Overview

Encryption of sensitive data becomes more and more important for applications. For example patient names, SSN, address-data or credit card-numbers etc..

Cache supports different flavors of encryption. Block-level database encryption and data-element encryption. The block-level database encryption protects an entire database.  The decryption/encryption is done when a block is written/read to or from the database and has very little impact on the performance.

With data-element encryption only certain data-fields are encrypted.  Fields that contain sensitive data like patient data or credit-card numbers. Data-element encryption is also useful if a re-encryption is required periodically. With data-element encryption it is the responsibility of the application to encrypt/decrypt the data.

Both encryption methods leverage the managed key encryption infrastructure of Caché.

The following article describes a sample use-case where data-element encryption is used to encrypt person data.  

But what if you have hundreds of thousands of records with an encrypted datafield and you have the need to search that field? Decryption of the field-values prior to the search is not an option. What about indices?

This article describes a possible solution and develops step-by-step a small example how you can use SQL and indices to search encrypted fields. 

If I have defined a class query in one of my classes and I want to use that query from a method of another class, what are the pros and cons of using the %SQL.Statement interface versus the %Library.ResultSet interface?

I believe %SQL.Statement is the newer interface.

So if the old way is:

USER>s rs=##class(%Library.ResultSet).%New("%Library.File:FileSet")
 
USER>s sc=rs.Execute("c:\s\","*.txt")
 
USER>w sc
1
USER>while rs.%Next() {w !,rs.Data("Name")}

...

then the new way is:

Keywords:  IRIS, IntegratedML, Flask, FastAPI, Tensorflow Serving, HAProxy, Docker, Covid-19

Does anyone NOT use a debugger? I can't remember the last time I did. It's not because I don't dislike them, I just don't need to use them. The main reason for this is because I have a certain development methodology that either produces less bugs, catches them at a unit test level, or makes tracking them down much easier.

Here are my tips...

1. Write your own COS cheat-sheet.

There's plenty of goodness in the %-packages InterSystems supplies, and it seems that every new version of Caché brings something new. The browser-based class documentation (a.k.a. Documatic) generally provides a good level of information, but on the basis that "a picture is worth a thousand words" I sometimes want a diagram.

For example, when trying to navigate the %Dictionary package for a project that needed to find out about class definitions, here's one of the UML class diagrams I created.

For Global Summit 2016, I set out to showcase a Reference Architecture I had been working on for a National Provider Directory solution with State Level Instances and a National Instance all running HealthShare Provider Directory and all running on AWS Infrastructure.

In short, I wanted to highlight:

• The implementation of Amazon Web Services to provision the infrastructure, including the auto-creation of the state level instances through Cloud Formation.
• The use of the HSPD Broadcast functionality to Notify Upstream Systems Changes in Master Provider Data.
• The implementation of a transformation of the standard Broadcast Object to HL7 MFN for interoperability.
• The principals of Master Data Management applied to the Provider Directory.

Preface: our small, but very ambitious company called “Black Mushroom Studio” came up with an idea for an e-commerce project and a mobile app that would let users pay for certain goods/services via a payment aggregator.

What we had initially: an Android app skeleton that, of course, liked communicating via HTTP and JSON, and a payment system with an API – web services with SOAP content.

Goal: make it all work together.

Preface

Before we begin, I'd like to mention that I am by no means an Ensemble expert, so take this with a grain of salt and please feel free to offer any suggestions for improvement. That being said, I have enjoyed working with Ensemble and wanted to share the approach I took to poll an external REST API for patient data in the hopes that it might help others with a similar goal.

Hi folks,

I've created a datatype class whoch extends from %Library.String with a REGEX parameter and the validation of the value against the regular expression. The class does not support Populate using the regular expression as a template for data population.

InterSystems' iKnow technology allows you to identify the concepts in natural language texts and the relations that link them together. As that's still a fairly abstract definition, we produced this video to explain what that means in more detail. But when meeting with customers, what really counts is a compelling demonstration, on data that makes sense to them, so they understand the value in identifying these concepts over classic top-down approaches. That's why it's probably worth spending a few articles on some of the demo apps and tools we've built to work with iKnow. 

In the first article in this series, we'll start with the Knowledge Portal, a simple query interface to explore the contents of your domain.

Last week, we announced the InterSystems IRIS Data Platform, our new and comprehensive platform for all your data endeavours, whether transactional, analytics or both. We've included many of the features our customers know and loved from Caché and Ensemble, but in this article we'll shed a little more light on one of the new capabilities of the platform: SQL Sharding, a powerful new feature in our scalability story.

This is a  rather personal view on the history before Caché.
It is in no sense meant to compete with the excellent books from Mike Kadow  discussed in an earlier article.
We have different history and so this is meant to create a different prospective of the past.

If you want to start IRIS as a service on CentOS7 you can use systemd.

Login as root and create a new file iris.service in /etc/systemd/system.

After a five-part series on sample iKnow applications (parts 1, 2, 3, 4, 5), let's turn to a new feature coming up in 2017.1: the iKnow REST APIs, allowing you to develop rich web and mobile applications. Where iKnow's core COS APIs already had 1:1 projections in SQL and SOAP, we're now making them available through a RESTful service as well, in which we're trying to offer more functionality and richer results with fewer buttons and less method calls. This article will take you through the API in detail, explaining the basic principles we used when defining them and exploring the most important ones to get started.