Connect FiveTran to CluedIn

Connecting Fivetran to CluedIn: A Complete Guide

This guide explains how to integrate Fivetran with CluedIn so that the data pipelines and transformations managed in Fivetran flow directly into CluedIn’s data quality and master data management (MDM) framework.

Why Connect Fivetran to CluedIn?

  • Seamless Ingestion: Automatically land data from SaaS, databases, and applications into CluedIn via your warehouse.
  • Data Quality Monitoring: Allow CluedIn to validate and score the data streamed by Fivetran.
  • Master Data Governance: Feed harmonized data into CluedIn golden records for entity resolution and survivorship rules.
  • Operational Efficiency: Use CluedIn’s alerts (Slack/Teams/Email) to monitor Fivetran pipelines and resulting data quality.

Integration Architecture

  • Fivetran extracts and loads data into a supported warehouse.
  • CluedIn connects to the same warehouse (via JDBC/ODBC) or consumes Fivetran outputs.
  • CluedIn applies enrichment, data quality rules, and master data processing.

Prerequisites

  • Fivetran: Active account with connectors configured to land data in your warehouse.
  • CluedIn: Access to ingestion pipelines and entity mappings.
  • Warehouse: Supported target (Snowflake, BigQuery, Redshift, Azure Synapse, SQL Server, etc.).
  • Credentials: Database/service accounts with read access for CluedIn.

Step 1 — Set Up Fivetran Connector

  1. Log in to Fivetran dashboard.
  2. Choose a source connector (e.g., Salesforce, HubSpot, MySQL).
  3. Configure destination schema (e.g., fivetran_salesforce, fivetran_hubspot).
  4. Verify sync is active and data is landing in the warehouse.

Step 2 — Prepare Data for CluedIn

  • Align schema names and tables with business domains (e.g., customer_raw, product_raw).
  • Optionally use Fivetran Transformations (dbt integrated) to clean data before CluedIn ingestion.
  • Ensure consistent primary keys (id, email, sku) for CluedIn entity resolution.

Step 3 — Connect CluedIn to the Warehouse

  1. In CluedIn, go to Data Sources → Add Connector.
  2. Select your warehouse type (Snowflake, BigQuery, SQL Server, etc.).
  3. Enter JDBC/ODBC connection details:
    • Host, Port, Database
    • User & Password / Key
    • Schema (e.g., fivetran_salesforce)
  4. Test the connection and save.

Step 4 — Map Fivetran Tables to CluedIn Entities

  • Example mapping:
    • fivetran_salesforce.accounts → Customer entity
    • fivetran_hubspot.contacts → Lead/Customer entity
    • fivetran_erp.products → Product entity
  • Define attributes (columns) and link them to CluedIn’s schema.
  • Enable deduplication and survivorship rules.

Step 5 — Automate Data Quality Monitoring

  1. Create CluedIn Data Quality rules:
    • Completeness (e.g., Customer Email required).
    • Validity (e.g., VAT number format).
    • Consistency (e.g., SKU in ERP matches SKU in CRM).
  2. Apply rules to ingested Fivetran tables.
  3. Enable alerts (Slack, Teams, Email) to monitor DQ scores in real time.

Step 6 — Enable Master Data Workflows

  • As Fivetran loads new/updated data, CluedIn:
    • Merges records into golden entities.
    • Resolves duplicates across systems.
    • Applies survivorship rules (e.g., “email from CRM overrides ERP”).
  • Configure downstream syncs to push golden records back to target systems if needed.

Step 7 — Automate via Scheduling

  • Fivetran handles incremental syncs automatically.
  • CluedIn ingestion jobs can be scheduled to run after each Fivetran sync.
  • Optionally integrate via webhook/trigger: when Fivetran finishes sync, it triggers CluedIn ingestion.

Best Practices

  • Schema Naming: Keep Fivetran schemas clear (fivetran_<source>).
  • Entity Alignment: Decide early how sources map to CluedIn entities (Customer, Product, Supplier).
  • Transform Before or After?
    • Use dbt/Fivetran transformations for light cleaning.
    • Use CluedIn for entity resolution, survivorship, and golden records.
  • Monitoring: Configure Slack alerts for pipeline failures in Fivetran and DQ failures in CluedIn.
  • Security: Use vaults/secret stores for credentials, never hardcode them.

Troubleshooting

  • No data in CluedIn: Check schema permissions and ensure warehouse sync is complete.
  • Duplicate records: Verify unique keys are consistent across Fivetran sources.
  • DQ rules failing unexpectedly: Inspect dbt/Fivetran transformations vs. CluedIn expectations.
  • Slow ingestion: Partition large tables or enable incremental loading.

Summary

By connecting Fivetran to CluedIn, you can:

  • Ingest data from hundreds of SaaS apps and databases.
  • Monitor and improve data quality across sources.
  • Build and maintain golden records through entity resolution and MDM.
  • Keep teams informed with real-time alerts when data quality or pipeline issues arise.

This integration turns your Fivetran pipelines into a governed, quality-assured data supply chain managed inside CluedIn.