Master the Lakehouse: Professional Databricks & Apache Spark Training Program
In today’s data-driven world, organizations are increasingly adopting Databricks and Apache Spark to build scalable, high-performance data platforms. As enterprises migrate toward Lakehouse architecture, the global demand for skilled professionals in Azure Databricks and AWS Databricks continues to skyrocket.
This Professional Databricks Training Program is a comprehensive, 25–40 hour 1-to-1 instructor-led course. Designed for real-world implementation, it focuses on industry best practices and hands-on labs that prepare you for elite data engineering roles.
🚀 Why Learn Databricks?
Databricks has become the backbone of modern data engineering and machine learning. By mastering the Databricks Lakehouse architecture, you gain expertise in:
Apache Spark: The gold standard for massive big data processing and distributed computing.
Delta Lake: Ensuring reliable data management with ACID transactions, time travel, and unified batch/streaming.
Databricks SQL: Powering high-performance analytics directly on the data lake.
Cloud Engineering: Hands-on experience with managed services in Azure and AWS environments.
👥 Who Should Enroll?
This program is tailored for professionals looking to modernize their technical stack, including:
Data Engineers and Big Data Developers looking to master PySpark.
Data Analysts transitioning into Engineering roles via Databricks SQL.
Cloud Engineers (Azure/AWS) and ETL professionals modernizing legacy pipelines.
Software Engineers entering the data domain.
Freshers aiming for high-growth data careers with a specialized skill set.
Corporate Teams seeking rapid enablement for enterprise migration projects.
📋 Course Specifications
Duration: 25–40 Hours of personalized, high-intensity learning.
Mode: 1-to-1 Instructor-Led Training (Live Sessions).
Platforms: Azure Databricks, AWS Databricks, and Databricks Community Edition.
Curriculum: 100% Hands-on labs with flexible scheduling to fit your professional life.
🛠 Comprehensive Course Curriculum & Lab Guide
Module 1: Architecture & Workspace Fundamentals
Core Content:
Evolution from Data Warehouse to Data Lake to Lakehouse.
Databricks Runtime, DBFS (Databricks File System), and Control Plane vs. Data Plane.
Managing Notebooks, Dashboards, and Libraries (PyPI/Maven).
Lab 1: Setting up a Databricks Workspace, creating a multi-node cluster, and mounting Azure Data Lake Storage (ADLS Gen2) or AWS S3.
Module 2: Apache Spark & PySpark Core
Core Content:
Spark Distributed Computing: Driver, Worker, and Executor roles.
Understanding Lazy Evaluation, Transformations (Narrow vs. Wide), and Actions.
Mastering the Spark DataFrame API for structured data processing.
Lab 2: Developing a PySpark application to perform complex filtering, grouping, and window functions on large datasets.
Module 3: Data Ingestion & ETL Pipelines
Core Content:
Reading/Writing data: Parquet, Avro, JSON, CSV, and JDBC.
Schema Inference vs. Schema Enforcement.
Handling corrupt records and data quality validation.
Lab 3: Building an automated ingestion pipeline that cleanses raw landing zone data and converts it into optimized Parquet format.
Module 4: Delta Lake Mastery
Core Content:
The Bronze-Silver-Gold (Medallion) architecture.
ACID Transactions on the Lake:
INSERT,UPDATE,DELETE, andMERGE.Time Travel (Version History) and Vacuuming.
Lab 4: Implementing a Delta Lake Medallion architecture with "Upsert" logic using the
MERGEcommand to handle Change Data Capture (CDC).
Module 5: Performance Tuning & Optimization
Core Content:
Shuffling, Partitioning vs. Bucketing.
Data Skipping, Z-Ordering, and File Compaction (
OPTIMIZE).Caching strategies and Broadcast Joins.
Lab 5: Profiling a slow Spark job using the Spark UI and applying Z-Ordering to reduce query execution time by 50%.
Module 6: Databricks SQL & Analytics
Core Content:
Building SQL Warehouses (Pro and Classic).
Creating Visualizations and AI-powered Dashboards.
Performance tuning with Query Profile.
Lab 6: Developing an executive dashboard using Databricks SQL that queries Silver and Gold Delta tables in real-time.
Module 7: Workflows & Production Orchestration
Core Content:
Databricks Workflows: Task orchestration and dependencies.
Job scheduling, multi-task jobs, and error notifications.
Parameter passing between notebook tasks.
Lab 7: Deploying a multi-step production workflow that triggers on file arrival and includes automated retries on failure.
Module 8: Security, Governance & Unity Catalog
Core Content:
Identity management: Users, Groups, and Service Principals.
Secret Scopes for managing API keys and passwords.
Introduction to Unity Catalog for centralized governance.
Lab 8: Configuring Secret Scopes and managing table-level permissions using SQL Grant statements.
🎯 Career Outcomes
Upon completion of this training, you will be equipped to:
Build scalable, production-grade data pipelines using Medallion architecture.
Implement Delta Lake for reliable, high-speed storage with ACID compliance.
Optimize Spark jobs for maximum performance and significant cloud cost-efficiency.
Architect modern Lakehouse solutions that unify BI and AI.
Ace technical interviews for Senior Data Engineer and Databricks Solutions Architect positions.
❓ Frequently Asked Questions
Is Databricks beginner-friendly? Yes. While SQL or Python knowledge is helpful, our structured 1-to-1 guidance starts from the basics and scales to advanced engineering.
Azure vs. AWS Databricks: Which should I choose? We cover both. The core Spark and Delta logic is identical; we teach you the specific cloud integrations for both ecosystems to make you cloud-agnostic.
Does this include a certification path? Yes, the course content is specifically aligned with the "Databricks Certified Data Engineer Associate" and "Professional" exam requirements.
✨ Start Your Journey with Eduarn.com
This professional training is delivered through Eduarn.com, a premier online learning platform for modern technologies.
Why Choose Eduarn?
Personalized Learning: 1-to-1 sessions tailored to your pace.
LMS Access: Lifetime access to our Learning Management System and recorded sessions.
Industry Aligned: Curriculum updated for the latest Spark 3.x and Delta 3.x releases.
👉 Visit eduarn.com to explore free courses, access our LMS, and enroll in professional training today.
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This Databricks training course is ideal for anyone looking to become a Data Engineer using Azure Databricks or AWS Databricks. The 1-to-1 format really helps in understanding Spark concepts deeply.
ReplyDeleteI like that this course includes Delta Lake, Databricks SQL, and real-world data pipeline labs. Very useful for Databricks interview preparation.
ReplyDeleteEduarn.com offering free LMS access and free courses makes it a great platform for learners and corporate teams.
ReplyDeleteVery good post and start learning today for data engineering..
ReplyDelete