AnalyzeThis is a tool for getting a personalized preview of your own data inside of InterSystems BI. This allows you to get first hand experience with InterSystems BI and understand the power and value it can bring to your organization. In addition to getting a personalized preview of InterSystems BI through an import of a CSV file with your data, Classes and SQL Queries are now supported as Data Sources in v1.1.0!

With the advent of Embedded Python, a myriad of use cases are now possible from within IRIS directly using Python libraries for more complex operations. One such operation is the use of natural language processing tools such as textual similarity comparison.

Your may not realize it, but your InterSystems Login Account can be used to access a very wide array of InterSystems services to help you learn and use InterSystems IRIS and other InterSystems technologies more effectively. Continue reading to learn more about how to unlock new technical knowledge and tools using your InterSystems Login account. Also - after reading, please participate in the Poll at the bottom, so we can see how this article was useful to you!

We now get to make use of the IKO.

Below we define the environment we will be creating via a Custom Resource Definition (CRD). It lets us define something outside the realm of what the Kubernetes standard knows (this is objects such as your pods, services, persistent volumes (and claims), configmaps, secrets, and lots more). We are building a new kind of object, an IrisCluster object.

In a customer project I was asked how you can keep track of database changes: Who changed what at which date and time. Goal was to track insert, update and delete for both SQL and object access.

This is the table that I created to keep the Change Log:

Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

Hi - Recently I have been investigating an annoying situation whilst editing ObjectScript classes or routines in VSCode.

What was happening to me was, as I was typing in lines of code into my class (for example, adding a new Method, or changing the Class signature, or a block of code), this would quickly get syntax checked, re-formatted, and compiled - inevitably, (since I would be mid-way through my typing), this would generate compilation errors.

If you're running IRIS in a mirrored configuration for HA in GCP, the question of providing a Mirror VIP (Virtual IP) becomes relevant. Virtual IP offers a way for downstream systems to interact with IRIS using one IP address. Even when a failover happens, downstream systems can reconnect to the same IP address and continue working.

The main issue, when deploying to GCP, is that an IRIS VIP has a requirement of IRIS being essentially a network admin, per the docs.

To get HA, IRIS mirror members must be deployed to different availability zones in one subnet (which is possible in GCP as subnets always span the entire region). One of the solutions might be load balancers, but they, of course, cost extra, and you need to administrate them.

In this article, I would like to provide a way to configure a Mirror VIP without using Load Balancers suggested in most other GCP reference architectures.

If you've worked with iKnow domain definitions, you know they allow you to easily define multiple data locations iKnow needs to fetch its data from when building a domain. If you've worked with DeepSee cube definitions, you'll know how they tie your cube to a source table and allow you to not just build your cube, but also synchronize it, only updating the facts that actually changed since the last time you built or synced the cube. As iKnow also supports loading from non-table data sources like files, globals and RSS feeds, the same tight synchronization link doesn't come out of the box. In this article, we'll explore two approaches for modelling DeepSee-like synchronization from table data locations using callbacks and other features of the iKnow domain definition infrastructure.

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.

I have challenged to create a bot application using Azure Bot that can retrieve and post data to IRIS for Health.

A patient's data has already been registered in the FHIR repository of IRIS for Health.

The patient's MRN is 1001. His name is Taro Yamada. (in Japanese :山田 太郎)

This bot can post new pulse oximeter readings as an observation resource linked to the patient.

InterSystems IRIS provides a complete application development environment for building sophisticated data- and analytics-intensive applications that connect data and application silos. It is designed to work with all of the common development technologies in an open, standards-based fashion and supports both server-side and client-side programming.

We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

When it comes to build an iris image, we can use the cpf merge files.

Here is an cpf merge example:

[Actions]
CreateDatabase:Name=IRISAPP_DATA,Directory=/usr/irissys/mgr/IRISAPP_DATA

CreateDatabase:Name=IRISAPP_CODE,Directory=/usr/irissys/mgr/IRISAPP_CODE

CreateNamespace:Name=IRISAPP,Globals=IRISAPP_DATA,Routines=IRISAPP_CODE,Interop=1

ModifyService:Name=%Service_CallIn,Enabled=1,AutheEnabled=48

CreateApplication:Name=/frn,NameSpace=IRISAPP,DispatchClass=Formation.REST.Dispatch,AutheEnabled=48

ModifyUser:Name=SuperUser,PasswordHash=a31d24aecc0bfe560a7e45bd913ad27c667dc25a75cbfd358c451bb595b6bd52bd25c82cafaa23ca1dd30b3b4947d12d3bb0ffb2a717df29912b743a281f97c1,0a4c463a2fa1e7542b61aa48800091ab688eb0a14bebf536638f411f5454c9343b9aa6402b4694f0a89b624407a5f43f0a38fc35216bb18aab7dc41ef9f056b1,10000,SHA512