In this hands-on tutorial, you’ll learn how to seamlessly ingest Salesforce data into Databricks using Lakeflow Connect and implement real-world data engineering patterns for scalable analytics.
Watch on YouTube: https://youtu.be/NxuThfalRRE?si=k1JiJegmG853h33d
🔹 What you’ll learn in this video:
✅ How to connect Salesforce to Databricks
✅ Perform a Full Load (Initial historical data ingestion)
✅ Configure Incremental Load for continuous data sync
✅ Implement Slowly Changing Dimension (SCD) Type 1– overwrite old values with latest updates
✅ Implement Slowly Changing Dimension (SCD) Type 2 – preserve historical changes with versioning
📌 Use Cases Covered:
- Salesforce Opportunities data ingestion
- Customer/Account historical tracking
- Near real-time CRM analytics
- Data warehouse modernization with Databricks
🎯 Who is this for?
- Data Engineers / Architects
- Analytics Engineers
- Databricks Engineers
- Salesforce Admins/Developers
- Anyone preparing for Databricks or modern data platform roles
🛠 Tech Stack:
- Databricks Lakeflow Connect
- Salesforce
- Delta Lake
- Unity Catalog
🚀 Ingest Salesforce Data into Databricks using Lakeflow Connect | Full Load, Incremental Load, SCD Type 1 & Type 2 In this hands-on tutorial, you'll learn how to seamlessly **ingest Salesforce data into Databricks using Lakeflow Connect** and implement real-world data engineering patterns for ...
