This tag relates to the discussions on the development of analytics and business intelligence solutions, visualization, KPI and other business metrics management.
The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently.
TL;DR: My comment to Microsoft when I voted:Our team has implemented most of what we need for source management of Power BI Report files in Perforce. The missing piece?
I am working with InterSystems IRIS and seeking guidance on how to perform specific tasks related to the FHIR SQL Builder using commands or code, rather than the graphical user interface (GUI). The specific tasks I am trying to accomplish are:
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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.
A few months ago, I faced a significant challenge: streamlining the handling of business logic in our application. My goal was to extract the business logic from the code and hand it over to analysts. Dealing with a multitude of rules could easily result in a code littered with countless "if" statements, especially if the coder lacked an understanding of cyclomatic complexity. Such code becomes a source of pain for those working with it—difficult to write, test, and develop.
I hope this message finds you well. I am reaching out because I have encountered an issue with a new dimension I created, named "Region," and I could use your assistance in resolving it.
The problem is that when I open the cube analyzer, the "Region" dimension does not populate data as expected. Instead, it merely displays the text "sourceRegion," which I specified as an expression in the architect.
Watch this video to learn about some recent machine learning engagements InterSystems is driving, including TrakCare predictive analytics and examples from our Developer Community and partners:
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We recently published a new White Paper on the use of reporting nodes ("asynchronous reporting mirror members" in full) in a mirrored environment. More and more customers are looking into this mechanism as a quick and easy way to set up a copy of their production data that stays current, yet can be used for analytical querying or heavy-duty reporting workloads without impacting the source system. Read the White Paper here.
Creating information dashboards, pivot tables, and widgets is an important step in analysis that provides valuable sources of information for informed decision-making. The IRIS BI platform offers many opportunities to create and customize these elements. In this article, we will take a closer look at the basic techniques for developing them and the importance of using them.
Hello community, I need to solve a complex but trivial issue.
Given:
Two tables "Comment" and "Post". Each one contains an "Author" field, which is essentially a user ID. In these tables, each user ID represents an author. The goal is to count all participants together and then group them by month, language, and other metrics.
The question is how to do this within the IRIS ecosystem. Is it even possible to take two tables, get distinct data from them and then combine into one cube?
When analyzing data, there is often a need to look at specific indicators more thoroughly and to highlight sections of information of particular interest to a user.
For instance, examining the data dynamics for specific regions or dates can help us uncover some hidden trends and patterns that will allow us to make an informed decision about our project in the future.
I'm trying to build a cube based on a linked table but seems that IRIS is not able to do it :O
Long story short, I have a linked table in IRIS that sources a Microsoft SQL table (using standard linked feature from the portal). It works fine, I can access it using SQL as many other times. On top of that, I've created in DeepSee (ok, Analytics) a cube that uses this class as source. It compiles correctly, no errors given. When I build it with 100 records, all goes well and using Analyzer I can see results.
Anyone who has (near or distant, with a preference for the 1st option) knowledge of the use of Amazon QuickSight with IRIS is invited to share his|her experience in this discussion.
We have received quite a lot of interest in using SQL on FHIR data. As you know, FHIR data is encoded in the form of a complex directed graph, and thus you can not easily query it with traditional SQL queries or business intelligence tools. Some customers have noticed that the "FHIR search tables" in IRIS for Health have flattened part of the FHIR graph, and have tried to use them for analytics. This is an undocumented and unsupported part of IRIS for Health, and can change without notice.
How to include IRIS Data into your Google Big Query Data Warehouse and in your Data Studio data explorations. In this article we will be using Google Cloud Dataflow to connect to our InterSystems Cloud SQL Service and build a job to persist the results of an IRIS query in Big Query on an interval.
As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:
A simple data analysis example created in IntegratedML and Dashboard
Based on InterSystems' Integrated ML technology and Dashboard, automatically generate relevant predictions and BI pages based on uploaded CSV files. The front and back ends are completed in Vue and Iris, allowing users to generate their desired data prediction and analysis pages with simple operations and make decisions based on them.
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When I started this project I had set myself limits: Though there is a wide range of almost ready-to-use modules in various languages and though IRIS has excellent facilities and interfaces to make use of them I decided to solve the challenge "totally internal" just with embedded Python, SQL, ObjectScript Neither Java, nor Nodes, nor Angular, PEX, ... you name it. The combination of embedded Python and SQL is preferred. ObjectScript is just my last chance.
Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.
And now it is possible to use with InterSystems IRIS as well.
An online demo is available and it uses IRIS Cloud SQL as a data source.
Our team has had success creating and publishing Power BI reports using an ODBC connection to an IRIS database, but there have been concerns about the responsiveness of these reports.
As an attempt to improve responsiveness, I'm trying out the "DirectQuery" connection using the InterSystems IRIS connector available in our version of Power BI Desktop (September 2021).
The version of IRIS I'm connecting with is "IRIS for Windows (x86-64) 2022.2"
With the improvement of living standards, people pay more and more attention to physical health. And the healthy development of children has become more and more a topic of concern for parents. The child's physical development can be reflected from the child's height and weight. Therefore, it is of great significance to predict the height and weight in a timely manner.
Watch this video to see InterSystems IRIS in action as it is applied to real-world use cases, including business 360 and real-time analytics processing:
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