Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

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Creating information dashboards, pivot tables, and widgets is an important step in analysis that provides valuable sources of information for informed decision-making. The IRIS BI platform offers many opportunities to create and customize these elements. In this article, we will take a closer look at the basic techniques for developing them and the importance of using them.

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When analyzing data, there is often a need to look at specific indicators more thoroughly and to highlight sections of information of particular interest to a user.

For instance, examining the data dynamics for specific regions or dates can help us uncover some hidden trends and patterns that will allow us to make an informed decision about our project in the future.

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As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:

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Hi Developers!

Often solutions with InterSystems IRIS BI can turn into a quite big solution with dozens of pivots and dashboards.

With every new IRIS BI solution release we can add changes that could influence the behavior of existing pivots or dashboards so they stop working. For example if we change the dimension or measure name, forget deploying some cubes or subject areas, conduct refactoring via mass renaming of cubes and its elements etc some widgets could stop functioning.

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Article
· Feb 3, 2023 3m read
Queue monitoring

Overview

With the gradual improvement of hospital information construction, there are more and more business interfaces in hospitals. Due to the influence of various factors (network, consumer system, etc.), the data processing of business interface may cause excessive message accumulation and even the situation of interface card congestion, which affects the normal business development in the hospital. Therefore, the monitoring of the queue of business interface components becomes more and more important.

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Article
· Feb 7, 2023 3m read
IRIS Queue monitoring component

1. Overview

With more and more hospital applications built, business interface data processing may be affected by a variety of factors (network, consumer systems, etc.), there is an excessive accumulation of messages or even cause interface lag, affecting the routine performance of hospital IT systems , so the monitoring of the business interface components queue is increasingly important.

While current Intersystems IRIS platform's built-in queue monitoring only displays real-time queue information for interface components, which is limited in providing the queue data information needed by hospitals. The queue monitoring component program is based on the Intersystems IRIS platform and can monitor all interface components and display component queue information within 24h of the component, as well as query component historical queue data by setting a time period to better meet the needs of current in-hospital applications.

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IRIS BI

We offer you to embed business intelligence into your applications in order to give your users an opportunity to ask and answer sophisticated questions about their data. Typically, your application will include customizable dashboards that can provide insight into data from Business Intelligence models known as cubes.

In contrast with traditional BI systems that use static data warehouses, Business Intelligence keeps being constantly synchronized with the live transactional data.

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Today we will talk about Adaptive Analytics. This is a system that allows you to receive data from various sources with a relativistic data structure and create OLAP cubes based on this data. This system also provides the ability to filter and aggregate data and has mechanisms to speed up the work of analytical queries.

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When we work with IRIS, we usually have the ability to quickly deploy a ready-to-use infrastructure for BI (data, analytical cubes, and IRIS BI dashboards) using modules. When we start using Adaptive Analytics, we typically want to have the same functionality. Adaptive Analytics has all the tools that we need. The documentation contains a description of how to work with an open web API. All interactions between the user interface and the engine also occur via the internal web API and can be emitted.

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When we are at the starting stage of BI project development, we must remember that it is crucial to select the right tool for its implementation. Today we want to show you how one of the principal functionality of dashboards is implemented in different BI systems. Let's talk about drill down from both points of view: the dashboard development, and the convenience and clarity for the end user. We will touch on the applications of this technology in IRIS BI, Power BI and Tableau.

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Article
· Sep 9, 2022 1m read
DC Analytics Open Application

InterSystems Developer Community analytics. Project made with InterSystems IRIS BI (DeepSee), Power BI and Logi Report Designer to visualize and analyze members, articles, questions, answers, views and other pieces of content and activity on InterSystems Developer Community.

You can see your own activity, articles and questions. Track how your contribution changes developer community.

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Power BI dashboards provide us with a good way to analyze aggregated information. We can even choose time periods for aggregation (you can find more details regarding it in our article about drill down). However, we might still be interested in a detailed look at specific data points. With the right data filling, we can display detailed data for any column of the chart with all filters applied to that chart.

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InterSystems IRIS Business Intelligence allows you to keep your cubes up to date in multiple ways. This article will cover building vs synchronizing. There are also ways to manually keep cubes up to date, but these are very special cases and almost always cubes are kept current by building or synchronizing.

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What is Selective Build?

Selective Build is a BI feature in InterSystems IRIS (introduced in version 2020.1). Selective Build allows you to build specific elements of your cube while keeping your cube online.

What is special about Selective Build?

Before getting into the details of Selective Build, a brief recap of the different phases during a regular cube build is important. Here are the phases in a regular cube build:
1) Delete existing data in cube
2) Populate cube with full set of data
3) Build all indices in the cube

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Article
· Nov 26, 2019 3m read
Designing valid hierarchies in DeepSee

When designing a hierarchy in DeepSee, a child member must have only one parent member. In the case where a child corresponds to two parents, the results can become unreliable. In the case where two similar members exist, their keys must be changed so that they are unique. We will take a look at two examples to see when this happens and how to prevent it.

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I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.

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Article
· Sep 11, 2021 5m read
iris-analytics-for-money

I regret getting a late start in the InterSystems Analytics contest. I had tried a couple of times before to use Analytics, but I had not gotten too far. I have been recording financial transactions in Excel workbook ever since I had to retire Microsoft Money. Since my iris-for-money was not fully functional, I created a worksheet per account I was tracking. I had developed a CSP page in iris-for-money to import transactions by reading a CSV file.

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Previously I have already tried to play with Google Data Studio when I connected it to InterSystems FHIRaaS. It has quite a nice UI, with a few chart types available out of the box, it can be quite easily connected to some plain tables (stored as CSV or JSON, for instance), and gives the ability to build quite flexible analytics over it. So, I have decided to implement a new connector to InterSystems Analytics (DeepSee), with the ability to select a cube and do some queries on it.

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Article
· Aug 13, 2021 4m read
Building Analytics Solution with IRIS

Hi developers!

How to build an analytics solution with InterSystems IRIS?

To begin with, let's agree on the points of what is the analytics solution - and this could be a very wide topic. Let's limit the set of solutions to those you can present in the Analytics contest.

There are three kinds of analytics solutions that we will review here: monitoring, interactive analytics, and reporting.

Monitoring

The typical monitoring solution consists of an online dashboard with KPIs that are being actively updated.

The key use case is of monitoring is to visually observe the KPI of fresh data every moment to react in case of an emergency.

Interactive Analytics

This solution supposes a set of interactive dashboards with filters and drill-downs.

The key use case is to explore the data with filters and drill-downs making business decisions upon graph and table data visualization.

Reporting

Reporting solution provides a set of static (usually) reports in a form of HTML or pdf documents that deliver the data in graph and text form in a predesigned form and could be sent via email.

The typical use case of a reporting system is to obtain reports on a given period that will illustrate the status of the product, process, service, sales, etc that is crucial for the business.

How InterSystems products could be used to build such solutions? Let's discuss this below!

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When you have been using cubes for business intelligence in a namespace for some time, you may find that there are many cubes in the namespace, only some of which are actively being used. However, it can be difficult to tell which cubes users are or are not querying, and maintaining unused cubes can be costly both in terms of storage and of computation to keep them up to date. This article provides some suggestions and examples for monitoring which cubes are in active use, and for removing cubes that you determine are no longer necessary.

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Hi colleagues!

Every day Johns Hopkins University publishes new data on coronavirus COVID-19 pandemic status.

I built a simple InterSystems IRIS Analytics dashboard using InterSystems IRIS Community Edition in docker deployed on GCP Kubernetes which shows key measures of the disease outbreak.

This dashboard is an example of how information from CSV could be analyzed with IRIS Analytics and deployed to GCP Kubernetes in a form of InterSystems IRIS Community Edition.

Added the interactive map of the USA:

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