Data Ingestion with Lakeflow Connect

This course provides a comprehensive introduction to Lakeflow Connect, a scalable and simplified solution for ingesting data into Databricks from a wide range of sources. You’ll begin by exploring the different types of Lakeflow Connect connectors (Standard and Managed) and learn various data ingestion techniques, including batch, incremental batch, and streaming ingestion. You'll also review the key benefits of using Delta table and the Medallion architecture

Next, you’ll develop practical skills for ingesting data from cloud object storage using Lakeflow Connect Standard Connectors. This includes working with methods such as CREATE TABLE AS SELECT (CTAS), COPY INTO, and Auto Loader, with an emphasis on the benefits and considerations of each approach. You’ll also learn how to append metadata columns to your bronze-level tables during ingestion into the Databricks Data Intelligence Platform. The course then covers how to handle records that don’t match your table schema using the rescued data column, along with strategies for managing and analyzing this data. You’ll also explore techniques for ingesting and flattening semi-structured JSON data.

Following this, you’ll explore how to perform enterprise-grade data ingestion using Lakeflow Connect Managed Connectors to bring in data from databases and Software-as-a-Service (SaaS) applications. The course also introduces Partner Connect as an option for integrating partner tools into your ingestion workloads.

Finally, the course wraps up with alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with a strong foundation to support modern data engineering use cases.

Skill Level

Associate

Duration

Prerequisites

• Basic understanding of the Databricks Data Intelligence platform, including Databricks Workspaces, Apache Spark, Delta Lake, the Medallion Architecture and Unity Catalog.

• Experience working with various file formats (e.g., Parquet, CSV, JSON, TXT).

• Proficiency in SQL and Python.

• Familiarity with running code in Databricks notebooks.

Outline

Introduction to Data Engineering in Databricks

- Data Engineering in Databricks

- What is Lakeflow Connect?

- Delta Lake Review

- Exploring the Lab Environment

Cloud Storage Ingestion with LakeFlow Connect Standard Connectors

- Introduction to Data Ingestion from Cloud Storage

- Appending Metadata Columns on Ingest

- Working with the Rescued Data Column

- Ingesting Semi-Structured Data: JSON

Enterprise Data Ingestion with LakeFlow Connect Managed Connectors

- Ingesting Enterprise Data into Databricks Overview

- Enterprise Data Ingestion with Lakeflow Connect

Ingestion Alternatives

- Ingesting Data with Databricks Marketplace

- Ingesting into Existing Delta Tables

- Data Ingestion with MERGE INTO

Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Aug 04	09 AM - 01 PM (Asia/Singapore)	-	English	$750.00
Aug 04	09 AM - 01 PM (Europe/Paris)	-	English	$750.00
Aug 04	09 AM - 01 PM (America/Los_Angeles)	-	English	$750.00
Sep 01	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Sep 01	01 PM - 05 PM (Europe/Paris)	-	English	$750.00
Sep 01	09 AM - 01 PM (America/New_York)	-	English	$750.00
Oct 01	09 AM - 01 PM (Asia/Kolkata)	-	English	$750.00
Oct 01	09 AM - 01 PM (Europe/Paris)	-	English	$750.00
Oct 01	01 PM - 05 PM (America/New_York)	-	English	$750.00

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

Customer registration Partner registration

Private Class Request

If your company is interested in private training, please submit a request.

Request Private Training

See all our registration options

Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Aug 04	09 AM - 01 PM (Asia/Singapore)	-	English	$750.00
Aug 04	09 AM - 01 PM (Europe/Paris)	-	English	$750.00
Aug 04	09 AM - 01 PM (America/Los_Angeles)	-	English	$750.00
Sep 01	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Sep 01	01 PM - 05 PM (Europe/Paris)	-	English	$750.00
Sep 01	09 AM - 01 PM (America/New_York)	-	English	$750.00
Oct 01	09 AM - 01 PM (Asia/Kolkata)	-	English	$750.00
Oct 01	09 AM - 01 PM (Europe/Paris)	-	English	$750.00
Oct 01	01 PM - 05 PM (America/New_York)	-	English	$750.00

Registration options

Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

Purchase now

Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Architecting Data Warehouses for Large-Scale Deployments

This course covers performance optimization, cost control, and security for large-scale data warehousing deployments.This course is designed for Data Warehousing practitioners responsible for managing Databricks environments serving hundreds or thousands of users across multiple business units. You will gain the skills necessary to efficiently scale data warehousing operations while maintaining high performance, cost-effectiveness, and compliance with security standards.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

Building ETL Pipelines with SQL

This course teaches how to build production-ready ETL pipelines using pure SQL on the Databricks Data Intelligence Platform. Students learn Streaming Tables with Auto Loader for incremental ingestion, Materialized Views with incremental refresh for Silver-to-Gold transformations, AUTO CDC (FLOW AUTO CDC) for declarative SCD Type 1 and Type 2 dimension management, and Lakeflow Jobs with SQL File tasks for production orchestration. The course follows a realistic retail dataset through the medallion architecture (Bronze → Silver → Gold).

Generative AI Engineer

Generative AI Application Deployment and Monitoring

Ready to learn how to deploy, operationalize, and monitor generative AI applications? This content will help you gain skills in the deployment of generative AI applications using tools like Model Serving. We’ll also cover how to operationalize generative AI applications following best practices and recommended architectures. Finally, we’ll discuss the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.

Languages Available: English | 日本語 | Português BR | 한국어