Paradime Help Docs
Get Started
  • 🚀Introduction
  • 📃Guides
    • Paradime 101
      • Getting Started with your Paradime Workspace
        • Creating a Workspace
        • Setting Up Data Warehouse Connections
        • Managing workspace configurations
        • Managing Users in the Workspace
      • Getting Started with the Paradime IDE
        • Setting Up a dbt™ Project
        • Creating a dbt™ Model
        • Data Exploration in the Code IDE
        • DinoAI: Accelerating Your Analytics Engineering Workflow
          • DinoAI Agent
            • Creating dbt Sources from Data Warehouse
            • Generating Base Models
            • Building Intermediate/Marts Models
            • Documentation Generation
            • Data Pipeline Configuration
            • Using .dinorules to Tailor Your AI Experience
          • Accelerating GitOps
          • Accelerating Data Governance
          • Accelerating dbt™ Development
        • Utilizing Advanced Developer Features
          • Visualize Data Lineage
          • Auto-generated Data Documentation
          • Enforce SQL and YAML Best Practices
          • Working with CSV Files
      • Managing dbt™ Schedules with Bolt
        • Creating Bolt Schedules
        • Understanding schedule types and triggers
        • Viewing Run History and Analytics
        • Setting Up Notifications
        • Debugging Failed Runs
    • Migrating from dbt™ cloud to Paradime
  • 🔍Concepts
    • Working with Git
      • Git Lite
      • Git Advanced
      • Read Only Branches
      • Delete Branches
      • Merge Conflicts
      • Configuring Signed Commits on Paradime with SSH Keys
      • GitHub Branch Protection Guide: Preventing Direct Commits to Main
    • dbt™ fundamentals
      • Getting started with dbt™
        • Introduction
        • Project Strucuture
        • Working with Sources
        • Testing Data Quality
        • Models and Transformations
      • Configuring your dbt™ Project
        • Setting up your dbt_project.yml
        • Defining Your Sources in sources.yml
        • Testing Source Freshness
        • Unit Testing
        • Working with Tags
        • Managing Seeds
        • Environment Management
        • Variables and Parameters
        • Macros
        • Custom Tests
        • Hooks & Operational Tasks
        • Packages
      • Model Materializations
        • Table Materialization
        • View​ Materialization
        • Incremental Materialization
          • Using Merge for Incremental Models
          • Using Delete+Insert for Incremental Models
          • Using Append for Incremental Models
          • Using Microbatch for Incremental Models
        • Ephemeral Materialization
        • Snapshots
      • Running dbt™
        • Mastering the dbt™ CLI
          • Commands
          • Methods
          • Selector Methods
          • Graph Operators
    • Paradime fundamentals
      • Global Search
        • Paradime Apps Navigation
        • Invite users to your workspace
        • Search and preview Bolt schedules status
      • Using --defer in Paradime
      • Workspaces and data mesh
    • Data Warehouse essentials
      • BigQuery Multi-Project Service Account
  • 📖Documentation
    • DinoAI
      • Agent Mode
        • Use Cases
          • Creating Sources from your Warehouse
          • Generating dbt™ models
          • Fixing Errors with Jira
          • Researching with Perplexity
          • Providing Additional Context Using PDFs
      • Context
        • File Context
        • Directory Context
      • Tools and Features
        • Warehouse Tool
        • File System Tool
        • PDF Tool
        • Jira Tool
        • Perplexity Tool
        • Terminal Tool
        • Coming Soon Tools...
      • .dinorules
      • .dinoprompts
      • Ask Mode
      • Version Control
      • Production Pipelines
      • Data Documentation
    • Code IDE
      • User interface
        • Autocompletion
        • Context Menu
        • Flexible layout
        • "Peek" and "Go To" Definition
        • IDE preferences
        • Shortcuts
      • Left Panel
        • DinoAI Coplot
        • Search, Find, and Replace
        • Git Lite
        • Bookmarks
      • Command Panel
        • Data Explorer
        • Lineage
        • Catalog
        • Lint
      • Terminal
        • Running dbt™
        • Paradime CLI
      • Additional Features
        • Scratchpad
    • Bolt
      • Creating Schedules
        • 1. Schedule Settings
        • 2. Command Settings
          • dbt™ Commands
          • Python Scripts
          • Elementary Commands
          • Lightdash Commands
          • Tableau Workbook Refresh
          • Power BI Dataset Refresh
          • Paradime Bolt Schedule Toggle Commands
          • Monte Carlo Commands
        • 3. Trigger Types
        • 4. Notification Settings
        • Templates
          • Run and Test all your dbt™ Models
          • Snapshot Source Data Freshness
          • Build and Test Models with New Source Data
          • Test Code Changes On Pull Requests
          • Re-executes the last dbt™ command from the point of failure
          • Deploy Code Changes On Merge
          • Create Jira Tickets
          • Trigger Census Syncs
          • Trigger Hex Projects
          • Create Linear Issues
          • Create New Relic Incidents
          • Create Azure DevOps Items
        • Schedules as Code
      • Managing Schedules
        • Schedule Configurations
        • Viewing Run Log History
        • Analyzing Individual Run Details
          • Configuring Source Freshness
      • Bolt API
      • Special Environment Variables
        • Audit environment variables
        • Runtime environment variables
      • Integrations
        • Reverse ETL
          • Hightouch
        • Orchestration
          • Airflow
          • Azure Data Factory (ADF)
      • CI/CD
        • Turbo CI
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
          • Paradime Turbo CI Schema Cleanup
        • Continuous Deployment with Bolt
          • GitHub Native Continuous Deployment
          • Using Azure Pipelines
          • Using BitBucket Pipelines
          • Using GitLab Pipelines
        • Column-Level Lineage Diff
          • dbt™ mesh
          • Looker
          • Tableau
          • Thoughtspot
    • Radar
      • Get Started
      • Cost Management
        • Snowflake Cost Optimization
        • Snowflake Cost Monitoring
        • BigQuery Cost Monitoring
      • dbt™ Monitoring
        • Schedules Dashboard
        • Models Dashboard
        • Sources Dashboard
        • Tests Dashboard
      • Team Efficiency Tracking
      • Real-time Alerting
      • Looker Monitoring
    • Data Catalog
      • Data Assets
        • Looker assets
        • Tableau assets
        • Power BI assets
        • Sigma assets
        • ThoughtSpot assets
        • Fivetran assets
        • dbt™️ assets
      • Lineage
        • Search and Discovery
        • Filters and Nodes interaction
        • Nodes navigation
        • Canvas interactions
        • Compare Lineage version
    • Integrations
      • Dashboards
        • Sigma
        • ThoughtSpot (Beta)
        • Lightdash
        • Tableau
        • Looker
        • Power BI
        • Streamlit
      • Code IDE
        • Cube CLI
        • dbt™️ generator
        • Prettier
        • Harlequin
        • SQLFluff
        • Rainbow CSV
        • Mermaid
          • Architecture Diagrams
          • Block Diagrams Documentation
          • Class Diagrams
          • Entity Relationship Diagrams
          • Gantt Diagrams
          • GitGraph Diagrams
          • Mindmaps
          • Pie Chart Diagrams
          • Quadrant Charts
          • Requirement Diagrams
          • Sankey Diagrams
          • Sequence Diagrams
          • State Diagrams
          • Timeline Diagrams
          • User Journey Diagrams
          • XY Chart
          • ZenUML
        • pre-commit
          • Paradime Setup and Configuration
          • dbt™️-checkpoint hooks
            • dbt™️ Model checks
            • dbt™️ Script checks
            • dbt™️ Source checks
            • dbt™️ Macro checks
            • dbt™️ Modifiers
            • dbt™️ commands
            • dbt™️ checks
          • SQLFluff hooks
          • Prettier hooks
      • Observability
        • Elementary Data
          • Anomaly Detection Tests
            • Anomaly tests parameters
            • Volume anomalies
            • Freshness anomalies
            • Event freshness anomalies
            • Dimension anomalies
            • All columns anomalies
            • Column anomalies
          • Schema Tests
            • Schema changes
            • Schema changes from baseline
          • Sending alerts
            • Slack alerts
            • Microsoft Teams alerts
            • Alerts Configuration and Customization
          • Generate observability report
          • CLI commands and usage
        • Monte Carlo
      • Storage
        • Amazon S3
        • Snowflake Storage
      • Reverse ETL
        • Hightouch
      • CI/CD
        • GitHub
        • Spectacles
      • Notifications
        • Microsoft Teams
        • Slack
      • ETL
        • Fivetran
    • Security
      • Single Sign On (SSO)
        • Okta SSO
        • Azure AD SSO
        • Google SAML SSO
        • Google Workspace SSO
        • JumpCloud SSO
      • Audit Logs
      • Security model
      • Privacy model
      • FAQs
      • Trust Center
      • Security
    • Settings
      • Workspaces
      • Git Repositories
        • Importing a repository
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
        • Update connected git repository
      • Connections
        • Code IDE environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Scheduler environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Manage connections
          • Set alternative default connection
          • Delete connections
        • Cost connection
          • BigQuery cost connection
          • Snowflake cost connection
        • Connection Security
          • AWS PrivateLink
            • Snowflake PrivateLink
            • Redshift PrivateLink
          • BigQuery OAuth
          • Snowflake OAuth
        • Optional connection attributes
      • Notifications
      • dbt™
        • Upgrade dbt Core™ version
      • Users
        • Invite users
        • Manage Users
        • Enable Auto-join
        • Users and licences
        • Default Roles and Permissions
        • Role-based access control
      • Environment Variables
        • Bolt Schedules Environment Variables
        • Code IDE Environment Variables
  • 💻Developers
    • GraphQL API
      • Authentication
      • Examples
        • Audit Logs API
        • Bolt API
        • User Management API
        • Workspace Management API
    • Python SDK
      • Getting Started
      • Modules
        • Audit Log
        • Bolt
        • Lineage Diff
        • Custom Integration
        • User Management
        • Workspace Management
    • Paradime CLI
      • Getting Started
      • Bolt CLI
    • Webhooks
      • Getting Started
      • Custom Webhook Guides
        • Create an Azure DevOps Work item when a Bolt run complete with errors
        • Create a Linear Issue when a Bolt run complete with errors
        • Create a Jira Issue when a Bolt run complete with errors
        • Trigger a Slack notification when a Bolt run is overrunning
    • Virtual Environments
      • Using Poetry
      • Troubleshooting
    • API Keys
    • IP Restrictions in Paradime
    • Company & Workspace token
  • 🙌Best Practices
    • Data Mesh Setup
      • Configure Project dependencies
      • Model access
      • Model groups
  • ‼️Troubleshooting
    • Errors
    • Error List
    • Restart Code IDE
  • 🔗Other Links
    • Terms of Service
    • Privacy Policy
    • Paradime Blog
Powered by GitBook
On this page
  • Pull Requests Section
  • Commits Section
  • How to Apply Filters

Was this helpful?

  1. Documentation
  2. Radar

Team Efficiency Tracking

PreviousTests DashboardNextReal-time Alerting

Last updated 7 months ago

Was this helpful?

The Work Dashboard provides valuable insights into team productivity and collaboration, empowering teams to analyze and improve their workflows effectively. By tracking pull request performance, commit patterns, and individual contributions, teams can enhance their development processes and overall productivity.

Prerequisites

  • Completed setup in Radar's .

The Work dashboard is divided into two main sections:

  1. Pull Requests: Analyzes pull request metrics and trends. [link]

  2. Commits: Provides insights into commit patterns and file contributions. [link]


Pull Requests Section

The Pull Requests section offers a comprehensive view of your team's pull request activity and efficiency:

1. Pull Request Volume and Size

Value: Understand the overall workload and complexity of your team's pull requests.

How to use:

  • Monitor the total number of merged pull requests to gauge overall productivity.

  • Analyze the trend in pull request size over time to identify potential complexity issues or improvements in code organization.


2. Pull Request Efficiency

Value: Assess the speed and efficiency of your team's pull request process.

How to use:

  • Track the average cycle time to identify bottlenecks in the review process.

  • Monitor the number of file changes per pull request to balance between meaningful updates and manageable reviews.

  • Look for correlations between PR size, file changes, and cycle time to optimize your development process.


3. Code Change Impact

Value: Visualize the net impact of code changes in production.

How to use:

  • Assess the overall trend of code additions vs. deletions.

  • Identify weeks with significant code churn and correlate with major feature releases or refactoring efforts.


Commits Section

The Commits section provides insights into the nature and distribution of code contributions:

1. Commit Type Analysis

Value: Understand the balance between feature development and bug fixing efforts.

How to use:

  • Monitor the ratio of feature commits to bug fix commits to assess development focus.

  • Use this information to adjust resource allocation between new feature development and maintenance work.


2. Commit Trends

Value: Visualize commit patterns over time to identify productivity trends.

How to use:

  • Analyze weekly commit patterns to understand your team's development rhythm.

  • Identify any seasonal trends or impacts from project phases on commit frequency.


3. File Contribution Analysis

Value: Identify the most frequently updated files and potential areas of technical debt.

How to use:

  • Focus code review efforts on frequently changed files.

  • Identify files with high bug fix contributions as candidates for refactoring or increased testing.

  • Use this information to guide documentation efforts and knowledge sharing within the team.


How to Apply Filters

  1. Locate the "Select date range" dropdown at the top of both Pull Requests and Commits sections.

  2. Choose your desired time frame for analysis.

  3. The dashboard will automatically update to reflect your selection, allowing for focused analysis over specific periods.

📖
Team Efficiency Tracking
Get Started guide