Accelerating Data Workflows with Databricks

Day 1: Foundations of Data Engineering with Modern Tools

Learning Objectives:

1. Understand the principles of data engineering and its critical role in data-driven organizations.
2. Gain familiarity with foundational tools and platforms for building efficient data pipelines.
3. Explore the importance of scalable data storage and the integration of diverse data sources.

Agenda:

• Welcome and Introduction: Overview of the course and key learning goals.
• Core Concepts of Data Engineering: Responsibilities, evolution of data systems, and industry trends.
• Data Storage Architectures: Comparison of data lakes and warehouses, and an introduction to Delta Lake.
• Setting Up Data Environments: Hands-on exploration of tools and cloud-based workflows.
• Batch Data Processing Workflows: Designing and building efficient batch pipelines.

Day 2: Advanced Pipeline Development and Optimization

Learning Objectives:

1. Implement robust and efficient pipelines for batch and real-time processing.
2. Learn optimization techniques for data ingestion and transformation.
3. Understand the role of orchestration tools in managing data flows.

Agenda:

• Data Transformation Fundamentals: Techniques for cleaning, enriching, and validating data.
• Real-Time Data Processing: Introduction to streaming concepts and hands-on pipeline creation.
• Pipeline Optimization: Strategies for performance tuning and resolving bottlenecks.
• Orchestrating Data Pipelines: Overview of scheduling and monitoring workflows with practical exercises.

Day 3: Integration, Security, and Scalability

Learning Objectives:

1. Integrate pipelines with analytics platforms and machine learning workflows.
2. Ensure data pipeline security and compliance with industry standards.
3. Scale solutions to handle large-scale, distributed data environments.

Agenda:

• Integration with Analytics and ML Workflows: Connecting data pipelines to analytics and ML models.
• Data Security and Compliance: Best practices for secure storage, data transmission, and meeting regulatory standards.
• Scaling Data Pipelines: Handling large-scale data workloads using distributed frameworks.
• Workshop Wrap-Up: Review of concepts, Q&A, and actionable next steps for participants.
• Closing Remarks: Summary of outcomes and future learning opportunities.

Instructor Kit

(PPTX/PDF of Slides + Optional Instructor Notes)
Comprehensive slide deck with detailed content covering all modules, plus optional instructor notes to enhance teaching effectiveness.

Student Kit / Handout

(with Free Branding)
Professionally designed handouts for students, including all essential course information and customizable branding options for your organization.

Course Agenda / Outline

Detailed day-by-day course agenda and outline, ensuring smooth course delivery and a structured learning experience for students.

Study Guide

A concise guide summarizing key concepts and topics covered in the course, perfect for post-course review and exam preparation.

FAQ

Answers to commonly asked questions about the course content, delivery, and labs to support instructors and students.

Briefing Doc

A high-level document summarizing the course objectives, target audience, and key learning outcomes, ideal for internal use and marketing.

Sales Enablement Kit for IT Training Sales Engineers

(Additional Fee)
Exclusive toolkit designed for IT training sales teams, including pitch decks, objection handling, and ROI documentation to support course sales.

Course AI GPT

(Course Assistant GPT so students can talk to the course materials!)
A cutting-edge AI-driven assistant that allows students to interact with course content, ask questions, and receive instant feedback.

Optional Podcast

(of the entire course or for each individual module)
Engaging audio content covering the entire course or individual modules, perfect for on-the-go learning or reinforcement.

Lab Guide

(Lab Environments are additional and can be found at CourseLabs.io)
Step-by-step lab guide to support hands-on learning, with lab environments available separately at CourseLabs.io.

Lab Files

(If you choose to host your own lab environment)
All necessary files and instructions for setting up and running labs in your own environment, offering flexibility in deployment.

Databricks - Latest stable version

Apache Spark - Latest stable version

MLflow - Latest stable version

Course Objectives

This course is designed to empower learners with the knowledge and hands-on experience needed to excel in modern data engineering using Databricks and Delta Lake. By the end of this course, participants will:

• Build and optimize scalable data pipelines with Delta Live Tables.
• Implement robust data governance strategies using Unity Catalog.
• Gain expertise in real-time data processing with Apache Spark and Delta Lake.
• Apply performance tuning techniques to maximize data pipeline efficiency.

Learning Objectives

Participants will learn to:

• Design and manage multi-hop medallion architectures.
• Automate workflows with data pipeline orchestration tools.
• Monitor and troubleshoot data pipelines effectively.
• Combine static and streaming datasets for real-time analytics.

Who This Course is For

This course is ideal for:

• Data Engineers and Developers looking to enhance their skills in Databricks.
• Technical teams tasked with managing data pipelines and optimizing analytics.
• Professionals in industries like retail, healthcare, and manufacturing who rely on data-driven decision-making.

Course Format

• 50% Lecture, 50% Hands-On Labs: Each topic combines in-depth theoretical discussions with practical, real-world exercises to ensure a comprehensive learning experience.

Customizable Course Options

We understand every organization has unique training needs. That’s why our courseware is fully customizable:

• Choose from a 5-day, 4-day, 3-day, 2-day, or even 1-day format to suit your team’s schedule.
• Priced competitively at $40 per student per day, ensuring maximum value.

Let this course transform your team’s data engineering capabilities and drive success in today’s data-driven world.