This is my introduction to a series of posts explaining how to create an end-to-end Machine Learning system.

Starting with one problem

Our IRIS Development Community has several posts without tags or wrong tagged. As the posts keep growing the organization
of each tag and the experience of any community member browsing the subjects tends to decrease.

First solutions in mind

We can think some usual solutions for this scenario, like:

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.

Purpose

This set of tools (RanRead, RanWrite, and the combined RanIO) is used to generate random read and write events within a database (or pair of databases) to test Input/Output operations per second (IOPS). They can be used either in conjunction or separately to test IO hardware capacity, validate target IOPS, and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis. The suggested method is by running the System Performance tool that comes bundled within IRIS. Please note that this is an update to a previous release, which can be found here.

IRIS BI

We offer you to embed business intelligence into your applications in order to give your users an opportunity to ask and answer sophisticated questions about their data. Typically, your application will include customizable dashboards that can provide insight into data from Business Intelligence models known as cubes.

In contrast with traditional BI systems that use static data warehouses, Business Intelligence keeps being constantly synchronized with the live transactional data.

The pandemic that struck the world in 2020 made everyone follow the news and the numbers that involve the COVID-19.

Why don’t you take that opportunity to create something simple and pleasant, to follow the number of vaccinations worldwide?

To face this challenge, I'm using the data provided by Our World in Data - Research and data to make progress against the world’s largest problems.

They have a dedicated repository on Github with the data of COVID-19, and I took the vaccination data to help me with my tracker.

When you have been using cubes for business intelligence in a namespace for some time, you may find that there are many cubes in the namespace, only some of which are actively being used. However, it can be difficult to tell which cubes users are or are not querying, and maintaining unused cubes can be costly both in terms of storage and of computation to keep them up to date. This article provides some suggestions and examples for monitoring which cubes are in active use, and for removing cubes that you determine are no longer necessary.

Hi guys.

Recently, I get interest in FHIR in order to run for the IRIS for Health FHIR
contest. As a beginner on this topic, I've heard somewhat about it, but I didn't know how complex and powerful was FHIR. As pointed out by @Henrique.GonçalvesDias here, you can model several aspects of the patient history and other related entities.

The capacity of taking numerous records every second while also facilitating real-time queries simultaneously in real time is called Hybrid Transactional Analytical Processing (HTAP). It is also called Transactional analytics or Transanalytics or Translytics and is a very useful element in scenarios where there is constant flow of real time data coming from IIOT sensors or data on fluctuations in stock market, and supporting the need for querying these data sets in real-time or near real-time.

Making a Chart using Intersystems IRIS + Python

How to use the IRIS Native API in Python to access globals and plot some charts.

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application.
If you are curious (https://www.python.org/about/apps/)

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:

Inter

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.

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.

Hi Developers!

As you know the application errors live in ^ERRORS global. They appear there if you call:

d e.Log() 

in a Catch section of Try-Catch.

With @Robert Cemper's approach, you can now use SQL to examine it.

Inspired by Robert's module I introduced a simple IRIS Analytics module which shows these errors in a dashboard: