What you'll learn
Build and manage production-ready Delta Live Tables (DLT) and Lakeflow Declarative Pipelines from scratch
Ingest file-based live streaming data using Auto Loader
Handle schema inference and schema evolution in production environments
Merge multi-source data streams into unified tables using Append Flows architecture
Capture real-time source changes with Change Data Capture (CDC) and Auto CDC Flow
Implement enterprise SCD Type 1 and SCD Type 2 architectures on DLT
Set up automated data quality rules and isolate bad data using DLT Expectations
Build dynamic, parameter-driven pipelines that adapt at runtime
Optimize pipeline performance and manage workspace costs
Monitor pipeline health, lineage, and handle production errors
Requirements
A basic understanding of SQL or Python is enough for you to grasp data querying logic easily.
A general familiarity with foundational data engineering concepts, such as ETL, databases, and table structures, is required.
Prior familiarity with the Databricks interface is an advantage; however, it is not mandatory thanks to the orientation lessons included in the course.
A computer with an internet connection is all you need to follow the hands-on applications; no local software installation is required.
Description This course contains the use of artificial intelligence.
Welcome to "Databricks Data Engineering with DLT & Lakeflow Pipelines"course.
Master real-time data streaming, Change Data Capture (CDC), data quality governance, and enterprise data warehouse architectures using Delta Live Tables (DLT) and Lakeflow Declarative Pipelines. Secure, automate, and professionally manage your big data systems with Databricks-100% hands-on.
Master streaming architectures, data quality controls, and modern data engineering from absolute scratch using Databricks DLT and Lakeflow. Build production-ready big data pipelines with confidence.
The Real Challenge in Big Data
The biggest hurdle in big data engineering isn't learning theory-it'spractical execution. If building streaming pipelines, handling Change Data Capture (CDC), or implementing Slowly Changing Dimensions (SCD) feels overwhelming, you're not alone. What modern enterprises truly demand isn't just someone who can write static ETL scripts; they need engineers who can construct and manage production-grade, real-time data streams.
Start from Scratch, Graduate to Production Standards
With Databricks introducing Delta Live Tables (DLT) and Lakeflow, the era of managing pipelines with clunky, monolithic code is officially over. However, there is a massive gap between understanding DLT in theory and deploying error-free, automated pipelines in a live enterprise environment. Most online courses simply fall short of preparing you for real-world production scenarios.
That's where this course changes the game. Even if you've never touched Databricks or DLT before, you won't need to write complex infrastructure boilerplate. You'll learn how to build intelligent pipelines by simply declaring your data logic. Throughout this course, you'll gain true hands-on experience by building, testing, and deploying end-to-end pipelines from absolute scratch.
If you're ready to design self-healing, zero-touch data architectures that autonomously monitor data quality in real time, let's dive straight into the first lesson!
What You Will Learn in This Course
-Fundamentals & Setup from Scratch: Master the core architecture of Delta Live Tables, navigate the differences between legacy and modern UI formats in Databricks, and get comfortable with the DLT code editor. Build and deploy your very first pipeline right away.
-DLT Building Blocks: Deep dive into Streaming Tables, Materialized Views, and Live Tables. Understand their unique use cases and seamlessly integrate them into a cohesive pipeline architecture.
-Streaming Data Pipelines with Auto Loader: Harness Databricks' powerful Auto Loader to build file-based streaming pipelines from the ground up. Manage schema inference and schema evolution through real-world scenarios.
-Unified Streaming Tables via Append Flows: Consolidate data streams from multiple disparate sources into a unified streaming table, mastering Append Flow architectures and their critical role in production.
-Change Data Capture (CDC) & Auto CDC Flow: Capture real-time insert, update, and delete events from source systems, automatically reflecting them into target tables using DLT Auto CDC Flow on real-world datasets.
-SCD Type 1 & Type 2 Architectures: Construct Slowly Changing Dimensions (SCD Type 1 and Type 2)-the core of enterprise data warehousing-step-by-step on DLT. Master these high-frequency interview topics with field-ready confidence.
-Data Quality Governance with DLT Expectations: Guarantee data integrity by defining automated quality rules, tracking corrupted records, and controlling pipeline flows when quality violations occur.
-Dynamic & Parameterized DLT Pipelines: Move beyond static configurations. Learn to build flexible, environment-agnostic DLT pipelines that accept runtime parameters dynamically.
-Lakeflow Declarative Pipelines Updates: Stay ahead of the big data curve by mastering the latest architectural shifts and updates brought by Databricks Lakeflow.
What Makes This Course Unique? Why Learn with Us?
-We Build Intelligent Architectures from Scratch: Unlike typical courses that cover DLT in theory with a few basic tables, this course walks you through building complete, production-grade architectures. You'll enforce data quality via Expectations, automate CDC streams, implement SCD Type 1 & 2, and parameterize pipelines for dynamic execution.
-Cracking Senior Data Engineer Interview Topics: Technical interviews often probe deeply into Change Data Capture, Slowly Changing Dimensions, and streaming management. We skip the documentation recitation and tackle these advanced topics through hands-on production practices.
-No "Ideal Scenario" Traps: In the real world, data is rarely clean. This course sets itself apart by teaching you how to catch and handle dirty data using DLT Expectations, ensuring your pipelines remain resilient under real-world conditions.
-Production-Grade SCD Type 1 & Type 2 Implementation: While others brush past Slowly Changing Dimensions in slides, we build both SCD Type 1 and Type 2 patterns step-by-step using actual datasets, demonstrating the operational differences live.
-Focused on the Latest Lakeflow Ecosystem: No outdated DLT docs. We focus strictly on the modern Databricks Lakeflow Declarative Pipelines framework, highlighting UI transitions and recent platform updates so your knowledge stays fresh and relevant.
Course Structure & Curriculum Summary
This course is structured into five core functional modules designed to take you from foundational concepts to production-grade data pipeline architectures
1. Foundations & Environment Setup (Sections 1-2)
Master Delta Live Tables architecture, transition seamlessly between legacy and modern Databricks interfaces, and learn how to construct pipelines using core building blocks like Streaming Tables, Live Tables, and Materialized Views.
2. Ingestion & Multi-Source Streaming (Sections 3-4)
Build scalable, file-based streaming pipelines with Databricks Auto Loader. Manage dynamic schema inference and schema evolution, and merge disparate data streams into unified tables using DLT Append Flows.
3. Enterprise Data Warehousing: CDC & SCD Patterns (Sections 5-7)
Implement Change Data Capture (CDC) with Auto CDC Flow to process real-time updates and deletes. Design and deploy production-grade Slowly Changing Dimensions (SCD Type 1 and Type 2) from scratch to handle historical dimension tracking.
4. Data Governance & Operational Flexibility (Sections 8-9)
Ensure data integrity across your pipelines using DLT Expectations for automated quality enforcement and exception handling. Parameterize your DLT code to build flexible, environment-agnostic pipelines ready for production deployment.
5. Modern Ecosystem & Continuous Updates (Section 10)
Stay updated with the latest advancements in the Databricks Lakeflow Declarative Pipelines ecosystem, ensuring your engineering practices align with current industry standards.
Frequently Asked Questions
Can a complete beginner to Databricks or DLT take this course?
Absolutely! This course was specifically designed with beginners in mind. Don't let terms like "streaming" or "big data architectures" intimidate you. We break down every complex concept into easy-to-digest, step-by-step practical demonstrations. You'll start with the fundamentals of the DLT interface and progress to building advanced pipelines independently.
Do I need Python or SQL experience?
Either works! Delta Live Tables natively supports both SQL and Python APIs. Throughout the course, we showcase logic using both approaches depending on the business scenario. A basic understanding of data querying concepts is all you need to follow along.
Do I need a paid enterprise Databricks account or cloud budget?
Not at all. You can easily follow along with all core concepts and pipeline setups using the free Databricks Community Edition or standard free trial options without spending a dime.
How does DLT differ from traditional Apache Spark or AWS Glue pipelines?
Traditional setups require manual engineering effort for checkpointing, dependency tracking, infrastructure management, and error recovery. DLT and Lakeflow abstract away this operational burden-you simply define the transformation logic and quality constraints, while Databricks handles the rest. Learning DLT aligns you directly with where the industry is heading.
Do I need to install heavy software on my computer?
No local software installations are required! All development and pipeline execution take place entirely in the cloud via your web browser. All you need is a stable internet connection.
Where should I focus next after completing this course?
Once you've mastered streaming pipelines, CDC, SCD patterns, and data quality controls, your ideal next steps are exploring Unity Catalog governance integrations, advanced orchestration with Lakeflow Jobs, and Delta Lake performance optimization techniques.
Why Choose OAK Academy?
Driven by Educational Quality
Based in London,OAK Academy is a top-rated online education provider offering global courses across data engineering, software development, IT certifications, and technical fields. With over 5,000 hours of high-impact video content on Udemy, you will experience expert industry instruction from the very first minute.
Flawless Video & Audio Production
We produce all our courses to elite production standards so your learning experience remains engaging and uninterrupted. Enjoy crisp 4K visual clarity, crystal-clear audio narration, and structured explanations designed for maximum retention.
-Lifetime Uninterrupted Access: Learn at your own pace with lifetime access to all lectures and future course updates.
-Direct Q&A Instructor Support: Post questions directly in the Q&A section and receive fast, solution-focused support from our technical instruction team.
-Official Certificate of Completion: Showcase your verified certificate directly on your CV and LinkedIn profile.
Take your next big step toward mastering modern data engineering, real-time streaming, CDC, and data quality at enterprise standards.Enroll in the Databricks Delta Live Tables & Lakeflow Declarative Pipelines course today!
Who this course is for
Data Engineers who want to transition from traditional ETL processes to modern streaming and declarative architectures.
Senior Data Engineer Candidates looking to specialize in advanced DLT, CDC, and SCD topics that frequently appear in technical interviews.
Data Architects and Developers who will utilize the Databricks ecosystem and the latest Lakeflow infrastructure in large-scale data projects.
All Technology Professionals who want to build data pipelines autonomously by defining what they want, rather than writing extensive code.



https://rapidgator.net/file/f1691747c14871a073c891237185bc13/Databricks_Data_Engineering_with_DLT_&_Lakeflow_Pipelines.part1.rar.html
https://rapidgator.net/file/eabce9fea6acf871db9f212d40e57ce1/Databricks_Data_Engineering_with_DLT_&_Lakeflow_Pipelines.part2.rar.html
https://rapidgator.net/file/4721adf6d58c6df1aefdbf247728e848/Databricks_Data_Engineering_with_DLT_&_Lakeflow_Pipelines.part3.rar.html
https://rapidgator.net/file/4db5ac298561c858f4581ee19072c851/Databricks_Data_Engineering_with_DLT_&_Lakeflow_Pipelines.part4.rar.html