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..

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.

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:

• Several MDX improvements to better handle null values and semi-additive measures like year-to-date.
• New parameters to enable setting the visibility of calculations and calculation groups in BI tools.
• Support for inbound query crossjoins that return empty cells

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!

Regards

The InterSystems IRIS is a great data platform and it is met the current features required by the market. In this article, you see the top 10:

Note: this list was updated because many features are added to IRIS in last 3 years (thanks @Kristina Lauer)

Hi, Community!

Want to use your data to make better business decisions? Creating virtual models can help! See how:

Creating Virtual Models with InterSystems IRIS® Adaptive Analytics

In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used. InterSystems IRIS Data Platform answers that with and add-on of Adaptive Analytics that can deliver this unified semantic layer. There are a lot of articles in DevCommunity about using it via BI tools. This article will cover the part of how to consume it with AI and also how to put some insights

InterSystems IRIS Adaptive Analytics version 2024.1.3 is now available from the InterSystems Software Distribution  page.  This release includes AtScale 2024.1.3, and an updated User Defined Aggregate Function (UDAF) file.  This release includes and the following new modeling and BI capabilities:

Just in time for Valentine’s Day, we are showing you some Adaptive Analytics love!  InterSystems IRIS Adaptive Analytics version 2023.3 is now available from the InterSystems Software Distribution  page.  This release includes AtScale 2023.3 with additional tuning, API enhancements and the following new capabilities:

Power BI

Connecting to a Data Source

To connect to AtScale, we will use the SQL Server Analysis Services database. Let's open it in the Power Query editor. To do that, select Transform Data on the Home.

In the window that appears, go to the Home, expand New Source and select Analysis Services.

InterSystems IRIS Adaptive Analytics version 2023.2 is now available from the InterSystems Software Distribution site.  This new release brings along some great enhancements included with our partner AtScale's Version 2023.2 including:

• Increased object sharing across cubes to make virtual data model development easier
• A simplified way to create common, but complex, model elements like time-relative measures, intelligent dimensions, and calculation groups
• Improved connector for Microsoft PowerBI
• Built in usage metrics dashboard to manage aggregates and queries

In this article, we will explore the use of parameters, formulas and labels in Logi Report Designer (formerly Logi JReport Designer). What are they for and how to create them?

Using the basic functionality of InterSystems Reports Designer, parameters, formulas and labels, you can significantly improve the detail and information content of the generated report. In addition, these tools allow you to automate some of the processes, which greatly speeds up and facilitates the creation of reports.

Let's analyze each tool separately now.

In our latest episode of Data Points, I had a conversation with @Thomas Dyar about AI Link, which helps bridge the gap between data scientists and business analysts. Our conversation talks about how AI Link fits with IntegratedML and Adaptive Analytics, as well, as what new features are on the horizon for IntegratedML. Take a listen!

Today we will talk about InterSystems Reports. This is a BI system that provides you with tools to create static reports and export them to different file formats. We will see how it works using the DC Analytics public analytical sample as an example. In this article, we will examine how to familiarize yourself with the reports available in the repository, how to make a new report based on a ready-made data structure, and how to prepare a data structure from scratch.

To begin with, you need a licensed copy of InterSystems Reports. 

Developers, we have prepared a tutorial to get you started with InterSystems Adaptive Analytics powered by AtScale. In it, in addition to setting up AtScale and working with data cubes, we will also touch on methods of working with InterSystems Reports and other analytical systems.

Now the course is ready and we want to conduct a pilot training course on a small group of volunteers (3-5 people).

Today we will talk about Adaptive Analytics. This is a system that allows you to receive data from various sources with a relativistic data structure and create OLAP cubes based on this data. This system also provides the ability to filter and aggregate data and has mechanisms to speed up the work of analytical queries.

Let's take a look at the path that data takes from input to output in Adaptive Analytics. We will start by connecting to a data source -  our instance of IRIS. 

In our latest episode of Data Points, I had a conversation with Carmen Logue and Mary Ann Fusi about Adaptive Analytics and Smart Data Fabrics. A lot has changed and improved since the last time we discussed this product on the podcast, so take a listen!

When we work with IRIS, we usually have the ability to quickly deploy a ready-to-use infrastructure for BI (data, analytical cubes, and IRIS BI dashboards) using modules. When we start  using Adaptive Analytics, we typically want to have the same functionality. Adaptive Analytics has all the tools that we need. The documentation contains a description of how to work with an open web API. All interactions between the user interface and the engine also occur via the internal web API and can be emitted.

When we are at the starting stage of BI project development, we must remember that it is crucial to select the right tool for its implementation. Today we want to show you how one of the principal functionality of dashboards is implemented in different BI systems. Let's talk about drill down from both points of view: the dashboard development, and the convenience and clarity for the end user. We will touch on the applications of this technology in IRIS BI, Power BI and Tableau.

InterSystems Developer Community analytics. Project made with InterSystems IRIS BI (DeepSee), Power BI and Logi Report Designer to visualize and analyze members, articles, questions, answers, views and other pieces of content and activity on InterSystems Developer Community.

You can see your own activity, articles and questions. Track how your contribution changes developer community.

Analyse statistics about you and your friends using IRIS BI, Adaptive Analytics, InterSystems Reports, Tableau and Power BI.

Power BI dashboards provide us with a good way to analyze aggregated information. We can even choose time periods for aggregation (you can find more details regarding it in our article about drill down). However, we might still be interested in a detailed look at specific data points. With the right data filling, we can display detailed data for any column of the chart with all filters applied to that chart. For example, we can see what exact questions were asked on the site on a particular day, who their author was, how many views they received, etc, and all of that without going beyond our

One of the most important tasks of dashboards is, on the one hand, to help you perceive data in an aggregated form, and, on the other hand, not to lose the depth of immersion in the data if you need this. One of the tools that help us achieve this result is drill down. It enables us to display several hierarchical levels of data, from aggregated to detailed.Our task is to make an analytical dashboard that will be able to drill down by time periods:  from months to weeks and days in each chart. The stack that we will use for work consists of IRIS as a data storage system, Adaptive Analytics for

AtScale pulls data from the IRIS database. 

The AtScale product forms a virtual OLAP cube on the intermediate layer, which external applications can access using standard SQL and MDX (Multidimensional Expressions) languages. The solution includes three main components.

When we collect temporary data (the number of purchases in the store, the number of comments on the post), it may happen that there is no data for a certain period of time. In this case, this time period (hour, day, month) is not represented in the database, that is, there is not a single row for this period. In other words, there are no rows in the database for this period.

Hi All! We have recently updated the Exploring Healthcare Analytics with InterSystems exercise to a new version. Originally from a 2021 Virtual Summit experience lab, this exercise now focuses more specifically on using InterSystems IRIS Adaptive Analytics with InterSystems IRIS for Health. It features a new and improved data model and exercise to explore. Feel free to give it a try!

It is very interesting to compare different BI technologies. It is curious to me what the differences are in functionality, development tools, speed and usability.

For this application, I chose a dataset with water conditions in various European countries. This is an open source dataset containing observational data from 1991 to 2017.

The team and I decided to make a model based on this BI dataset using IRIS BI, Tableau, PowerBI and InterSystems Reports (powered by Logi Reports).

For the frontend, we made a web interface in PythonFlask via Embedded Python.

Colleagues, hello!

In this article, I will tell you how we reduced the report generation time from 28 minutes to 1 minute. Let me tell you how we achieved this.

I hope that if necessary you will be able to reproduce the same results for yourself. Useful links will be inside this post, so read to the end.

Let's start.

Report

Hi Developers, 

New video is already on InterSystems Developers YouTube: 

⏯ Adaptive Analytics in Action: Financial Services Use Case

I was using PowerBI to create regular display data obtained from one popular web sourse with hundreds of thousands of visitors per month and a big number of users.

At the beginning of that visualisation development, I was using direct connection from Power BI to Adaptive Analytics powered by AtScale. Adaptive Analytics is useful for cached data, aggregates and fast data sources switching between development and stage phases. The “AtScale cubes'' connection method was used:

The Problem 

Hey Community,

Enjoy watching the new video on InterSystems Developers YouTube channel:

⏯ Creating Virtual Models with InterSystems IRIS Adaptive Analytics

Hey Community,

See how cubes are constructed for use in business intelligence, and learn about SQL and MDX query languages. Physical and virtual cubes are used in InterSystems IRIS® Business Intelligence and Adaptive Analytics:

⏯ Introduction to Cubes in Business Intelligence