Every now and then you may encounter a situation where for various reasons
ODBC is the only option to access a remote system. Which is sufficient as long as you need to examine or change tables.
But you can't directly execute some commands or change some Global.

According IDC, 80% of all data produced are NoSQL. See:

There are digital documents, scanned documents, online and offline texts, blob content into SQL, images, videos and audio. Imagine a Corporate Analytics initiative without all these data to analyze and support decisions?

In all the world, many projects are using techonologies to transform these NoSQL data into textual content, to allows analyze it. See:

According to IDC, more than 80% of information it is NoSQL, especially text into documents. When the digital services or applications not process all this information, the business lose. To face this challenge, it is possible use OCR technology. OCR uses machine learning and/or trained image patterns to transform image pixels into text. This is important, because many documents are scanned into images inside PDF, or many documents contains images with text inside. So OCR are an important step to get all possible data from a document.

Hello developers!

I submitted for the contest a solution that would allow organizing message notifications and providing information to users of the messenger Telegam. This is achieved by creating two bots: an administrator and an informant. The administrator manages the list of users connected to the bot informator and their access rights.

The Solution based on project
https://github.com/intersystems-community/TelegramAlerts

My team is working on redesigning an Interoperability solution that currently runs on a HealthShare server that is part of a mirror. Most of the messages are delimited records processed using Complex Record Mapping. We were told to utilize cloud services available in AWS, use containers, autoscaling…

Hi Community,

OpenAPI-Client Gen has just released, this is an application to create an IRIS Interoperability Production client from Swagger 2.0 specification.

Instead of the existing tool ^%REST that creates a server-side REST application, OpenAPI-Client Gen creates a complete REST Interoperability Production client template.

Install by ZPM:

The productions are components developed with InterSystems IRIS Interoperability module to promote integrations between systems, data sources/targets, web services, API, message channels, etc. Productions are composed by:

1) Business services to get/ingest/get data events or requests;

2) Business operations to send or persist data to repositories, systems, API, web services, etc; and

3) BPL - BPEL flows to orchestrate, mediate, compose and route data from business services to business operations.

Moving over from Studio To VSCode like many other will do now the ObjectScript plugin reached version 1.0, I noticed I was missing some items in the objectscript explorer. For example when creating a Rest API using the spec first approach, 3 classes are generated, an application.impl, application.disp and application.spec class, but the disp class was missing in the Object Explorer.

As the application.disp is a generated class, for showing these classes you need to turn this on by hitting the switch on the object explorer:

It's a wrap! All of the focus sessions have aired now. Of course, all of our 102 pre-recorded focus sessions are available on-demand now, so you can watch any and all of them, even if you missed the opportunity for live Q&A.

The second week of Virtual Summit 2020 kicked off with the first day of focus sessions. We covered a LOT of great content - 38 sessions across a wide range of subjects. I thought it would be valuable to recap and review some of the bigger announcements and talking points.

The aim of my question is to achieve this :

• User with authorization :

• User without authorization :

You can notice that some information of the PID segment are obfuscated.

As we all well know, InterSystems IRIS has an extensive range of tools for improving the scalability of application systems. In particular, much has been done to facilitate the parallel processing of data, including the use of parallelism in SQL query processing and the most attention-grabbing feature of IRIS: sharding. However, many mature developments that started back in Caché and have been carried over into IRIS actively use the multi-model features of this DBMS, which are understood as allowing the coexistence of different data models within a single database. For example, the HIS qMS database contains both semantic relational (electronic medical records) as well as traditional relational (interaction with PACS) and hierarchical data models (laboratory data and integration with other systems). Most of the listed models are implemented using SP.ARM's qWORD tool (a mini-DBMS that is based on direct access to globals). Therefore, unfortunately, it is not possible to use the new capabilities of parallel query processing for scaling, since these queries do not use IRIS SQL access.

Meanwhile, as the size of the database grows, most of the problems inherent to large relational databases become right for non-relational ones. So, this is a major reason why we are interested in parallel data processing as one of the tools that can be used for scaling.

In this article, I would like to discuss those aspects of parallel data processing that I have been dealing with over the years when solving tasks that are rarely mentioned in discussions of Big Data. I am going to be focusing on the technological transformation of databases, or, rather, technologies for transforming databases.

IRIS Community Edition Installation Process.

Hello there developers,

Swift-FHIR-Iris

iOS app to export HealthKit data to InterSystems IRIS for Health (or any FHIR repository)