Easily transform a CSV file into a personalized preview of DeepSee - InterSystems BI

AnalyzeThis can be found on InterSystems Open Exchange. Use the Download link to navigate to GitHub and begin installing the project. Follow the “Installation” section of the GitHub README.

The Caché / Ensemble standard distribution contains in namespace SAMPLES
a nice example of a CSP page consuming WebService as a Client.
I have modified it not only to display the replies but to feed them back into a Global.
I used the classic Hyperevent to achieve this. The replies end up as a log in global^WSREPLY.
When there is no input anymore the page closes and goes away.

There are 2 versions with visible and hidden display during operation.
dc.WSCSP.reverseVerbose.cls and dc.WSCSP.reverseHidden.cls

Last week saw the launch of the InterSystems IRIS Data Platform in sunny California.

For the engaging eXPerience Labs (XP-Labs) training sessions, my first customer and favourite department (Learning Services), was working hard assisting and supporting us all behind the scene.

Introduction

Hello! In this article, I will be discussing database degrade, a type of data integrity issue one can face when using IRIS. First, I will be going over a review of the structure of IRIS databases. I'll then discuss how database degrade can manifest and common causes of degrade issues. I'll then conclude with general tips we give our customers about how to prevent or prepare for database degrade issues.

What I find really useful about IRIS when teaching my subject of Postrelational databases is the fact that it is a multi model database. Which means that I can actually go into architecture and structure and all that only once but then show the usage of different models (like object, document, hierarchy) using the same language and approach. And it is not a huge leap to go from an object oriented programming language (like C#, Java etc) to an object oriented database.

However, along with advantages (which are many) come some drawbacks when we switch from object oriented model to relational. When I say that you can get access to the same data using different models I need to also explain how it is possible to work with lists and arrays from object model in relational table. With arrays it is very simple - by default they are represented as separate tables and that's the end of it. With lists - it's harder because by default it's a string. But one still wants to do something about it without damaging the structure and making this list unreadable in the object model.

So in this article I will showcase a couple of predicates and a function that are useful when working with lists, and not just as fields.

Recently, the question came up while discussing the access to the data stored in IRIS from different languages with my students if it was possible to initiate the connection and get data from Cloud solution (InterSystems IRIS CloudSQL) from Microsoft Excel, not the other way around. Considering the many varied ways one can get data in Excel (import data from external sources, connecting to databases using ODBC drivers, using power queries and web queries etc.) the obvious choice was to try ODBC driver. The only task left was to try to connect to the database in the cloud using the ODBC driver.

In recent versions of IRIS, a powerful new data loading command has been introduced to SQL: LOAD DATA. This feature has been highly optimized to import data into IRIS extremely fast, allowing hundreds of gigabytes of data to be inserted in seconds instead of hours or days.

This is a very exciting improvement. However, a big problem in the data loading experience still exists. Namely, the time and hassle it takes to:

One of the most common kinds of integration we are asked to do is emailing. One of the most typical email services our customers use is Microsoft’s Office 365. After setting up the right configuration on the Microsoft side, we can email from IRIS with two HTTP requests.

Hello IRIS Community,

InterSystems Certification is developing a certification exam for InterSystems IRIS SQL specialists, and if you match the exam candidate description given below, we would like you to beta test the exam. The exam will be available for beta testing on June 9 - 12, 2024 at InterSystems Global Summit 2024, but only for Summit registrants (visit this page to learn more about Certification at GS24). Beta testing will open for all other interested beta testers on June 24, 2024. However, interested beta testers should sign up now by emailing certification@intersystems.com (please let us know if you will be beta testing at Global Summit or in our online proctored environment). The beta testing must be completed by August 2, 2024.

BPL from 10,000 feet

BPL stands for Business Process Language.
This is an XML format for describing complex information orchestration interactions between systems.
InterSystems Integration engine has for two decades, provided a visual designer to build, configure, and maintain, BPL using a graphical interface.
Think of it like drawing a process flow diagram that can be compiled and deployed.

Hi everyone.

This is a full example how to use a %ScrollableResultSet for results pagination using %DynamicQuery:SQL and build a JSON response including page details.

Feel free to use, share, comment or improve it.

Kind Regards

There is an interesting new feature in the recently announced 2024.1 preview, JSON_TABLE. JSON_TABLE is one of a family of functions introduced by the 2016 version of the SQL Standard (ISO Standard, published in early 2017). It allows for JSON values to be mapped to columns and queried using SQL. JSON_TABLE is valid in the FROM clause of some SQL statements.

The syntax of JSON_TABLE is quite large, allowing for exceptional conditions where the provided JSON values don't match expectations, nested structures and so on.

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

• Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
• Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
• Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.