligent predictive and prescriptive services.
“One of the biggest data challenges facing businesses is integrating their data from across multiple systems and silos and turning it into actionable insights,” said Scott Gnau, Vice President of Data Platforms at InterSystems. “Enterprise data fabrics have emerged as the solution to this issue as they allow data to stay where it is, enabling businesses to maximize the value from their previous technology investments, including data lakes and warehouses, without having to “rip-and-replace” any of their existing technology. The latest update to InterSystems IRIS then incorporates the critical capabilities organizations need to implement a data fabric quickly and easily to meet their most challenging business requirements and fully leverage their data.”
Monica Summerville, Head of Capital Markets, Celent, an Oliver Wyman business, said, “There has been significant interest in the financial services sector for an approach like data fabrics to help meet the rapidly evolving needs of sector participants. By embedding analytics directly into the data management platform, smart data fabrics take these initiatives one step further by eliminating the need to move the data to different environments and reducing latencies to support real-time and near real-time use cases. Celent research has found that financial services firms are looking to self-service approaches and advanced data management technologies to increase efficiency, comply with risk and regulatory reporting, and deliver value to customers.”
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Additional SQL File Extensions for Analytics
As part of the latest release, additional SQL Extensions for Analytics make it easier for data teams to access data for machine learning, BI, and reporting use cases more quickly and efficiently, while InterSystems continued investment in powerful embedded analytics capabilities will increase query performance by up to 30% for InterSystems IRIS users.
A next-generation data platform, InterSystems IRIS provides powerful database management, integration, analytics, application development, and API management capabilities all in a single product built from the ground up – to speed time to value, simplify architectures, and lower total cost of ownership.
