Data Dictionaries

This guide explains how to access your data dictionaries

Accessing Data Dictionaries from Workspace Manager

Step 1: Start by selecting the Data Dictionaries chip in the Workspace Manager

Step 2: After clicking, a page displays all uploaded data dictionaries for the selected workspace. Hover over each data dictionary to view its name, last modified date, and the person who last modified it.

Accessing Data Dictionaries from Workspace Navigation

Step 1: Find the workspace navigation dropdown from any workspace artifact like Pipeline Builder or Runtime Fields. Use this feature to navigate between different artifacts within the workspaces, including Data Dictionaries.

Accessing Data Dictionaries from Pipeline Builder

Step 1: The process to access data dictionaries from an operator remains the same. Navigate to Pipeline Builder and select any Operator.

Step 2: Within the panel, access the data dictionary panel located at the top right corner.

This guide explains how upload your first data dictionary.

Creating from Workspace Manager

Step 1:  Start by selecting the Data Dictionaries chip in the Workspace Manager

Step 2: There are two ways to create a data dictionary. If no data dictionary exists, click the button “Create Data Dictionary” in the middle of the page to create your first data dictionary.

Otherwise, locate the navigation bar on the top right corner, and click on “Create New” to create your first data dictionary.

Step 3: Name the new data dictionary.

Step 4: Upload the file. If unsure about the type of file to upload, refer to the file-related information provided in the tooltips.

CSV Files for Tables: The first row represents the column name, and the second row indicates the type. The subsequent rows contain the table data.  

Supported Types: Types are case sensitive and have certain requirements for the data that are entered into their columns.

The following are the supported types and the requirements for each type:

• Text: Text types will accept any strings. If you want to represent a null enter '==NULL==' without the quotes. If you want a reserved character, i.e. comma, new line or ==NULL==, put either the character or entire string in double quotes '"test ,Text"'

• long: long types support integers.

• double: double types support floating point numbers. You can also represent not a number as 'NaN' as well as negative and positive infinity as 'inf' and '-inf'

• bool: bool types support true and false, case insensitive.

• LocalDate: LocalDate types are a date and are in the following format: '%Y-%m-%d'. EX: 2023-04-26

• Instant: Instant types are a moment in time and in the following format: '%Y-%m-%dT%H:%M:%S.%fZ', EX: 2023-04-26T13:33:30.000Z

Step 5: Once the data dictionary is ready, drag and drop it to upload. The uploaded file is now available as a data dictionary.

Creating from Pipeline Builder

This guide explains how view your data dictionaries.

Viewing from Workspace Manager

Step 1:  Start by selecting the Data Dictionaries chip in the Workspace Manager

Step 2: This action directs to the data dictionary list page displaying all data dictionaries.

Step 3: Click on a specific data dictionary to view its details.

Step 4: View the selected data dictionary data

Viewing from Pipeline Builder

Step 1: Navigate to the pipeline builder.

Step 2: Select any operator.

Step 3: Click on the data dictionary icon on the open panel

Step 4: Select the specific data dictionary to view.

Step 5: View the selected data dictionary data

This guide explains how to modify a data dictionary.

Modifying from Workspace Manager

Step 1: On the top navigation bar, select the Download option to have a local copy.

Step 2: Modify the downloaded data dictionary.

Step 3: On the top navigation bar, select the Upload option.

Step 4: Choose the modified file and upload it.

Modifying from Pipeline Builder

Step 1: Download the data dictionary to have a local copy.

Step 2: Modify the downloaded data dictionary.

Step 3: In the expanded Data Dictionary screen Select the Upload option.

Step 4: Choose the modified file and upload it.

This guide explains how to delete a data dictionary.

Deleting from List Page

Step 1: Select the data dictionary to delete from the list.

Step 2: Click on the Proceed option to confirm the deletion.

Deleting from View Page

Step 1: Navigate to the options in

Step 2: Click on delete to remove the data dictionary.

Step 3: Click on the Proceed option to confirm the deletion.

CSV Files for Tables: The first row represents the column name, and the second row indicates the type. The subsequent rows contain the table data.  

Supported Types: Types are case sensitive and have certain requirements for the data that are entered into their columns.

The following are the supported types and the requirements for each type:

• Text: Text types will accept any strings. If you want to represent a null enter '==NULL==' without the quotes. If you want a reserved character, i.e. comma, new line or ==NULL==, put either the character or entire string in double quotes '"test ,Text"'

• long: long types support integers.

• double: double types support floating point numbers. You can also represent not a number as 'NaN' as well as negative and positive infinity as 'inf' and '-inf'

• bool: bool types support true and false, case insensitive.

• LocalDate: LocalDate types are a date and are in the following format: '%Y-%m-%d'. EX: 2023-04-26

• Instant: Instant types are a moment in time and in the following format: '%Y-%m-%dT%H:%M:%S.%fZ', EX: 2023-04-26T13:33:30.000Z