Maybe someday you will need to use Adaptive Analytics but there is little information about this, so I decided to write an article on how to start developing a dashboard on Tableau using the Atscale cube.

In a previous article, I talked about the implemented package manager commands (generate, list, load).
In this article I want to talk about other commands.

repository

On the Option tab, you can see which current case is set and switch

Surely you wanted to use the OpenAPI Specification (OAS) JSON you used for your spec class on the iris-web-swagger-ui iris package. The generated OAS from the ##class(%REST.API).GetWebRESTApplication(...) method is very crude, with no description on the parameters or the expected response structure.

So after creating your REST application from an OAS you should have:

Demonstration example for the current Grand Prix contest for use of a more complex Parameter template to test the AI.

Interview Questions

There is documentation. A recruitment consultant wants to quickly challenge candidates with some relevant technical questions to a role.

Can they automate making a list of questions and answers from the available documentation?

Interview Answers and Learning

One of the most effective ways to cement new facts into accessible long term memory is with phased recall.

Introduction

This is a quickstart guide to IRIS for Linux systems administrators who need to be able to support the IRIS DB as well as other normal infrastructure tasks.

IRIS is a DB system from Intersystems. An IRIS DB can hold code (in the form of a Class) or data (in the form of Globals). IRIS DB are Linux files called IRIS.DAT.

Hi Community,

In this article, I will introduce my application iris-VectorLab along with step by step guide to performing vector operations.

IRIS-VectorLab is a web application that demonstrates the functionality of Vector Search with the help of embedded python. It leverages the functionality of the Python framework SentenceTransformers for state-of-the-art sentence embeddings.

Application Features

• Text to Embeddings Translation.
• VECTOR-typed Data Insertion.
• View Vector Data
• Perform Vector Search by using VECTOR_DOT_PRODUCT and VECTOR_COSINE functions.
• Demonstrate the difference between normal and vector search
• HuggingFace Text generation with the help of GPT2 LLM (Large Language Model) model and Hugging Face pipeline

I saw someone recently refer to ECP as magic. It certainly seems so, and there is a lot of very clever engineering to make it work. But the following sequence of diagrams is a simple view of how data is retrieved and used across a distributed architecture.

For more more on ECP including capacity planning follow this link: Data Platforms and Performance - Part 7 ECP for performance, scalability and availability

In the previous part of this series, we saw how to include data in a portlet from within DeepSee. This used the built in data controller. In this part, we are going to be pulling in data from outside of DeepSee. This will include both information from within InterSystems IRIS and from the OS.

Why use this?

This is useful if you would like to create a dashboard that only contains information about your system. It is also useful if you want to display data about your system along side data that you have stored in DeepSee.

SAP offers a broad support to OData in all your products. So, OData can be an excellent option to exchange data between SAP and InterSystems IRIS.

This article is a follow-up to this post.

In the previous article, [What is a Production?], we checked the production contents. We ran the sample code and checked the flowing messages' contents into the production on the Visual Trace page.

Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.

Hi Community,

In a hard work of data curation and data quality, the Health Dataset application deploy to you the above datasets.

These datasets can be used in your ML applications/models, AutoML and analytics projects. See more details here: