This year's Virtual Summit has more content around Analytics and AI than ever before. We've made this quick video to guide you through the program and put things into context with respect to InterSystems overall strategy for Data & Analytics.

https://www.youtube.com/embed/fTcNimWi2y0
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Announcement
· Aug 20, 2020
SQL Monitoring survey

Hi,

As part of our continuous efforts to expand and improve the InterSystems IRIS Data Platform, we’ve set up a brief survey around SQL monitoring. Your feedback will help us in designing and developing the right tools for the job and improve the platform’s overall ease-of-use. Please use the link below to access the survey, which should only take around 5 minutes to complete.

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InterSystems IRIS 2020.1 brings a broad set of improved and new capabilities to help build important applications. In addition to the many significant performance improvements accrued through 2019.1 and 2020.1, we are introducing one of our biggest changes in recent SQL history: the Universal Query Cache. This article provides more context on its impact to SQL-based applications at a technical level.

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Hi,

we're planning some work on our SQL Query Plan functionality for a future release of InterSystems IRIS and are interested to hear how you're using them today, or what'd keep you from using them. Rather than try and fit everything in a rigid survey, I thought a simple thread on our beloved DC might also reveal some use patterns that we support or could do a better job on.

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Hi,

While we're working on a new data product supporting the analytics development process, we'd like to test some of the UX (User eXperience) design elements on a real audience. If you've got some battle scars from earlier analytics work and are interested in participating, please complete this survey and we'll get in touch when we have something to show!

Feel free to share this survey with your data-savvy friends and colleagues if you think they match the profile.

Thanks in advance for your participation!

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Announcement
· Mar 15, 2019
SQL Developer Experience survey

Hi all,

In order to prioritize functional requirements for evolving our SQL developer experience, we have prepared a short survey to better understand how you’re currently using and, in an ideal world, would like most to interact with our SQL platform.

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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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Hi,

As we announced at our Global Summit in October, we are developing dedicated connectors for a number of third-party data visualization tools for InterSystems IRIS. With these connectors, we want to combine an excellent user experience with optimal performance when using those tools to visualize data managed on InterSystems IRIS Data Platform.

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We’re now less than a month away from our annual conference, the InterSystems Global Summit. This year, we’ll be descending on the beautiful outskirts of San Antonio, a city worth visiting for its wonderful river walkway and its 18th century Spanish Mission, even if it hadn’t been the location of this year’s InterSystems event. Leaving the tourist guidance to the tourist guides, let’s take a closer look at what the conference has in stock for you, including a dedicated post-summit symposium on AI and ML on Wednesday October 3!

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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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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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If you've worked with iKnow domain definitions, you know they allow you to easily define multiple data locations iKnow needs to fetch its data from when building a domain. If you've worked with DeepSee cube definitions, you'll know how they tie your cube to a source table and allow you to not just build your cube, but also synchronize it, only updating the facts that actually changed since the last time you built or synced the cube. As iKnow also supports loading from non-table data sources like files, globals and RSS feeds, the same tight synchronization link doesn't come out of the box. In this article, we'll explore two approaches for modelling DeepSee-like synchronization from table data locations using callbacks and other features of the iKnow domain definition infrastructure.

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This earlier article already announced the new iKnow REST APIs that are included in the 2017.1 release, but since then we've added extensive documentation for those APIs through the OpenAPI Specification (aka Swagger), which you'll find in the current 2017.1 release candidate. Without wanting to repeat much detail on how the APIs are organised, this article will show you how you can consult that elaborate documentation easily with Swagger-UI, an open source utility that reads OpenAPI specs and uses it to generate a very helpful GUI on top of your API.

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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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In previous articles on iKnow, we described a number of demo applications (iKnow demo apps parts 1, 2, 3, 4 & 5) that are either part of the regular kit or can be easily installed from GitHub. All of those applications assumed you already had your iKnow domain ready, with your data of interest loaded and ready for exploration. In this article, we'll shed more light on how exactly you can get to that stage: how you define and then build a domain.

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Article
· Jul 4, 2016 8m read
Introduction to the iKnow REST APIs

After a five-part series on sample iKnow applications (parts 1, 2, 3, 4, 5), let's turn to a new feature coming up in 2017.1: the iKnow REST APIs, allowing you to develop rich web and mobile applications. Where iKnow's core COS APIs already had 1:1 projections in SQL and SOAP, we're now making them available through a RESTful service as well, in which we're trying to offer more functionality and richer results with fewer buttons and less method calls. This article will take you through the API in detail, explaining the basic principles we used when defining them and exploring the most important ones to get started.

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