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VSCode is the most used IDE in the world. It is strategic have more extensions for VSCode for InterSystems technologies to keep increasing the developer community.

My new app IRIS VSCode Global Editor is an excellent sample to learn how to create extensions to IRIS. You can check it on https://openexchange.intersystems.com/package/IRIS-Global-VSCode-Editor.

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Article
· Dec 16, 2024 2m read
Edit your Globals with VSCode and YAML

The best way to list, edit, save and delete globals is using an IDE. Now, it is possible if you use VSCode. It is also possible to save globals using yaml files. Perform the following steps:

1. Get an InterSystems IRIS instance and install the application iris-global-yaml: 

zpm:USER>install iris-global-yaml

2. If you just to want an InterSystems IRIS trial for tests git clone and run on docker:

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The rise of Big Data projects, real-time self-service analytics, online query services, and social networks, among others, have enabled scenarios for massive and high-performance data queries. In response to this challenge, MPP (massively parallel processing database) technology was created, and it quickly established itself. Among the open-source MPP options, Presto (https://prestodb.io/) is the best-known option. It originated in Facebook and was utilized for data analytics, but later became open-sourced.

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In the modern world, the most valuable asset for companies is their data. Everything from business processes and applications to transactions is based on data which defines the success of the organization's operations, analysis, and decisions. In this scenario, the data structures need to be ready for frequent changes, yet in a managed and governed way. Otherwise, we will inevitably lose money, time, and quality of corporate solutions.

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The InterSystems IRIS has a series of facilitators to capture, persist, interoperate, and generate analytical information from data in XML format. This article will demonstrate how to do the following:

  1. Capture XML (via a file in our example);
  2. Process the data captured in interoperability;
  3. Persist XML in persistent entities/tables;
  4. Create analytical views for the captured XML data.

Capture XML data

The InterSystems IRIS has many built-in adapters to capture data, including the next ones:

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Question
· Mar 19, 2024
Support for Java 17+

Any prevision when Java 17 or superior will be released?

Java 11 is not used any more, because vulnerabilities, security problems and new java resources not present in 11 version

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Killer presentations are essential for opening doors, doing business and delighting customers. These types of presentations move away from the traditional and tiring topics and portions of texts, or even pictures of happy people to get closer to the interests of their audience.The best presentations materialize what customers are looking for into something they can see working. Instead of promises, examples in execution and the ability to be very close to what you want to do.

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Article
· Feb 1, 2024 2m read
Mind map your FHIR patient data

According Wikipedia a mind map is a diagram used to visually organize information into a hierarchy, showing relationships among pieces of the whole. It is often created around a single concept, drawn as an image in the center of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those major ideas.

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Article
· Jan 29, 2024 12m read
Creating custom login pages with %CSP.Login

The %CSP.Login class is the utility class provided by InterSystems IRIS to do custom login pages. If you want to control your IRIS application authentication UI, you must extend %CSP.Login and override some methods according to your needs. This article is going to detail those methods and what you can do with them. In addition to that, you will get an explanation of the delegated authentication mechanism provided by ZAUTHENTICATE.mac routine.

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In part I of this article, we have already learned more about HL7, its messages, structure, segments, and fields. In this part II, we will show you how to transform proprietary/custom data into HL7 using IRIS for Health. For our sample, we used the data generated by the SYNTHEA bulk data generation project (https://synthea.mitre.org/downloads). So, we will show you how to convert 1000 patients from a CSV file to HL7 v2, using the Interoperability features of IRIS for Health.

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EHR (Electronic Health Record) systems are designed in a proprietary format/structure and are not based on such market models as FHIR or HL7. Whereas some of those systems can interoperate data in a proprietary format for FHIR and further market models, others cannot. InterSystems has two platforms that can interoperate proprietary formats for market standards: InterSystems HealthShare Connect and InterSystems IRIS for Health.

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According to Databricks Apache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. Apache Parquet is designed to be a common interchange format for both batch and interactive workloads. It is similar to other columnar-storage file formats available in Hadoop, namely RCFile and ORC. (source: https://www.databricks.com/glossary/what-is-parquet).

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Article
· Nov 27, 2023 2m read
Generative AI for image creation

Currently, many digital artists use generative AI technology as a support to accelerate the delivery of their work. Nowadays it is possible to generate a corresponding image from a text sentence. There are several market solutions for this, including some available to be used through APIs. See some at this link: https://www.analyticsvidhya.com/blog/2023/08/ai-image-generators/.

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Article
· Nov 20, 2023 3m read
Parquet files and InterSystems IRIS

In the world of Big Data, selecting the right file format is crucial for efficient data storage, processing, and analysis. With the massive amount of data generated every day, choosing the appropriate format can greatly impact the speed, cost, and accuracy of data processing tasks. There are several file formats available, each with its own set of advantages and disadvantages, making the decision of which one to use complex. Some of the popular Big Data file formats include CSV, JSON, Avro, ORC, and Parquet.

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The part II you will learn how to run any Jasper report file (jrxml file) designed on Jasper Studio from InterSystems IRIS. We will create a REST API to return a processed report on PDF format.

The jrxml file

On part I, we designed this report:

1. First of all, rename the report from Blank_A4.jrxml to sample.jrxml (Project Explorer tab > click right the file > Rename):

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