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Asaf Sinay
Senior Support Manager | Analytics Technologies SME at InterSystems Corporation
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Announcement Asaf Sinay · Sep 18, 2025

InterSystems IRIS BI Tips & Tricks!

#InterSystems IRIS #HealthShare #InterSystems IRIS BI (DeepSee) #InterSystems IRIS for Health #Analytics #Cubes #Dashboards #Data Model #MDX #Tips & Tricks

Ready to elevate your Business Intelligence game?

We've got an engaging video, perfect for all skill levels.

Discover how to get started with IRIS BI, optimize cube performance, and drive analytics adoption. Plus, get a sneak peek at what's next!

[BONUS] If you watch it on YouTube, they added an Ask AI button    Image  If you click on it, it opens a chat on the right side of the video and lets you ask questions about the video's content, pretty cool! 

Discussion (3)3
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Comments

Asaf Sinay · Sep 18, 2025

This video provides tips and tricks for using InterSystems IRIS Business Intelligence (BI), covering three main scenarios:

  • Getting Started with IRIS BI: Learn about initial considerations, roles, and available learning resources like the IRIS BI Analyzer for data exploration, filters, and pivot tables. (4:10)
  • Optimizing Cube Build Efficiency: Understand factors affecting performance, such as data volumes, cube design, hardware, and indexing. Discover ways to improve efficiency through system configuration, code optimization, and selective data processing. (17:03)
  • Increasing Analytics Adoption: Explore methods for auditing system usage and MDX queries to gain insights into how users interact with your BI solution. (28:49)

The presenters also discuss future enhancements focused on improving cube building, filtering, and query speeds. (35:10)

Key takeaways: The video emphasizes assessing your organization's BI maturity, leveraging available learning resources, optimizing your cube builds for better performance, and using auditing to understand and improve user adoption of your analytics solutions.

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Stephen Canzano · Sep 22, 2025

There were several questions asked during the pressentation.  One of them was 

 How can we restrict usage of the cubes so that we only allow users to specific data?

If this were SQL one way of approaching this is to define a View and then grant access to the View but not the table to users.  Fortunately Analytics has the same concept. Just as SQL tables are the resource that has the data and a view is defined representation of the data, Analytics has Cubes which has the data and Subject Areas.  

A subject is a virtual view of the cube but does not require the additional storage/build/sync time.  Within the Subject Area you can

1. Define a filter, consider we want to define a subject on Senior Citizens, we would define a filter on Age > X.  Then when we make the Senior Citizen Subject area to a user they will only ever see patients > X,

2. Define what dimensions are available 

3. Define listings

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Robert Cemper · Sep 22, 2025

Hi @Asaf Sinay 

It was just by accident that I completed my untypical use of DeepSee:
After >12 years, I  took some time to get in again.
But I should say Documentation and Examples are excellent to get up to speed.
👍

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