InterSystems Takes Data Fabrics to the Next Level with Ever-Increasing Embedded Analytics Capabilities

InterSystems announces series of new releases and partnerships to further empower customers to solve critical business problems.

InterSystems, a provider of next-generation solutions dedicated to helping customers solve the most critical data challenges, has announced a series of new releases to its award-winning InterSystems IRIS data platform. The company has also recently announced a string of new customer wins as well as a new partnership as it continues to take data fabrics to the next level. According to Gartner analysts, “by 2024, data fabric deployments will quadruple efficiency in data utilization, while cutting human-driven data management tasks in half”

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InterSystems IRIS empowers customers to adopt a microservices-based architecture without the typical issues associated with microservices in data-intensive applications. By adopting a unified data platform, instead of dozens of individual services, InterSystems customers avoid the challenges of building a data fabric from scratch, including integration time and risk, maintenance of the architecture, high costs of maintaining multiple overlapping infrastructure services, and the complexity associated with data duplication.

Recent releases of InterSystems IRIS include new capabilities and enhancements that speed and simplify the creation of smart data fabric architectures, including Embedded Python and IntegratedML, as well as a new facility that lets data analysts and data scientists collaborate easily. Data analysts working on BI can develop measures, dimensions and labels that follow business needs, and are immediately usable by data scientists working on AI. Conversely, ML models created by data scientists are directly available to data analysts for use in dashboards, reports, and applications. This functionality connects AI and BI together under the hood without needing to move the data, thereby streamlining operations and enabling real-time insights for the business.

Further enhancements have also been made to performance and scalability to handle high throughput and high-performance transactional-analytic use cases; and to Adaptive Analytics, which provides self-service capabilities, empowering business users to freely explore the data, ask ad hoc questions, and drill down via additional queries based on initial findings.

When embedded into the data fabric, these analytics capabilities put the ‘smart’ into the next-gen ‘smart data fabric’ architectural approach which InterSystems champions. In doing so, InterSystems allows business users and data scientists alike to benefit from a wide range of built-in analytics capabilities, including data exploration, business intelligence, natural language processing, and machine learning.

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Adding to its data catalog, data lineage, and data governance capabilities, InterSystems has announced a partnership with Collibra, a data intelligence platform built for governance, quality, and privacy. The integration between the two platforms allows enterprise customers to take advantage of these extended capabilities on data that resides anywhere in the organization.

Further to this, InterSystems has released enhancements to the InterSystems Kubernetes Operator (IKO) to make scale up and management of data intensive applications in Kubernetes easier.

InterSystems IRIS and InterSystems IRIS for Health are available as managed cloud services, as well as a variety of smart data services in the cloud, including InterSystems FHIR Transformation Services, and InterSystems FHIR Server.

InterSystems is also celebrating a number of new customer wins, including UST and Harris Associates, demonstrating the continued appeal of InterSystems IRIS among key industries, such as financial services and supply chain.

Next week’s Gartner Data and Analytics Summit will see InterSystems take to the stage alongside representatives from Harris Associates to discuss the role of the smart data fabric in delivering real-time data access and prescriptive analytics for financial services.

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