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#MDX

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Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL, it is a query language for OLAP cubes.

Hence the question: is there a way to do that?

The goal is to get data (from half a thousand to 3-4 thousands lines) from DB, calculate standart deviation then use it as logical condition in analyzer.

For example IF std > custom_value = show_the_result ELSE null

There is a STDDEV(MDX) method used in Analyzer but it is a measure and it can not be used as logical condition (correct me if i am wrong)

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Hi Community,

I seek your assistance for below scenario.

Scenario-1: How to add filter or where clause while displaying data with listing fields ( I have not used Custom SQL listing to display this data).

For below table, I have created a Cube Student and I have created listing fields of the columns mentioned in the table. Also I have created the pivot and I am able to create the same table as shown below.

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How can I create a calculated member in Analyzer using MDX for the following logic?

WHEN 'F' THEN 'FEMALE'
WHEN 'Female' THEN 'FEMALE'
WHEN 'M' THEN 'MALE'
WHEN 'Male' THEN 'MALE'
WHEN 'U' THEN UNDIFFERENTIATED'
WHEN 'UN' THEN UNDIFFERENTIATED'
WHEN 'Undifferentiated' THEN UNDIFFERENTIATED'
ELSE 'OTHER'
END

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Question
· Oct 6, 2022
MDX Syntax Help

we have this container code where we want to create more CalcMember properties

<sharedCalcMember FullName="HSAAPATIENT||DEMOGRAPHICS||CITIZENSHIP.NATIONAL.sharedCalcMember" Dimension="Demographics" Name="Citizenship.National" Expression="[Demographics].[H10].[Citizenship].&amp;[USA]" SolveOrder="0" CubeName="HSAAPATIENT" UpperCaseDimension="DEMOGRAPHICS" UpperCaseName="CITIZENSHIP.NATIONAL"></sharedCalcMember>

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One of the most important tasks of dashboards is, on the one hand, to help you perceive data in an aggregated form, and, on the other hand, not to lose the depth of immersion in the data if you need this. One of the tools that help us achieve this result is drill down. It enables us to display several hierarchical levels of data, from aggregated to detailed.

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Hey Community,

See how cubes are constructed for use in business intelligence, and learn about SQL and MDX query languages. Physical and virtual cubes are used in InterSystems IRIS® Business Intelligence and Adaptive Analytics:

⏯ Introduction to Cubes in Business Intelligence

https://www.youtube.com/embed/l6XFj1JQ5Fw
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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Let's say I have a persistent class Sales.
I need to create a report that shows the amount of sales for each branch.
By simply using the class Sales for the source of the cube, I can show what I want with one little exception - the branches that did not have any sales are not shown.
Is there a way around that that does not involve creating a whole new table just for this cube or using a Data connector (they have horrible documentation and I am unable to figure out how to use them properly)?

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Hey Developers,

New demo show by InterSystems Manager @Amir Samary is already on InterSystems Developers YouTube:

⏯ InterSystems IRIS: Kafka, Schema Normalization and Service Enablement

https://www.youtube.com/embed/D9PXjn9kyIM
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

Open Exchange app
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Preview Mode was added to InterSystems IRIS Business Intelligence to give designers a quick view of what their resulting Pivot Table will look like without needing to wait for the results to fully execute. This can be beneficial when designing pivot tables because if you are dragging and dropping elements to see how they look/work in your pivot table and seeing if they have the desired data. Since you are exploring and designing, you don't necessarily care about the results at the moment, but you would still like to see how your table looks with the changes you have made.

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What is %SQLRESTRICT

%SQLRESTRICT is a special %FILTER clause for use in MDX queries in InterSystems IRIS Business Intelligence. Since this function begins with %, it means this is a special MDX extension created by InterSystems. It allows users to insert an SQL statement that will be used to restrict the returned records in the MDX Result Set. This SQL statement must return a set of Source Record IDs to limit the results by. Please see the documentation for more information.

Why is this useful?

This is useful because there are often times users want to restrict the results in their MDX Result Set based on information that is not in their cubes. It may be the case that this information may not make sense to be in the cube. Other times this can be useful when there is a large set of values you want to restrict. As mentioned before, this is not a standard MDX function, it was created by InterSystems to handle cases were queries were not performing well or cases that were not easily solved by existing functions.

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BridgeWorks is pleased to announce a VDM, v9.1.0.1. This release includes the following updates:

Updates

  • Historical Linking is now based off connection profile name
  • Saved Formatting is now based off connection profile name
  • Tables and Fields column headers no longer hide based on connection type

Bug Fixes

Open Exchange app
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Hello InterSystems Community,

We're excited to announce that we've completed our first Open Exchange submission for InterSystems platforms.

BridgeWorks VDM is an ad hoc reporting and graphical SQL query builder application that was designed for any user who needs access to their SQL projections in InterSystems Caché, InterSystems IRIS, InterSystems IRIS for Health databases as well as access to InterSystems DeepSee and InterSystems IRIS BI Cubes with minimal SQL scripting experience.

VDM features:

Open Exchange app
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I want to have a generic PercentOfAll measure that can be used for any dimension of the cube. This PercentOfAll should act like Count, but instead of showing the number of rows in a cell, it will show the percentage (100*number of rows for that member/all rows) .It should not matter what dimension is being viewed. Ex

There are a total of 100 rows in the source 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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Hi, Community!

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

​

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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Hi!

Sometimes I need to filter the widget on a dashboard from a different cube. And I face the following problem:

Widget A refers to a query from Cube A and I want to filter Widget B from Widget B.

Widget's B pivot refers to Cube B, and which has different dimensions for the same data.

E.g. cube A has the dimension Author and the Cube B has the dimension Member for the same data. So there is no way to filter such a widget B from the widget A.

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Question
· Mar 29, 2017
Dollar Ranges

How to setup dollar ranges to get the number of patient accounts. So, I want to capture the number of patient accounts based on the original balance of:
0 to 499
500 to 999
1000 to 2499
5000 to 9999
10000 to 24999
25000 to 49999
50000 to 74000
75000 to 99999

=100000

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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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