Basics of using ARCHITECT: Efficient data management and analysis in the InterSystems IRIS Data Platform

In today's digital age, effective data management and accurate information analysis are becoming essential for successful enterprise operations. InterSystems IRIS Data Platform offers two critical tools designed to provide convenient data management: ARCHITECT and ANALYZER.

ARCHITECT: ARCHITECT is a powerful tool created for developing and managing applications on the InterSystems IRIS platform. A vital feature of ARCHITECT is the ability to produce and customize complex data models. It allows users to handle the data structure with flexibility to meet the specific requirements of their applications. ARCHITECT simplifies the development process by providing a user-friendly interface for dealing with business logic and application functionality, as well as adapting to changing business needs. A crucial part of working with ARCHITECT is creating and customizing complex data models, so let's take a look at step-by-step instructions on how to do it.

In order to start using the ARCHITECT functionality, you need to go to the corresponding control panel. To accomplish that, go to the IRIS management section and select the "Analytics" tab. Then, proceed to the "Architect" section.

When in the Architect menu, click the "New" tab at the top of the screen.

It will open the "CREATE A NEW DATA MODEL DEFINITION" menu.

• Definition Type: This field selects the type of data model definition. In the context of ARCHITECT, it can be "Cube" or "Subject Area"."Cube" is typically used to define multidimensional data, whereas "Subject Area" describes only a narrow portion of data.

If the "Cube" type is selected, you can fill in the following fields as shown below:

• Cube Name:

In this mandatory field, you should specify a unique name for the data cube you want to create. This name will be used to identify the data cube in the system.

• Display Name:

Here, you can appoint a name that will be displayed in the user interface for this data cube. This name can be more descriptive and precise than the cube name to give the user a better understanding.

• Cube Source:

This section specifies the data source for the cube. This part is not clear to me. Try the following: "The "Class Cube" is selected, and a "Source Class" is specified here, both of which must already exist in the system. This class provides the data to fill the cube.

• Class Name for the Cube:

In this compulsory field, you should mention the class name used to create the data cube. In addition to that name, you must include the package name to identify the class correctly.

• Class Description:

This field allows you to enter a description or context for the data cube class you are creating, making it easier to understand its purpose and content. This description can come in handy for organizing and structuring data in the system.

If the "Subject Area" type is selected, the next fields can be populated as follows:

• Subject Area Name:

In this obligatory field, you should state a unique name for the created subject area.This name will be utilized to identify this subject area in the system.

• Display Name:

Here, you can select a name to display in the user interface for this subject area. This name can be more descriptive and straightforward than the subject area name since we generally need it for user convenience.

• Base Cube:

This field is required to be completed since it specifies an existing cube that will be employed as the base cube for this subject area. The data from this cube will be available within this subject area.

• Filter:

It is an MDX expression that filters the given subject area. It allows you to restrict the available data for particular conditions or criteria.

• Class Name for the Subject Area:

This mandatory field specifies the class name used to create the subject area. In addition to this name, you must include the package name to identify the class in a proper manner.

• Class Description:

This field lets you enter a description or context for the subject area class being created, simplifying the understanding of its purpose and content. This description can be beneficial for arranging and structuring data in the system.

When you have selected Definition Type, go to the "Open" tab on the ARCHITECT main menu.

Depending on the Definition Type you have chosen, the cube may be available in two tabs in ARCHITECT:

If the "Cube" type was picked, the created cube will be available in the "Cubes" tab.

If the "Subject Area" type was selected, the created subject area will be available in the "Subject Areas" tab.

Once the cube is opened, the following fields will be displayed:

• Source Class: 

This field indicates the source class associated with the data used to assemble this cube. In our case, it will be "Community.Member".

• Model Elements: 

This section lists all the items associated with the desired cube. Elements might include Measures, Dimensions, Listings, Listing Fields, Calculated Members, Named Sets, Relationships, and Expressions.

• Add Element: 

This button authorizes you to add a new element to the designated cube for further analysis.

• Undo: 

This function is employed to undo the last action or change made as a part of editing this cube.

• Expand All: 

This feature expands all items in the list for easy viewing and access to details.

• Collapse All: 

This function collapses all items in the list for effortless navigation and content review.

• Reorder: 

This action entitles you to alter the order of elements in the cube for uncomplicated display and data analysis.

To add a new element to the cube, click "Add Element", and the following menu "ADD ELEMENT TO CUBE" will appear:

• Cube Name: 

It is the name of the cube to which you will add a new element.

• Enter New Element Name: 

It is the field where you should enter a new name for the data item you want to add.

• Select an element to add to this cube definition: 

In this area, you pick the type of element you want to add. Options may include "Measure", "Data Dimension", "Time Dimension", "Age Dimension", "iKnow Dimension", "Shared Dimension", "Hierarchy", "Level", "Property", "Listing", "ListingField", "Calculated Member", "Calculated Dimension", "Named Set", "Relationship" and "Expression".

• Data dimensions specify how to group data by values other than time:

In this part, I will explain how data dimensions help group data into specific values other than temporal ones.

After successfully adding the desired element to the cube, it is vital to perform the cube compilation and assembly process to update and optimize the data. Cube compilation ensures that all changes and new elements are integrated into the cube structure in a proper way, while assembly secures performance optimization and data updates.

It is crucial to remember that the build will not be available until the compilation is completed successfully. It guarantees that the build process is based on accurate and up-to-date data processed and prepared during compilation.

When the compilation and build are complete, it is vital to click the "Save" tab to ensure that any alterations done to the cube structure have been saved successfully. It will guarantee that the latest changes and updates made within the cube are now available for future use and analysis.

ARCHITECT is an integral part of the InterSystems IRIS platform, which provides extensive capabilities for developing and managing data models. It equips users with unique flexibility to create and modify complex data models, allowing them to customize the data structure to meet the requirements of a specific application. The compile-and-build system enables efficient data updating and optimization, securing high performance and accuracy across various business scenarios.

With ARCHITECT, users can modify cube elements, including measurements, relationships, expressions, and others, and perform further analyses based on the updated data. It makes it easy to adapt applications to changing business requirements and respond quickly to a company's growing needs.

The save functionality allows users to preserve all modifications and customizations, ensuring reliability and convenience when working with data. ARCHITECT is central to successful data management and provides a wide range of tools for producing and optimizing data structures to facilitate efficient data analysis and informed business decisions.