Lakeflow Connect enables you to easily and efficiently ingest data from enterprise applications like Salesforce, ServiceNow, Google Analytics, SharePoint, NetSuite, Dynamics 365 and more. In this session, we’ll dive deep on using connectors for the most popular SaaS applications, reviewing common use cases such as analyzing consumer behavior, predicting churn and centralizing HR analytics. You'll also hear from an early customer about how Lakeflow Connect helped unify their customer data to drive an improved automotive experience. We’ll wrap up with a Q&A so you have the opportunity to learn from our experts.

Unlock the power of your SAP data with SAP Business Data Cloud—a fully managed SaaS solution that unifies and governs all SAP data while seamlessly connecting it with third-party data. As part of SAP Business Data Cloud, SAP Databricks brings together trusted, semantically rich business data with industry-leading capabilities in AI, machine learning, and data engineering. Discover how to access curated SAP data products across critical business processes, enrich and harmonize your data without data copies using Delta Sharing, and leverage the results across your business data fabric. See it all in action with a demonstration.

Ingesting data from SaaS systems sounds straightforward—until you hit API limits, miss SLAs, or accidentally ingest PII. Sound familiar? In this talk, we’ll share how Databricks evolved from scrappy ingestion scripts to a unified, secure, and scalable ingestion platform. Along the way, we’ll highlight the hard lessons, the surprising pitfalls, and the tools that helped us level up. Whether you’re just starting to wrangle third-party data or looking to scale while handling governance and compliance, this session will help you think beyond pipelines and toward platform thinking.

Hundreds of customers are already ingesting data with Lakeflow Connect from SQL Server, Salesforce, ServiceNow, Google Analytics, SharePoint, PostgreSQL and more to unlock the full power of their data. Lakeflow Connect introduces built-in, no-code ingestion connectors from SaaS applications, databases and file sources to help unlock data intelligence. In this demo-packed session, you’ll learn how to ingest ready-to-use data for analytics and AI with a few clicks in the UI or a few lines of code. We’ll also demonstrate how Lakeflow Connect is fully integrated with the Databricks Data Intelligence Platform for built-in governance, observability, CI/CD, automated pipeline maintenance and more. Finally, we’ll explain how to use Lakeflow Connect in combination with downstream analytics and AI tools to tackle common business challenges and drive business impact.

In this course, you’ll learn how to have efficient data ingestion with Lakeflow Connect and manage that data. Topics include ingestion with built-in connectors for SaaS applications, databases and file sources, as well as ingestion from cloud object storage, and batch and streaming ingestion. We'll cover the new connector components, setting up the pipeline, validating the source and mapping to the destination for each type of connector. We'll also cover how to ingest data with Batch to Streaming ingestion into Delta tables, using the UI with Auto Loader, automating ETL with Lakeflow Declarative Pipelines or using the API.This will prepare you to deliver the high-quality, timely data required for AI-driven applications by enabling scalable, reliable, and real-time data ingestion pipelines. Whether you're supporting ML model training or powering real-time AI insights, these ingestion workflows form a critical foundation for successful AI implementation.Pre-requisites: Beginner familiarity with the Databricks Data Intelligence Platform (selecting clusters, navigating the Workspace, executing notebooks), cloud computing concepts (virtual machines, object storage, etc.), production experience working with data warehouses and data lakes, intermediate experience with basic SQL concepts (select, filter, groupby, join, etc), beginner programming experience with Python (syntax, conditions, loops, functions), beginner programming experience with the Spark DataFrame API (Configure DataFrameReader and DataFrameWriter to read and write data, Express query transformations using DataFrame methods and Column expressions, etc.Labs: NoCertification Path: Databricks Certified Data Engineer Associate