InterSystems IRIS Adaptive Analytics is an optional extension that provides 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 virtual cubes 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.
Can someone give me an explanation of how Local.PD.Linkage.Definition.Individual works? This was setup by another company as part of our implementation.
Below is my configuration..
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We are getting a lot of matches on Given Name, but then the Family Name does not match at all, so I am wondering if these need to be adjusted. I just don't understand if they need to be positive or negative.
if I use the MLE CALIBRATION MONITOR, it seems that none of the values should be negative.
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InterSystems IRIS Adaptive Analytics version 2025.4.1 is now available from the InterSystems Software Distribution page. This release includes AtScale 2025.4.1 and is compatible with the existing Adaptive Analytics User-Defined Aggregate Function (UDAF) file - 2024.1. New features included in AtSCale's 2025 releases include:
Hi Everyone, I'm Prakash Hinduja, a financial advisor and consultant. My roots in India now living in Geneva, Switzerland (Swiss). I'm looking for some suggestions on how to get the best performance from Adaptive Analytics 2023.2. I know it uses Adaptive Parallel Execution and automatic aggregates, but I'm curious if you've found any other tips or tricks. For example, are there any specific data modeling choices or system configurations that have worked well for you? I'm trying to make our cubes as responsive as possible. Thanks in advance for any insights!