Importing Data (Edit existing items & Add new items)
Learn more about the Import functionality to quickly update metadata across the platform.
1. Purpose
The Import feature allows users to bulk update existing metadata or add new glossary or policy items by uploading structured CSV files. This enables faster changes, improves data quality, and minimizes manual edits across Decube.
2. Accessing the Import Tab
To begin, navigate to the Import tab from the side navigation in Export/Import tab.
3. Selecting Operation
Each import operation begins by selecting:
Import Type: Choose between
Edit Existing Items
orAdd New Items
Operation Type: Depending on your selection, the following options are supported:
Import Type
Supported Operation Types
Edit Existing Items
Catalog (Dataset / Non-Dataset), Glossary, Policies
Add New Items
Glossary, Policies
Ensure that you select the specific object type and click on Upload CSV
button.


After clicking on Upload CSV
button, you will be brought to the next page to upload your CSV.
4. Uploading a CSV
You can either:
Drag and drop your file into the upload area, or
Click on
Upload file
to browse from your system.
Decube supports only .csv files. Ensure your file follows the required format outlined in the CSV template structure documentation:
For editing existing items, see CSV Template Structure for Editing Existing Items
For adding new items, see CSV Template Structure for Adding New Items

5. General Guidelines
Each file should only contain data related to a single logical group of operation. For example:
One Glossary import (including glossary, categories, terms)
One Catalog source (e.g., Redshift → schema, tables, columns)
One object type group (e.g., all Dashboards or all Charts)
The file must contain the identifier columns for the selected operation type. Rows with missing identifier columns will be rejected on validation.
6. Important Warnings (Summary)
These warnings will be displayed on the Uploading a CSV screen according to the selected operation type. For detailed field-level requirements and constraints, refer to the relevant CSV template structure documentation.
Catalog Objects (Dataset & Non-Dataset)
File size must be under 100 MB and not exceed 10,000 rows.
Only one Data Owner allowed per object.
Maximum 3 tags per object.
Description length should not exceed 8,000 characters.
Glossary Objects (Edit)
File size must be under 100 MB and not exceed 10,000 rows.
Renaming of glossary, category, or term names is not allowed. Do it via UI.
Descriptions are mandatory for all glossary-related objects.
Each glossary can have up to 3 Data Owners.
Description limit: 8,000 characters.
Policies (Edit)
File size must be under 100 MB and not exceed 10,000 rows.
Do not rename existing policies. Use the platform UI instead.
Policy Classification Name must:
Be mandatory
Be unique
Be 5 characters or fewer
Glossary Objects (Add New Items)
File size must be under 100 MB and not exceed 10,000 rows.
Glossary names must be unique.
Category names must be unique within a glossary.
Term names must be unique within a category or glossary.
Descriptions are mandatory.
Character limits:
Name: 100 characters
Description: 8,000 characters
Maximum of 3 Data Owners per glossary.
Policies (Add New Items)
File size must be under 100 MB and not exceed 10,000 rows.
Policy Name and Policy Classification Name are required and must be unique.
Classification Name: max 5 characters.
Once file is uploaded, next will be Smart Validation & Error Handling.
7. Smart Validation & Error Handling
Once uploaded, your CSV file undergoes validation for:
File format
Required headers & structure
Object-level constraints (e.g., tag limits, owner limits, character limits)
Data type and identifier validation
Common validation errors include:
Missing required fields
Unknown or duplicate attributes
Unsupported object type or row structure
8. Validation in Progress
Once you upload a file the system begins validating your input.
What you will see:
A loader with Message: “We’re validating your file…”
After validation finishes, there can be two scenarios:
Success: If the file passes all checks, you’ll be directed to the success confirmation screen.
Fail: If any rows or structure within the file fail validation, you will see the error screen.
9. Success
What’s included:
Success message: “Your file has been validated and is ready for import”
Summary box: shows the summary of changes that will be executed on the platform.
Name the CSV: you can name the csv as per your preference.
Checkbox: You must acknowledge a disclaimer confirming the changes are irreversible.
Import button: Once confirmed, you can proceed with importing the validated metadata.
Cancel Upload: If you do not agree with change summary and you want to make changes to the file, you can cancel upload.
Once import is successful, changes will be executed on the platform.

10. Fail
What’s included:
Error message: “There were issues with your file.”
Error summary box: will show all the errors encountered while validation. For example:
Number of rows that failed validation
Types of errors detected (e.g., missing identifiers, invalid attribute values)
Retry button: Allows you to re-upload a corrected file.
Retry returns the user to the import screen to re-upload a corrected CSV file based on the issues shown in the error summary.

After a CSV file is validated and the user confirms the import, the system processes the file in the background. Upon completion, users receive an email notification informing them whether the import succeeded or failed.
If your email shows an error:
Trigger Condition: Sent when the CSV passes validation, but the import process fails due to issues such as system-level errors, unexpected attribute values, or conflicts during metadata update.
You will need to download the error report from the History tab.
About the Import Error Report:
No changes will be executed on the platform in import fail.
The error report is the same CSV file the user uploaded, but it includes inline error messages for each failed row.
Example: If row 10 had an invalid attribute, that row will be marked with the corresponding error.
Users only need to fix the rows with errors—they do not need to recreate the entire file.
For detailed field requirements, examples, and best practices, always refer to the relevant CSV template structure documentation:
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