Export Schema
The Data Schema in Sequentum Cloud is a crucial component that defines the structure and format of your exported data. This configuration ensures that the exported data is well-organized, accurate, and ready for further analysis or processing. The Schema includes the name of the Export files, Column Names, Content Type, Allow Empty, Format Style, Format & Time Zone.
Key Components of the Data Schema
Table Name: The Table Name field identifies the main container command or a specific container sub-command from which data will be exported into a file. This structure simplifies data export management and tracking.
Two key scenarios are:
Agent-Level Export: The top-level "Agent" command encompasses all other commands. Data exports at this level will display "Agent" in the Table Name. As shown below,
Separate Export: You can assign specific sub-commands for independent export by enabling the Separate Export Table option.
This creates dedicated data files for the selected sub-commands, and the Table Name field will display the name of the corresponding sub-command as shown below:
By following these guidelines, Data exports are efficiently managed and Data integrity is maintained across all export operations.
Name: Specifies the name of each column or command within the table or file which will be exported. Clear and descriptive field names enhance data understanding and analysis.
Content Type: Sequentum Cloud supports the following Data Types for captured data:
Data Type | Description |
Text | All content will be captured as Text by default. Text content can be up to 4000 characters long. |
Long Text | Long Text content can be any length, but cannot always be used in comparisons, so you may not be able to include Long Text content in duplicate checks. |
File | |
Integer | A whole number. |
Big Integer | A 64-bit signed integer. |
Float | A floating-point number. |
Decimal | Represents a decimal floating-point number. A fixed precision and scale numeric value between -10 38 -1 and 10 38 -1. |
Date | Date value. |
Time | Time value. |
Date and Time | Date and/or time value. |
Boolean | A value that can be true or false. Boolean values are stored as 1 or 0 integer values. |
Correctly assigning data types ensures data integrity and compatibility with downstream processes.
Allow Empty: Specifies whether the captured column can be empty or not. Consider the impact of empty values on data analysis and processing. You can also set the percentage of blanks allowed in a particular column or field.
Always: This option permits empty or missing values in the captured content, providing maximum flexibility.
Never: This setting disallows any empty or missing values, ensuring that all fields must be completed before export.
Runtime Only: This option allows empty values during runtime, while enforcing restrictions at other times, striking a balance between flexibility and data integrity.
Percentage: This setting allows a specified percentage of empty values, enabling some degree of flexibility while maintaining overall data completeness.
Format Style: Specifies the data format style for captured content. The default value is set to ‘Blank’. Data captured can be formatted into the following styles:
Blank: Default style of data format.
Regular Expression: Specifies the style of the data format using Regular expressions.
Name | Content Type | Format Style | Format |
Url | Text(200) | Regular Expression | ^.{1,200}$ |
CategoryID | Text(100) | Regular Expression | ^[a-zA-Z0-9]$ |
Date: Specifies the style of data format for date
Number Range: Specifies the style of data format as a range number.
JSON: Specifies the style of data format for JSON.
Name | Content Type | Format Style | Format |
|---|---|---|---|
Product JSON | Text(2000) | JSON | {} |
Format: Formatting acts as a form of validation. It ensures both that the data collected is of the correct type and the desired format for export.
For example, you could specify DateTime to be formatted as yyyy-mm-dd.
Example | Format |
02/17/2009 | mm/dd/yyyy |
17/02/2009 | dd/mm/yyyy |
Feb 17, 2009 | MMM dd, yyyy |
17Feb2009 | ddMMMyyyy |
2009/2/17 | yyyy/m/dd |
The Sequentum Cloud supports the Standard date and time formatting strings for a detailed explanation or reference please refer to the link below.
https://learn.microsoft.com/en-us/dotnet/standard/base-types/standard-date-and-time-format-strings
For Custom date and time format strings please refer to the link below.
https://learn.microsoft.com/en-us/dotnet/standard/base-types/custom-date-and-time-format-strings
Time Zone: This setting allows you to specify how time zones are managed during data export. The options include:
Assume Local Time: This option assumes that the times are in the local time zone of the system.
Assume Universal Time: This setting treats all times as being in Universal Time (UTC), regardless of the local time.
Adjust to Universal Time: This option converts the local time to Universal Time (UTC), ensuring consistency in time representation across different regions.