#Analytics

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This tag relates to the discussions on the development of analytics and business intelligence solutions, visualization, KPI and other business metrics management.

Running predictive models natively in an InterSystems IRIS Business Process has of course always been the goal of our PMML support, but somehow never made it into the kit because there were a few dependencies and choices that needed addressing and answering. Anyhow, thanks to some pushing and code kindly provided by @Amir Samary (Thanks again Amir!), we finally got it wrapped in a GitHub repo for your enjoyment, review and suggestions.

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The following post outlines an architectural design of intermediate complexity for DeepSee. As in the previous example, this implementation includes separate databases for storing the DeepSee cache, DeepSee implementation and settings. This post introduces two new databases: the first to store the globals needed for synchronization, the second to store fact tables and indices.

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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.

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The following post outlines a more flexible architectural design for DeepSee. As in the previous example, this implementation includes separate databases for storing the DeepSee cache, DeepSee implementation and settings, and synchronization globals. This example introduces one new databases to store the DeepSee indices. We will redefine the global mappings so that the DeepSee indices are not mapped together with the fact and dimension tables.

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The source class of a DeepSee cube has a property referencing a different class:

Class ClassA Extends %Persistent {
     Property P1 As ClassB;
}

When records in class B change, the ^OBJ.DSTIME global for Class A will not be automatically updated. This means that synchronization of cubes based on source class A will not reflect the changes occurred to property P1.
This post will help you determine the best way to achieve synchronization of properties referencing a different class

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Hi, Community!

I’m sure you are using Developer Community analytics built with InterSystems Analytics technology DeepSee:

You can find DC analytics n InterSystems->Analytics menu.

DC Analytics shows interactive dashboards on key figures of DC entities: Posts, Comments, and Members. 

Since the last week, this analytics project is available for everyone with source code and data on DC Github!

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I was approached recently by and end use who wanted to perform analysis of their databases and see how they could save some space by picking data good for deletion without harming the application. As part of investigation, they wanted to know sizes of globals within datasets. This can be achieved by various means but all of them provide data in text form only.

I thought I might be a good tool for database administrators in general - to see global sizes in a graphical way.

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With the release of InterSystems IRIS, we're also making available a nifty bit of software that allows you to get the best out of your InterSystems IRIS cluster when working with Apache Spark for data processing, machine learning and other data-heavy fun. Let's take a closer look at how we're making your life as a Data Scientist easier, as you're probably already facing tough big data challenges already, just from the influx of job offers in your inbox!

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Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

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Hi, Community! 

This is the 3rd part of DeepSee Web story - Angular base UI for DeepSee Dashboards, see the beginning here.

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By design, DSW provides an implementation for every widget in DeepSee library. But there are some extra features in DSW which make solutions built with DSW dashboards more functional.  This article describes it.

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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.

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Hi, Community!

In the second part about DeepSee Web, I’ll describe what customization options you have with DSW.  

There are two types of customizations: widget customization and dashboard panel customization.

Example of dashboard customization on Developer Community analytics.

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System Monitor is a flexible and highly configurable tool supplied with Caché (Ensemble, HealthShare), which collects the essential metrics of the operating system and Caché itself. System Monitor also notifies administrators about issues with Caché and the operating system, when one or several parameters reach the admin-defined thresholds.

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Article
Michelle Stolwyk · May 25, 2017 2m read
The Interns are Coming!

The Data Platforms department here at InterSystems is gearing up for this year's crop of interns, and I for one am very excited to meet them all next week!

We've got folks from top technical colleges with diverse specialties from hard core engineers to pure computer scientists to mathematicians to business professionals. They come from countries around the world like Vietnam, China, and Finland and they all come with impressive backgrounds. We're sure they will do very well this summer.

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How are we doing THIS year versus the same period LAST year? 
This is a common need in Business Intelligence. In fact, many design specifications for reports make use of a comparison between a selected period (year, quarter, etc) up to a certain date (for example November 15th, 2016) and a summary of the same information for the previous year (i.e. up to November 15th, 2015). 
This post shows how to implement this in DeepSee.

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Whether you are accessing DeepSee for the first time ever or you are configuring DeepSee on a new instance, there are two common issues that are encountered after clicking on the “DeepSee” option in the System Management Portal.

Issue #1: Architect/Analyzer is grayed out!

Issue #2: DeepSee must be enabled before use.

Issue #1: Architect/Analyzer is grayed out!

There are two common causes for this problem.

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I've asked a lot of questions leading up to this, so I wanted to share some of my progress.

The blue line represents the number of messages processed.  The background color represents the average response time.  You can see ticks for each hour (and bigger ticks for each day).   Hovering over any point in the graph will show you the numbers for that period in time.

This is super useful for "at a glance" performance monitoring as well as establishing patterns in our utilization.

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This article contains the tutorial document for a Global Summit academy session on Text Categorization and provides a helpful starting point to learn about Text Categorization and how iKnow can help you to implement Text Categorization models. This document was originally prepared by Kerry Kirkham and Max Vershinin and should work based on the sample data provided in the SAMPLES namespace.

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