The InterSystems IRIS has a very nice container class to allows you have your Dashboards as classes source code. It is %DeepSee.UserLibrary.Container.

With this class is possible group all your dashboard and pivot table definitions.

This is useful to automatically create your dashboards when you build your docker project and other automation scenarios.

See:

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Today, is important analyze the content into portals and websites to get informed, analyze the concorrents, analyze trends, the richness and scope of content of websites. To do this, you can alocate people to read thousand of pages and spend much money or use a crawler to extract website content and execute NLP on it. You will get all necessary insights to analyze and make precise decisions in a few minutes.

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Hi guys!

I'd like to present you my new project: iris-analytics-notebook, a notebook approach to use IRIS analytics capabilities.

Project description

In past few years, notebooks tools like Jupyter are gaining popularity due its natural way to express ideias.

An almost unipresent tool for data scientists, notebook can also help to improve the impact of analytics tools for all sort of users.

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Web Crawling is a technique used to extract root and related content (HTML, Videos, Images, etc.) from websites to your local disk. This is allows you apply NLP to analyze the content and get important insights. This article detail how to do web crawling and NLP.

To do web crawling you can choose a tool in Java or Python. In my case I'm using Crawler4J. (https://github.com/yasserg/crawler4j).

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Article
Yuri Marx · Nov 20, 2020 2m read
Enrich your analytics projects with NLP

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:

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Hi guys.

Recently, I get interest in FHIR in order to run for the IRIS for Health FHIR
contest
. As a beginner on this topic, I've heard somewhat about it, but I didn't know how complex and powerful was FHIR. As pointed out by @Henrique Dias here, you can model several aspects of the patient history and other related entities.

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Article
Evgeny Shvarov · Aug 2, 2020 1m read
Application Errors Analytics

Hi Developers!

As you know the application errors live in ^ERRORS global. They appear there if you call:

d e.Log() 

in a Catch section of Try-Catch.

With @Robert Cemper's approach, you can now use SQL to examine it.

Inspired by Robert's module I introduced a simple IRIS Analytics module which shows these errors in a dashboard:

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This is my introduction to a series of posts explaining how to create an end-to-end Machine Learning system.

Starting with one problem

Our IRIS Development Community has several posts without tags or wrong tagged. As the posts keep growing the organization
of each tag and the experience of any community member browsing the subjects tends to decrease.

First solutions in mind

We can think some usual solutions for this scenario, like:

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A few months ago, I read this interesting article from MIT Technology Review, explaing how COVID-19 pandemic are issuing challenges to IT teams worldwide regarding their machine learning (ML) systems.

Such article inspire me to think about how to deal with performance issues after a ML model was deployed.

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Now available on Open Exchange is a library of third party charts available to use within DeepSee/InterSystems IRIS BI dashboards. To start, simply download and install, select the new portlet as the widget type, then select the chart type that you desire. If you don't find the type of chart you are looking for, you can easily extend the portlet to implement your desired chart type. These new chart types can be used within existing dashboards or you can create new dashboards using them.

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Keywords:  PyODBC, unixODBC, IRIS, IntegratedML, Jupyter Notebook, Python 3

 

Purpose

A few months ago I touched on a brief note on "Python JDBC connection into IRIS", and since then I referred to it more frequently than my own scratchpad hidden deep in my PC. Hence, here comes up another 5-minute note on how to make "Python ODBC connection into IRIS".

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Making a Chart using Intersystems IRIS + Python

How to use the IRIS Native API in Python to access globals and plot some charts.

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application.
If you are curious (https://www.python.org/about/apps/)

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In an ever-changing world, companies must innovate to stay competitive. This ensures that they’ll make decisions with agility and safety, aiming for future results with greater accuracy.
Business Intelligence (BI) tools help companies make intelligent decisions instead of relying on trial and error. These intelligent decisions can make the difference between success and failure in the marketplace.
Microsoft Power BI is one of the industry’s leading business intelligence tools. With just a few clicks, Power BI makes it easy for managers and analysts to explore a company’s data. This is important because when data is easy to access and visualize, it’s much more like it’ll be used to make business decisions. 


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There are several options how to deliver user interface(UI) for DeepSee BI solutions. The most common approaches are:

  • use native DeepSee Dashboards, get web UI in Zen and deliver it in your web apps.
  • use DeepSee REST API, get and build your own UI widgets and dashboards.

The 1st approach is good because of the possibility to build BI dashboards without coding relatively fast, but you are limited with preset widgets library which is expandable but with a lot of development efforts.

The 2nd provides you the way to use any comprehensive js framework (D3, Highcharts, etc) to visualize your DeepSee data, but you need to code widgets and dashboards on your own.

Today I want to tell you about yet another approach which combines both listed above and provides Angular based web UI for DeepSee Dashboards -  DeepSee Web library.

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Article
Peter Steiwer · Mar 2, 2020 2m read
SQL -99 error while viewing a listing

This error is sometimes seen while viewing a listing in InterSystems IRIS Business Intelligence:
ERROR #5540: SQLCODE: -99 Message: User <USERNAME> is not privileged for the operation (4)  

As the error suggests, this is due to a permission error. To figure out which permissions are missing/needed, we can take a look at the SQL query that is generated. We will use a query from SAMPLES as an example.

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Preview Mode was added to InterSystems IRIS Business Intelligence to give designers a quick view of what their resulting Pivot Table will look like without needing to wait for the results to fully execute. This can be beneficial when designing pivot tables because if you are dragging and dropping elements to see how they look/work in your pivot table and seeing if they have the desired data. Since you are exploring and designing, you don't necessarily care about the results at the moment, but you would still like to see how your table looks with the changes you have made.

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AnalyzeThis is a tool for getting a personalized preview of your own data inside of InterSystems BI. This allows you to get first hand experience with InterSystems BI and understand the power and value it can bring to your organization. In addition to getting a personalized preview of InterSystems BI through an import of a CSV file with your data, Classes and SQL Queries are now supported as Data Sources in v1.1.0!

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Hello Community,

Thank you all for your continued feedback and support of our ad hoc reporting platform, VDM.  There's been some questions around setting up a non-ODBC connection for InterSystems platforms.  We published a new YouTube video showing the steps necessary to connect to InterSystems Caché and InterSystem IRIS with BridgeWorks VDM. 

 

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In the previous part of this series, we saw how to include data in a portlet from within DeepSee. This used the built in data controller. In this part, we are going to be pulling in data from outside of DeepSee. This will include both information from within InterSystems IRIS and from the OS.

Why use this?

This is useful if you would like to create a dashboard that only contains information about your system. It is also useful if you want to display data about your system along side data that you have stored in DeepSee.

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When using Related Cubes in InterSystems IRIS BI, cubes must be built in the proper order. The One side must be built before the Many side. This is because during build time for the Many side, it looks up the record on the One side and creates a link. If the referenced record is not found on the One side, a Missing Relationship build error is generated. The One side is going to be the independent side of the relationship, AKA the side of the relationship that is referenced by the Many side or the Dependent cube. For example: Patients contain a reference to their Doctor.

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What is %SQLRESTRICT

%SQLRESTRICT is a special %FILTER clause for use in MDX queries in InterSystems IRIS Business Intelligence. Since this function begins with %, it means this is a special MDX extension created by InterSystems. It allows users to insert an SQL statement that will be used to restrict the returned records in the MDX Result Set. This SQL statement must return a set of Source Record IDs to limit the results by. Please see the documentation for more information.

Why is this useful?

This is useful because there are often times users want to restrict the results in their MDX Result Set based on information that is not in their cubes. It may be the case that this information may not make sense to be in the cube. Other times this can be useful when there is a large set of values you want to restrict. As mentioned before, this is not a standard MDX function, it was created by InterSystems to handle cases were queries were not performing well or cases that were not easily solved by existing functions.

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Article
Peter Steiwer · Dec 31, 2019 3m read
Portlets that use data from DeepSee


In the previous part of this series, we saw how to reference a web page that will enhance our dashboard experience.  Now we will look into referencing data that is already in our cubes.

In this example, we will be referencing the controller object and we will be extracting data from it. This data will then be displayed as text in our Dashboard. In Part 5, we will show how to incorporate this data into other charting libraries.

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In the previous part of this series, we saw how to define a basic portlet. Now we will look into making this portlet reference a web page that will enhance our dashboard experience.

In this example, we will be embedding a Developer Community article along side a couple of widgets displaying information related to the number of views on the Developer Community articles. This example is not hosted on the Community Analytics server, but if it was we could see the view counts going up as we interacted with the page.

Why use this?

In a real case, perhaps you have an embedded page from an external web site showing the current Emergency Room wait times for Hospitals in your area. This portlet can be used along side widgets from your Emergency Room showing how many people are waiting, how many doctors are active, and how many people are being treated. As other Emergency Room wait times grow, you can possibly expect your volume to increase as well. This can help you make decisions on how to allocate resources.

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Article
Peter Steiwer · Dec 12, 2019 2m read
Creating Portlets in DeepSee

What is a portlet?

The simple answer is: a custom widget. A portlet can exist by itself on a DeepSee dashboard, it can be used along side standard DeepSee widgets, or along side other portlets. The rendering of the custom widget is completely user defined. This means you can embed a web page, create a form to perform any sort of action needed based on the data on your dashboard, use third party charting libraries, or simply display data from outside of a DeepSee cube.

How to get started

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