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Data Dictionary
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Configure dynamic operators more efficiently with the Data Dictionary panel. The panel provides convenient access to create, download, upload, and view data dictionary tables, making it easy to reference and utilize relevant data in the configuration. This streamlines the workflow and enhances productivity if you are working with dynamic operators.
Creating Your First Data Dictionary
This guide explains how to access and upload your first data dictionary.
Step 1: Select an Operator, then access the data dictionary panel located at the top right corner.
![image(32).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(32).png)
Note: To enlarge the view of the data dictionary select the “Open in new tab” option from the menu
![image(34).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(34).png)
Step 2: To create a Data dictionary choose the option to create a new data dictionary.
![image(36).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(36).png)
Step 3: Name the new data dictionary.
![image(37).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(37).png)
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.
![image(39).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(39).png)
Modify An Existing Data Dictionary or Creating A New Data Dictionary
This guide explains how to modify a data dictionary.
Step 1: Download the data dictionary to have a local copy.
![image(40).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(40).png)
Step 2: Modify the downloaded data dictionary.
Step 3: In the expanded Data Dictionary screen Select the Upload option.
![image(41).png](http://cdn.us.document360.io/c65001f1-30e3-4f1d-b335-57abf64ebd31/Images/Documentation/image(41).png)
Step 4: Choose the modified file and upload it.
![](http://usercontent.clueso.io/e8e80269-1826-48a3-9dcf-125e74db9b9d/8bc5091b-0539-45b5-a8db-11f62ba724a5/c1f0744f-cc2d-49ba-94ae-df00e8cdf687/images/731ff434-4cbd-45ba-b645-1822a81ced24.png)
Supported File Types
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
Looking for a sample data dictionary? You can download a sample CSV file by clicking on the provided link.