Conduit Docs
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    • Conduit vs Google Looker Studio
  • Use Cases
    • Use Case: AI-powered Text Extraction
    • Use Case: Track Ad Campaign Performance with Conduit
    • Use Case: Enhancing Project Management with Copilot
    • Use Case: Using Conduit for Financial Analysis
    • Use Case: Use ChatGPT with your data
    • Use Case: Build financial models from raw transactional data and generate P&L statements.
    • Use Case: Marketing data analytics
    • Use Case: Using data science frameworks using your data in spreadsheets Low-Code
    • Use Case: Custom Dimensions for Ad Operations
    • Use Case: Custom dimensions for E-Commerce
    • Use Case: Extract invoices from PDF
    • Use Case: Export data from SaaS applications to your spreadsheet
    • Use Case: Online store and a physical retail locations consolidated
    • Use Case: Pull data from Advertisement platforms to a spreadsheet
    • Use Case: Consolidation of data received as separate files, for example, separate Excel reports
    • Use Case: Names, IDs, SKUs normalization
    • Use Case: Integrating Conduit with a custom CRM using SSO/OAuth2
    • Use Case: Chat Bot for Your Data
    • Use Case: Display Net sales On a Dashboard by Subtracting Ad spend from Total Sales
    • Use Case: Conduit for Healthcare Applications
  • Security & Data Privacy
    • Data Retention Policy
    • How Conduit Complies with GDPR?
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  • Spreadsheets
    • Writing data to spreadsheets: Overwrite and Update
    • Using Formulas in Spreadsheets
    • The Time Range in formulas
    • The table in the spreadsheet does not start from the first line
  • Conduit for Digital Agencies
    • How to Use White Label
    • What is a Workspace and a Sub-account
    • Use Case: Creating a Dashboard for Two Clients
    • Users in Your Team vs. Sub-Accounts in Workspaces
    • Deleting a Workspace
    • How to Log Into a Workspace
    • How to Buy Additional Workspaces
    • Schedulers in Workspaces
  • Troubleshooting
    • Error codes and how to troubleshoot data-related issues
    • Google Drive Refusing To Connect
    • Why Are my Shopify stats different?
    • Facebook Integration: How to Fix the GraphMethodException Error
  • Copilot
    • Copilot Roles: Data Analyst vs AI Generalist
    • Conduit Copilot vs. ChatGPT – What's The Difference?
    • How to Tune the Copilot
    • Data Sources for Copilot
  • For Developers
    • IP Addresses of Conduit Servers
    • Create an AI Сopilot for your app
    • Manage your AI Copilot users
    • Upload CSV files to Conduit via API (Guide)
  • Integrations
    • Instagram Integration
    • Dashboard Widgets Based On a SQL Connection
    • GA4 Integration Notes
    • Salesloft Integration
    • Self-service and Manual integrations
    • Installing Google Sheets Add-On
    • Slack Integration
    • YouTube Integration
    • HubSpot Integration
    • Conduit integration for Bigcommerce
    • Xero Integration
    • Recharge integration
    • Wrike Integration
    • Zoho Integration
    • Monday.com Integration
    • ActiveCampaign Integration
    • ClickUp Integration
    • FreshSales Integration
    • Google Ads Quality Score
    • Facebook Ads Reach
    • Shopify Net Sales and Returns
    • Gorgias tickets with Spam/Deleted/Auto-Close statuses
    • Looker Studio Connector
  • Workflows
    • Workflows – Adding New Columns
    • Workflows – using the Join by Key block
    • Workflows – using the Union block
    • Workflows – using the Transpose block
    • Workflows – creating a weekly Ad Spend report
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  1. Workflows

Workflows – using the Join by Key block

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Last updated 11 months ago

The “Join by Key” block serves as the bridge between two datasets. Conduit processes each row in the primary dataset, seeking matches in the secondary dataset based on a specified key. Rows from the secondary dataset that don't find a match in the primary dataset are excluded from the final output.

This feature could be useful, when you trying to merge related data from different sources, such as Ad networks

Here's a practical example:

  1. Start a Workflow by pulling data from Facebook Ads and Google Analytics accounts

  2. Add the Join by Key block into your Workflow.

  3. Set up the block by choosing the primary and secondary datasets. In our case, let's enrich our advertising data with insights from the analytics system.

  4. Select "Demo Facebook" as the Primary dataset.

  5. Choose "Demo Google Analytics" as the Secondary dataset.

Now, configure the key matching process. In our example, we aim to find values from Demo Google Analytics and incorporate them into rows of the primary dataset where Date and Ad Campaign values align.

Applying pro-data distribution for metrics

The Join by Key block in Conduit comes with an additional configuration - the "Apply pro-rata distribution for metrics" setting. This feature addresses scenarios where one row from a dataset corresponds to multiple rows in another dataset, potentially leading to an increase in metric values due to duplicated rows.

Here is an example:

Facebook Data

Data
Campaign
Clicks

2024-01-01

Ads

11

2024-01-01

Ads

11

2024-01-02

Ads

15

Google Analytics

Date
Ad Campaign
Medium
Purchases

2024-01-01

Ads

m1

3

2024-01-01

Ads

m2

4

2024-01-02

Ads

m3

1

2024-01-02

Ads 2

m1

5

As a result of joining, we should receive a dataset with three rows

Date
Ad Campaign
Medium
Clicks
Purchases

2024-01-01

Ads

m1

6

3

2024-01-01

Ads

m2

5

4

2024-01-02

Ads

m3

15

1

As you can see, we encountered a duplication issue on January 1st, causing the total Clicks to increase from 26 to 37. By activating this setting, we would achieve a different outcome.

Date
Ad Campaign
Medium
Clicks
Purchases

2024-01-01

Ads

m1

6

3

2024-01-01

Ads

m2

5

4

2024-01-02

Ads

m3

15

1