The pandemic that struck the world in 2020 made everyone follow the news and the numbers that involve the COVID-19.

Why don’t you take that opportunity to create something simple and pleasant, to follow the number of vaccinations worldwide?

To face this challenge, I'm using the data provided by Our World in Data - Research and data to make progress against the world’s largest problems.

They have a dedicated repository on Github with the data of COVID-19, and I took the vaccination data to help me with my tracker.

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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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Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems Analytics Contest!

Date & Time: Monday, January 4, 2021 – 10:00 EDT

What awaits you at this virtual Meetup? 

  • Our winners' bios.
  • Short demos on their applications.
  • An open discussion about technologies being used, bonuses, questions. Plans for the next contests.

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Hey Developers,

This week is a voting week for the InterSystems Analytics Contest! So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote? 

Please meet the new voting engine and algorithm for the Experts and Community nomination:

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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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Hi everyone, 

I'm creating something to test the Analytics capabilities. 

I have a table with 100k records. Consulting the data using ^%G or SELECT, everything is working fine. 

But, when I create a Cube using this same class as Source, the Build results in only 1 fact.

I would like to know if anyone else faces the same situation before and have some guidance. 

Some details:

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Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems Analytics Contest Kick-off Webinar! The topic of this webinar is dedicated to the Analytics contest.

On this webinar, we’ll demo the iris-analytics-template and answer the questions on how to develop, build, and deploy Analytics applications using InterSystems IRIS.

Date & Time: Monday, December 7 — 12:00 PM EDT

Speakers:  
🗣 @Carmen Logue, InterSystems Product Manager - Analytics and AI
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager


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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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According to IDC, more than 80% of information it is NoSQL, especially text into documents. When the digital services or applications not process all this information, the business lose. To face this challenge, it is possible use OCR technology. OCR uses machine learning and/or trained image patterns to transform image pixels into text. This is important, because many documents are scanned into images inside PDF, or many documents contains images with text inside. So OCR are an important step to get all possible data from a document.

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