To address the implementation of a computed column in InterSystems IRIS similar to the PostgreSQL query you provided:

IRIS does not support GENERATED ALWAYS AS directly in SQL DDL commands for computed columns. The approach involves using COMPUTECODE. However, the error you encountered, suggests issues with syntax or implementation. A viable alternative might involve defining the logic in an appropriate trigger function or querying with derived columns directly [1][2].

For further assistance, you might consider asking for specific guidance on the Developer Community, especially if the proposed methods or adaptations still do not align with your requirements.

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To create a dashboard based on an SQL query in InterSystems Analytics, you can follow these general steps:

1. Create a Namespace if Needed:
   Set up a separate namespace where you can compile messages or report outputs. This includes configuring databases for globals and routines for the namespace [1].

2. Import and Prepare Code:
   Develop classes in Studio to fetch and calculate metrics, and compile them for use in your dashboard. Store the processed metrics in persistent classes that can later be used in an analytics cube [1].

3. Global and Package Mapping:
   Configure global and package mappings for the namespaces involved in your analytics. These settings allow data to be retrieved from specified sources when building the dashboard [1].

4. Build Analytics Cube:
   Use the Analytics Architect to create a cube based on the class that stores the metrics. Define dimensions, measures, and time roll-up elements as needed. Compile the cube and verify its structure [1].

5. Create Pivot Tables:
   Access the Analyzer to generate pivot tables based on the cube. Drag dimensions and measures onto rows and columns as appropriate. Save these tables after organizing the data display according to your requirement [1][2].

6. Design and Add Pivot Tables to Dashboard:

   • Open Analytics > User Portal and create a new dashboard.
   • Add widgets (e.g., tables) to the dashboard by selecting the pivot tables created earlier.
   • Arrange and resize widgets for better visibility and presentation [3][2].

7. Add Filters and Controls:
   Configure filter controls directly on widgets in the dashboard editor. Filters allow users to interact and narrow down the data (e.g., by ZIP code or other dimensions). Default values for these controls can also be added to streamline dashboard use [2].

8. Save and Test Dashboard:
   Store the dashboard configuration, test interactions, and verify the appearance and functionality. By default, analytics dashboards auto-save upon modification [2].

By completing the steps above, you can effectively transform your SQL query into an operational analytics dashboard, enabling efficient visualization and filtering for users. [1][3][2]

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No, a pre-existing <Signature> element is not required in the XML document before signing it using %XML.Security.Signature. The signing process builds and inserts the <Signature> element during the SignDocument() call, provided the signature object is properly initialized and associated with the document.

The error "Canonicalize error: Signature not found" occurs when the signature's structure does not match the expected format or is not correlated correctly with the document. The %XML.Security.Signature requires the setup of references and methods, and all associated objects must be correct and linked before executing the SignDocument() method.

To resolve the situation:
1. Ensure the SignedInfo section is properly configured using the required signature and digest methods.
2. Associate the Reference instance with the signature object using AddReference().
3. Confirm the document object is correctly serialized before calling the SignDocument() method. This ensures adequate linkage between the XML structure and the signature object [1][2].

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