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The Data Profiles List page allows you to manage all the data profiles you have created through the data entry process. Data profiles help standardize and organize metadata across your analytics and eCommerce projects, ensuring consistency, completeness, and better data discoverability. This page serves as a central hub for creating, editing, reviewing, and deleting data profiles.
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1. What Is a Data Profile?

A Data Profile is a structured metadata template that contains detailed information about a dataset or project. It typically includes:
  • Dataset title and description
  • Category or industry classification
  • Methodology or data source
  • Data collection period
  • Variables or metrics included
  • Geographic coverage
  • Data owner or organization details
Using data profiles ensures that every project contains standardized and complete information, which improves reporting accuracy and collaboration.

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2. Available Actions on the Data Profiles List Page

On this page, you can perform the following actions:

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2.1 Edit a Data Profile

You can update an existing data profile at any time. Editing allows you to:
  • Modify metadata fields
  • Update descriptions
  • Add missing information
  • Correct inaccuracies
  • Improve data documentation quality
If the data profile is linked to active projects, updates may affect how those projects are presented within the platform. Best Practice: Review your data profiles periodically to ensure all information remains accurate and up to date.

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2.2 Create a New Data Profile

You can create a new data profile directly from this page. This is useful when:
  • Preparing metadata before uploading a dataset
  • Standardizing information across multiple projects
  • Creating reusable templates for similar data categories
Once created, the data profile can be selected and applied during the data entry process for new projects. Creating profiles in advance saves time and ensures consistency across your analytics workflows.

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2.3 Remove a Data Profile

You can delete a data profile that is no longer needed. Important Considerations:
  • If the data profile is linked to active projects, you may need to unlink or reassign those projects before deletion.
  • Deleting a data profile may remove associated metadata from linked projects.
Before removing a profile, ensure it is no longer in use.

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3. Data Profile Overview Information

For each data profile listed, you can view key details, including:

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3.1 Linked Projects

See how many data projects are associated with a specific data profile. This helps you:
  • Understand profile usage
  • Identify widely used templates
  • Avoid deleting profiles that are actively linked

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3.2 Creation Date

Displays the date the data profile was created. This is useful for:
  • Tracking profile versions
  • Reviewing outdated templates
  • Managing lifecycle updates

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3.3 Completed Fields

You can view all completed fields within each data profile. This helps you:
  • Identify missing information
  • Ensure metadata completeness
  • Improve dataset transparency
  • Maintain high-quality documentation standards
A more complete data profile improves searchability, reporting accuracy, and trust among users and stakeholders.

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4. Why Data Profiles Matter

In a data analytics and eCommerce SaaS environment, well-structured data profiles:
  • Improve dataset organization
  • Enhance internal collaboration
  • Increase data transparency
  • Support compliance requirements
  • Improve reporting and insights generation
  • Help users understand the dataset before accessing it
They also make it easier to scale your operations when managing multiple projects across teams.

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5. Learn More

For a detailed guide on creating and structuring a data profile, refer to the (Data Profile guide)[/Survey-&-Data-Entry/Data-Profile-Guide] section. By properly managing your Data Profiles List, you ensure consistency, quality, and clarity across all your analytics and eCommerce data projects.