Presenter: Benjamin De Boe
Task: Perform advanced analytics on huge amounts of data
Approach: Use third-party analytics frameworks to leverage your entire clustered environment

In this session, we’ll explain what machine learning means and how it can help you gain insights in vast amounts of data, leveraging complex environments.

Content related to this session, including slides, video and additional learning content can be found here.

After upgrading an Information Exchange/HealthShare instance that has a registry namespace, you may notice that the Caché audit log gets filled with frequent login failures by the HS_Services user (check this by going to Management Portal > System Administration > Security > Auditing > View Audit Database). Clicking the “details” shows event data like:

Error message: Access Denied
CSP Application: /csp/healthshare/hsregistry
Authentication: Delegated

In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph.
Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.

HealthShare HealthConnect and Information Exchange version 15.03 support import transformations from C-CDA 2.1 to SDA. You can find these transforms in your installation's csp/xslt/SDA3 directory. For general information about import transforms, see "CDA Documents and XSL Transforms in HealthShare" in Overview of Health Connect.

Among the enhancements to import functionality added in connection with C-CDA 2.1 support is the ability to preprocess your C-CDA input files prior to the transformation done for import.

... but let’s first look at error handling.

In part 1, part 2, and part 3 parts of this series we set up three user types. In part 4 we saw how to secure model elements and DeepSee items. In this last part of the tutorial we conclude with some remarks on DeepSee security and troubleshooting tips. In particular, we see how pivot tables in User Portal can be "hidden".

Users of analytical applications often need to generate and send out PDF reports comprised of elements of the analytical panel. In the InterSystems stack, this task is solved using the DSW Reports project that is an extension of DeepSeeWeb. In this article, we will explain how to use DSW Reports for generating PDF reports and emailing them.

The client part of the code for this game is on the MS Excel sheet and consists of:

Hi All,

With this article, I would like to show you how easily and dynamically System Alerting and Monitoring (or SAM for short) can be configured. The use case could be that of a fast and agile CI/CD provisioning pipeline where you want to run your unit-tests but also stress-tests and you would want to quickly be able to see if those tests are successful or how they are stressing the systems and your application (the InterSystems IRIS backend SAM API is extendable for your APM implementation).

Setting up Management Portal Help Pages for Full WebServers

On each page of the System Management Portal, there is a “Help” button. This takes users to an article in documentation that describes the page functionality and use.

Caché provides local documentation for all of these articles.

InterSystems IRIS does not provide local documentation. Instead, the Help button will redirect users to the articles in the online documentation at docs.intersystems.com.

Purpose

Most CloudFormation articles are Linux-based (no wonder), but there seems to be a demand for automation for Windows as well. Based on this original article by Anton, I implemented an example of deploying a mirror cluster to Windows servers using CloudFormation.I also added a simple walk through.
The complete source code can be found here.

Update: 2021 March 1 I added a way to connect to Windows shell by public key authentication via a bastion host as a one-liner.

Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.