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Projects

DeepDQ uses a project-based approach to organize your data quality work. Projects help you separate different data quality initiatives, environments, or organizational units, making it easy to manage resources and switch contexts within the platform.

What are Projects?​

Projects serve as organizational containers that allow you to:

  • Organize Work: Group related data quality initiatives by team, business unit, or data domain
  • Switch Contexts: Easily switch between different environments (development, staging, production)
  • Manage Resources: Keep sentinels, vaults, and configurations organized by project scope
  • Control Access: Manage who can view and modify different aspects of your data quality program
  • Track Progress: Monitor data quality improvements across different initiatives

Project Interface​

Projects List​

The main Projects page displays:

  • Project Names: List of all available projects (e.g., "dummy proj", "test project")
  • Search Functionality: Search bar to quickly find specific projects
  • Bulk Actions: Select multiple projects for batch operations
  • Add Project: Blue "Add Project" button to create new projects
  • Delete Selected: Red button to remove selected projects
  • Pagination: Navigate through multiple pages of projects

Project Navigation​

  • Top Navigation Dropdown: Select different projects from the dropdown in the top navigation
  • Context Switching: All platform views (Sentinels, Vaults, Alert Gateways, Catalog, Data Lineage, IAM etc.) update to show only the selected project's resources
  • Real-time Updates: The interface immediately reflects the selected project's data and configurations

Creating Projects​

Add New Project​

  1. Click the "Add Project" button from the Projects page
  2. Enter the required project information:
    • Project Name: Enter a descriptive name for your project
    • Validation: The system will validate that the project name meets requirements
  3. Click "Create Project" to add the new project
  4. The new project will appear in your projects list and be available in the navigation dropdown

Project Naming​

  • Use descriptive names that clearly identify the project purpose
  • Consider including environment indicators (e.g., "Production-Sales-DQ", "Dev-Analytics")
  • Follow your organization's naming conventions for consistency

Managing Projects​

Editing Projects​

  1. Click on a project name from the Projects list to access the edit interface
  2. Modify the Project Name as needed
  3. Click "Save Changes" to update the project
  4. Use the "← Back" link to return to the projects list

Project Operations​

  • Search Projects: Use the search bar to quickly locate specific projects
  • Select Projects: Use checkboxes to select one or more projects for bulk operations
  • Delete Projects: Select projects and click "Delete Selected" to remove them
  • Clear Search: Use the "Clear" button to reset search filters

Switching Between Projects​

  1. Navigation Dropdown: Select a project from the dropdown in the top navigation bar
  2. Context Switch: The entire DeepDQ interface updates to show resources for the selected project
  3. Persistent Selection: Your project selection remains active across browser sessions
  4. Isolated Views: Each project maintains its own separate set of:
    • Sentinels and monitoring rules
    • Vaults and database connections
    • Alert gateways and notification settings
    • Catalog and data lineage information

Project Organization​

Project Structure​

Each project acts as an isolated workspace containing:

  • Sentinels: Data quality monitoring rules specific to the project
  • Vaults: Database connections and configurations
  • Alert Gateways: Notification channels for project-specific alerts
  • Catalog: Data discovery and documentation within the project scope
  • Data Lineage: Lineage mappings and visualizations for project data

Use Cases​

Environment Separation​

  • Development Project: For testing and developing data quality rules
  • Staging Project: For pre-production validation and testing
  • Production Project: For live monitoring of production data systems

Organizational Units​

  • Sales Data Quality: Monitor CRM and sales database quality
  • Finance Analytics: Focus on financial data accuracy and compliance
  • Customer Data: Ensure customer information quality across systems

Initiative-Based Projects​

  • Data Migration: Monitor quality during major data migrations
  • Compliance Initiative: Track data quality for regulatory requirements
  • Analytics Modernization: Ensure quality during analytics platform updates

Best Practices​

Project Organization​

  • Clear Naming: Use descriptive names that indicate the project purpose and scope
  • Logical Grouping: Organize projects by business function, environment, or data domain
  • Consistent Structure: Maintain similar organizational patterns across related projects
  • Regular Cleanup: Periodically review and remove obsolete or completed projects

Project Management​

  • Active Projects: Keep the projects list focused on currently active initiatives
  • Documentation: Maintain clear documentation of each project's purpose and scope
  • Resource Planning: Consider the number of sentinels and vaults needed per project
  • Team Coordination: Ensure team members understand which project to use for different tasks

Workflow Integration​

  • Development Flow: Use separate projects for development, testing, and production
  • Data Governance: Align projects with your organization's data governance structure
  • Reporting: Organize projects to support your data quality reporting requirements
  • Collaboration: Structure projects to facilitate team collaboration and resource sharing