Skip to content
Search to learn about InterSystems products and solutions, career opportunities, and more.

Accelerate Time to Insight with InterSystems IRIS Adaptive Analytics

Adaptive Analytics

To be successful, organizations need to provide their business users and data analysts with the ability to gain insights into every aspect of the enterprise. InterSystems IRIS® Adaptive Analytics extends InterSystems IRIS data platform to deliver faster time to insight and better business decisions for a wide range of users across the enterprise at scale.

InterSystems IRIS allows users to build important applications quickly and easily. Harnessing the power of machine learning – and featuring capabilities for data management, interoperability, and analytics – InterSystems IRIS is the right choice for building cloud-first solutions for mission-critical data.

Adaptive Analytics is an optional extension that makes InterSystems IRIS even more powerful by providing a business-oriented, virtual data model layer between InterSystems IRIS and popular Business Intelligence (BI) and Artificial Intelligence (AI) client tools. It includes an intuitive user interface for developing a data model in the form of a “virtual cube” where data can be organized, calculated measures consistently defined, and data fields clearly named. By having a centralized common data model, enterprises solve the problem of differing definitions and calculations to provide their end users with one consistent view of business metrics and data characterization.

Key Capabilities

  • Data stays in InterSystems IRIS for best possible performance – no copying or moving it around
  • Data stewards use the Adaptive Analytics modeler to make data accessible for business users – no need to expose complex data structures, tables, or relationships
  • Changes to the data model are published as virtual cubes without disrupting users – no waiting for lengthy rebuilding of cubes
  • Analytics users can employ the BI tool of their choice, e.g. Microsoft Excel and PowerBI, or Tableau, and access the same online analytical processing (OLAP) model
  • Adaptive Analytics uses the full breadth of data stored within InterSystems IRIS through live connectivity rather than partial content or stale data extracts
  • It provides a single layer to govern data access and protects sensitive data from unauthorized access

From the queries run against the data model, Adaptive Analytics builds acceleration structures that are used to satisfy frequently issued requests more efficiently. These pre-aggregated data structures are created automatically based on query patterns, and these aggregates get faster over time as further data requests are made. In contrast to simple caching, aggregates are generated to include additional data fields that may be needed to satisfy queries run in the future.

What Sets InterSystems IRIS Adaptive Analytics Apart?

  • Universal semantic layer makes complex backend data structures more accessible to non-technical users
  • Avoids the issue of differing query dialects to provide consistent answers to the same question across the organization, no matter which BI or AI tool is used
  • Enables self-service BI so that business users can carry out interactive and multidimensional analysis themselves without waiting on IT staff
  • Learns from query patterns and builds aggregations using machine learning to get smarter and faster
  • Unprecedented scaling and performance via the power of InterSystems IRIS

Who Will Use InterSystems IRIS Adaptive Analytics, and What are the Benefits to Them?

Typically, there are three types of users who will benefit from Adaptive Analytics:

  1. DBA/data engineers – Adaptive Analytics frees them to spend time handling complex issues and finding new data assets to make available via additional data pipelines, instead of being consumed with manually curating and creating aggregates to make things run faster
  2. Data stewards/modelers – Adaptive Analytics provides them with an intuitive drag-and-drop user interface to create the data model and streamline field names, generating the building blocks for end users to build upon
  3. Business users – Adaptive Analytics gives them easy and consistent access to well-defined data using their tools of choice

Availability

Adaptive Analytics is an optional extension to InterSystems IRIS and IRIS for Health Advanced Server, available with InterSystems IRIS and IRIS for Health versions 2021.1.

 

Other Resources You Might Like

May 09, 2025
Longitudinal Health Record
This briefing highlights how InterSystems is collaborating with diverse customer organizations to streamline the set-up of new data feeds to a high-performing longitudinal health record.
May 09, 2025
Enabling More Resilient, Flexible, and Transparent Supply Chains
InterSystems technology enables you to optimize your supply chain performance by predicting disruptions before they occur, and optimally handling them when they do.
May 09, 2025
HIMSS TV
Dr. Alfredo Almerares, clinical executive manager at InterSystems, says the company's generative AI tools that summarize patient visits are helping Latin American clinicians to relieve burnout and build patient relationships.
May 08, 2025
IDC Conversation
Learn how access to data and data quality impact efforts to improve the supply chain and the primary causes of longer time to value and high implementation costs.
May 02, 2025
InterSystems IRIS for Health and FHIR
Simplifying Data Access with InterSystems FHIR Solutions
Apr 29, 2025
Fundamentals
Compare RAG, fine-tuning, and prompt engineering to find the best AI approach for your needs. Includes practical examples and an interactive decision tool.
Apr 21, 2025
Internet of Healthcare Things
Developing solutions that deliver the promise of Internet of Healthcare Things (IoHT) can be difficult. To be successful, developers must capture vast amounts of medical device data in real time.
Apr 15, 2025
Enterprise Master Person Index
Next-Generation Enterprise Master Person Index for Identity Management Seamless patient, member, and beneficiary identification is essential for efficient operations across healthcare organisations and government agencies. Yet, fragmented systems, inconsistent identifiers, and data gaps continue to disrupt workflows, increase costs, and compromise care quality and service delivery. 35% of denied medical claims stem from inaccurate patient identification¹, while mergers and affiliations further complicate record consolidation. Even within a single information system, duplicate or overlaid records can introduce inefficiencies and risks; by creating costly administrative burdens and compromising the accuracy of AI workflows built on unreliable data. To maintain data integrity and prevent cascading errors, organisations must be able to detect problematic records in real time and trigger corrective actions.
Apr 08, 2025
IDC InfoBrief
In today’s rapidly evolving healthcare landscape, the strategic implementation and optimization of advanced Electronic Health Record (EHR) systems continue to be paramount, despite significant prior investments in this area. Download the IDC InfoBrief
Apr 04, 2025
Optimizing Analytics Development in Financial Services
Smarter Processes, Smarter Decisions

Take The Next Step

We’d love to talk. Fill in some details and we’ll be in touch.
*Required Fields
Highlighted fields are required
*Required Fields
Highlighted fields are required

By submitting your business contact information to InterSystems through this form, you acknowledge and agree that InterSystems may process this information, for the purpose of fulfilling your submission, through a system hosted in the United States, but maintained consistent with any applicable data protection laws.



** By selecting yes, you give consent to be contacted for news, updates and other marketing purposes related to existing and future InterSystems products and events. In addition, you consent to your business contact information being entered into our CRM solution that is hosted in the United States, but maintained consistent with applicable data protection laws.