Delta Lake Masterclass: Databricks & Spark Mastery

Delta Lake Masterclass: Databricks & Spark Mastery | Udemy [Update 08/2025]
English | Size: 11.5 GB
Genre: eLearning

Master Delta Lake with Databricks & Spark: Real-time data pipelines, Unity Catalog, DLT & Interview Prep

What you’ll learn
Build and manage Delta Lake tables (managed vs external) with schema enforcement, schema evolution, and table constraints.
Understand the internal architecture of Delta Lake including transaction logs, deletion vectors, Z-ordering, partitioning, and caching.
Apply Delta Lake features such as Time Travel, Restore, Vacuum, Auto-compaction, Change Data Feed, and Delta Cloning.
Perform Insert, Update, Delete, and Merge (Upsert) operations using Delta Lake with audit logging and performance tuning.
Implement Slowly Changing Dimensions (SCD1 & SCD2) with and without Delta Lake in Spark for real-world data warehouse design.
Optimize performance by converting Parquet to Delta, reordering columns, and applying best practices for query performance.
Develop and manage real-time streaming pipelines using Delta Lake with continuous and one-time triggers.
Use Unity Catalog for secure governance, workspace migration, and managing external vs managed tables.
Design and orchestrate end-to-end ETL pipelines in Databricks using Delta Live Tables and Azure Data Factory (ADF).
Prepare for Azure Databricks and Delta Lake interviews with practical questions and real-world use cases.

Are you ready to master Delta Lake and take your Databricks & Spark skills to the next level?
This course is designed for data engineers, architects, and developers who want to build real-time, scalable, and production-ready data pipelines using the most in-demand tools in the industry.

Building on top of my first course, Databricks & Spark Masterclass: Real-Time Data Engineering (recommended for foundational learning), this Delta Lake Masterclass focuses exclusively on advanced Delta Lake concepts, performance optimization, governance, orchestration, and interview preparation.

What you’ll learn in this course:

Create and manage Delta Tables (managed vs external) with schema enforcement, schema evolution, and constraints.
Deep dive into Delta Lake architecture, internal working mechanisms, and storage layers.
Implement powerful Delta features like Time Travel, Change Data Feed, Cloning, Optimize, Auto-Compaction, Partitioning & Z-Ordering.
Perform SCD1 and SCD2 implementations with and without Delta Lake, using merge operations and audit logging.
Build real-time streaming pipelines in Databricks with Delta Lake streaming and AutoLoader.
Manage governance with Unity Catalog and design scalable pipelines with Delta Live Tables (DLT).
Orchestrate Databricks notebooks with Azure Data Factory (ADF) and optimize pipelines for performance.
Prepare for Databricks, Spark, PySpark, and Delta Lake interviews with dedicated sessions and coding practice.

Why Choose This Course

100% hands-on with real Databricks & Delta Lake projects
Covers latest features like Deletion Vectors, Column Encryption, AutoLoader, Unity Catalog, and DLT
Structured learning path: From core Delta features to advanced governance and orchestration
Includes interview-focused coding sessions for PySpark, SQL, and Delta Lake
Designed by a Data Engineering Architect with 20+ years of experience

By the End of This Course, You Will Be Able To

Build end-to-end real-time data engineering pipelines with Delta Lake
Optimize performance with advanced Delta features
Manage enterprise-grade governance with Unity Catalog
Confidently tackle data engineering interviews for Databricks & Spark roles

Enroll now and become a Delta Lake expert—mastering real-time data engineering with Databricks & Spark.

Who this course is for:

Data Engineers and Architects who want to master Delta Lake for building scalable data platforms.
Spark and PySpark developers looking to upgrade their skills with Databricks and Delta Lake.
SQL developers, ETL developers, and BI professionals who want to transition into modern data engineering.
Cloud data professionals working with Azure Databricks, Data Lake, and ADF who want hands-on, real-world projects.
Students, freshers, or professionals who have completed my “Databricks & Spark Masterclass: Real-Time Data Engineering” course and want to take the next step into advanced Delta Lake concepts.
Anyone preparing for Databricks, Spark, or Delta Lake interviews with practical, project-based learning.

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