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Data Lake Mastery: The Key to Big Data & Data Engineering

Name: Data Lake Mastery: The Key to Big Data & Data Engineering
Rating: 4.6 (630 reviews)

Data Lake Mastery using AWS: A Shortcut to Success in Big Data, Cloud Data Engineering and Data Architecture

Created byNikolai Schuler

Last updated 6/2026

English

What you'll learn

Master the complete implementation of full-scale Data Lake solutions in the cloud
Apply Data Lake concepts professionally in cloud data engineering
Create a multi-layered security strategy for Data Lake protection
Design & implement efficient data ingestion strategies in AWS
Master Data Lake Architecture for effective cloud implementations
Master Data Lake Governance & Security
Master Leadership & Strategy Essentials for Successful Data Lakes
Learn comprehensive access control strategies within Data Lakes
Understand and implement robust monitoring and security in Data Lakes
Enhance your career prospects with advanced Data Lake skills and knowledge

Course content

12 sections • 97 lectures • 10h 14m total length

Welcome!2:13
Meet the instructor as he shares his journey from business intelligence to data engineering and invites you to set a 20-day, 30-60 minute daily goal.
About This Course6:54
All slides & files0:47
What is a Data Lake?3:49
What is a Data Lake?
Benefits of a Data Lake5:52
Understanding Data Lakes: Benefits and Challenges
Key Terms & Concepts7:52
Designing a Data Lake: Architecture and Components
Data Lake vs. Data Warehouse vs. Lakehouse6:53
Compare data lake, data warehouse, and lakehouse, detailing raw vs structured data, governance, scalability, cost considerations, and use cases in analytics and machine learning.
Comparing Data Lakes, Warehouses, and Lakehouses
Understanding the different Tiers in AWS3:47
AWS Account Setup3:51
Set up an AWS account and explore free tier options, including always free, 12-month, and trial offers, and verify email to access the AWS Management Console.
Setting a budget7:07
Learn to monitor and control cloud spending by setting zero spend and monthly budgets, configuring alerts, and using billing and cost management to guard against unexpected costs.
Creating S3 buckets7:35
Initial Setup for Retail Insights Inc.'s Data Lake

Essential Elements of a Data Lake4:26
Design a scalable data lake architecture with storage, processing, governance, metadata management, and IAM-based access control and orchestration to enable secure data flow across diverse sources.
High Level Overview of Data Flow5:01
Trace the data flow in a data lake from ingestion to insights, highlighting schema on read, metadata governance, and consumption via BI tools.
Understanding Data Lake Architecture and Workflow
Different Zones in Data Lake9:38
Explore a practical, multi-layer data lake architecture with landing, raw, curated, and consumption zones, plus an optional exploration area, to enable governance, security, schema on read, and scalable analytics.
Designing Data Lake Zones
Tools for the different zones2:47
Data Formats used In a Data Lake5:59
Data Formats in Data Lakes

Data Ingestion Methods6:32
Basics of Batch Ingestion5:20
Understanding Batch Ingestion in Data Lakes
Data Catalog & Profiling5:13
Project Scenario1:35
Note: Cost of running Glue Jobs0:37
Hands-on: Data Catalog & Crawlers10:31
Set up an S3 source and raw zone, then use a glue crawler to build the data catalog and auto-detect schemas for subsequent ingestion.
Batch Ingestion with AWS Glue9:36
Implementing Data Ingestion into the Raw Zone
Ingestion Patterns5:04
Event-Driven Ingestion10:16
Set up event-driven ingestion with AWS S3 and Lambda by triggering on new source-bucket files to move them into the target data lake, automating data ingestion.
Event-Driven Ingestion
Event-Driven Ingestion with AWS Lambda
Data Profiling3:03
In-Place Querying3:57
Athena In-Place Querying10:34
Data Cataloging with Crawlers and Querying in Athena
Understand Data Streaming6:55
Understand Data Streaming
AWS Kinesis Streaming11:32
Monitoring and Troubleshooting5:29
Monitor and troubleshoot data ingestion pipelines in a data lake by tracking kpis, configuring alerts, collecting logs, and using dashboards to ensure proactive reliability.
Hands-on: Monitoring & Troubleshooting9:34

Key Concepts for Data Storage Management2:35
Environment Overview3:10
Plan a multi-zone data lake with raw, transformed, curated, and exploratory zones, plus an optional landing zone. Separate production and development with AWS accounts and use buckets, folders, and metadata.
Partitioning3:48
Folder Structure4:47
Data Storage Management in Data Lakes
Automatic Partition Creation11:46
Manually Updating the Data Catalog4:23
Schema Changes8:45
Data Lifecycle Management5:53
Learn how data lifecycle management in data lakes balances cost and accessibility by moving data across S3 storage classes—from standard to glacier—while automating lifecycle rules for archiving and deletion.
Data Lifecycle Management
Hands-on: Storage Classes5:03
Hands-on: Lifecycle Rules4:39
Intelligent Tiering4:13
Intelligent-tiering automatically moves data between frequent, infrequent, and archive tiers based on access patterns. Configure lifecycle rules to optimize cost and control archive options.
Strategic Storage Optimization for Retail Insights Inc.'s Data Lake
Versioning in Data Lakes5:56
Hands-on: Versioning in S310:08
Replication6:36
Cross-Region Replication6:38
Create a versioned AWS source bucket and a destination bucket in another region, then configure a replication rule to enable cross-region replication.
Backups & Recovery5:37
Hands-on: Backup & Recover9:39
Hands-on: Backup Plan6:29

Understanding Data Processing in Data Lakes7:07
Understanding Data Processing in Data Lakes
Hadoop7:19
Explore how Hadoop provides distributed storage with the Hadoop distributed file system and MapReduce processing, delivering fault tolerance and scalability, contrasting with cloud data lake options like S3.
Spark5:57
Spark delivers fast in-memory processing, outpacing Hadoop MapReduce, with scalable clustering and RDDs; it supports Scala, Python, and Java for real-time streaming and machine learning.
Data Integration with AWS Glue7:44
Hands-on: Data Transformations12:50
Incremental Loads6:18
Incremental Loads
Processing a Stream17:49
Incremental Loading
Cost optimization in Data Lakes5:44
Optimize data lake costs and performance by using parquet or ORC formats, partitioning data, applying pushdown predicates, and automating incremental processing with data lifecycle management.

The Need for Monitoring in Data Lake4:11
The Need for Monitoring in Data Lake
Toolset for Monitoring4:44
Monitoring Using Metrics8:13
Setting up Dashboards6:01
Set up dashboards in CloudWatch to monitor query performance with line charts and data tables. Tune refresh intervals and metrics like total execution time; add alarms for Athena and Glue.
Setting up alarms9:19
Using Logs9:30
Monitoring AWS Glue Resource Utilization

Access Control in Data Lakes3:47
Principle of Least Privilege (PoLP)3:37
Role-Based Access Control (RBAC)5:52
Learn to implement role-based access control in AWS by mapping users to groups and policies, defining roles, and reviewing permissions for analysts and engineers.
Understanding Access Control
Implementation of RBAC6:56
Testing RBAC3:01
Test RBAC by logging in as a distinct IAM user in the AWS console, validating access to S3 buckets and Glue ETL jobs, and refining permissions with a custom policy.
Custom policies7:43
Implementing RBAC in Data Lake

Requirements

No previous experience is needed
If you wish to join the practical implementation, we'll set up an AWS account, utilizing mainly free tools, with overall costs expected to remain under $5

Description

Blueprint to Data Lake Mastery: Unleash the Power of Cloud Data Engineering

Are you ready to dive into the world of Data Lakes and transform your skills in Cloud Data Engineering?

This skill is a game-changer in data engineering and you're making a wise move by diving into it.

This is the only course you need to master architecting and implementing a full-blown state-of-the art data lake!

This comprehensive course offers you the ultimate journey from basic concepts to mastering sophisticated data lake architectures and strategies.

Why Choose This Course?

Complete Data Lake Guide: From setting up AWS accounts to mastering workflow orchestration, this course covers every angle of Data Lakes.
Step-by-Step Master: Whether you're starting from scratch or looking to deepen your expertise, this course offers a structured, step-by-step journey from beginner basics to advanced mastery in Data Lake engineering.
State-of-the-Art Expertise: Stay on the cutting edge of Data Lake technologies and best practices, with a focus on the most recent tools and methods.
Practical & Hands-On: Engage with real-life scenarios and hands-on AWS tasks to solidify your understanding.
Holistic Understanding: Beyond practical skills, gain a comprehensive understanding of all critical concepts, theories, and best practices in Data Lakes, ensuring you not only know the 'how' but also the 'why' behind each aspect.

What Will You Learn?

Throughout this course, we will learn all the relevant concepts and implement everything within AWS, the most widely utilized cloud platform, ensuring practical, hands-on experience with the industry standard.

However, the knowledge and skills you acquire are designed to be universally applicable, equipping you with the expertise to operate confidently across any cloud environment.

Foundational Concepts: Understand what Data Lakes are, their benefits, and how they differ from traditional data warehouses.
Architecture Mastery: Dive deep into Data Lake architecture, understanding different zones, tools, and data formats.
Data Ingestion Techniques: Master various data ingestion methods, including batch and event-driven ingestion, and learn to use AWS Glue and Kinesis.
Storage Management: Explore key concepts of data storage management in Data Lakes, such as partitioning, lifecycle management, and versioning.
Processing and Transformation: Learn about Hadoop, Spark, and how to optimize data processing and transformation in Data Lakes.
Workflow Orchestration: Understand how to automate data workflows in a Data Lake environment, using retail data scenarios for practical insights.
Advanced Analytics: Unlock the power of analytics in Data Lakes with tools like Power BI, QuickSight, and Jupyter Notebooks.
Monitoring and Security: Learn the essentials of monitoring Data Lakes and implementing robust security measures.

Who Is This Course For?

Whether you're ...

a beginner aspiring to become a data engineer / data architect or
an experienced professional seeking to specialize in Data Lakes gaining incredibly valuable skills,
or just want to learn some of the most valuable skills

... this is the right course for you!

Your Path to Becoming a Data Lake Expert:

This course is tailored for aspiring data engineers, IT professionals, and anyone keen on mastering Data Lakes. You will emerge with the confidence and skills to design, implement, and manage Data Lakes, elevating your professional standing in the world of cloud data engineering.

Enrollment Benefits:

Complete Guide: From basic concepts to advanced strategies, this course is your one-stop-shop for Data Lake expertise.
Real-World Skills: Equip yourself with practical skills that are immediately applicable in professional settings.
Lifetime Access: Join and gain lifetime access to course all materials.
Community and Support: Join a community of learners and receive dedicated support throughout your learning journey.

Enroll Today!

Join now and gain an almost unfair advantage in the realm of Cloud Data Engineering with Data Lakes. This course is your shortcut to becoming a Data Lake expert, offering you the blueprint to success in this rapidly evolving field.

Get instant and lifetime access – backed by a no-questions-asked 30-day money-back guarantee. See you inside the course!

Who this course is for:

Aspiring Data Engineers looking to start or advance their career
Cloud Technology Enthusiasts with an interest in Big Data
IT Professionals who want to expand their skillset to include Data Lake skills
Anyone that wants to add Data Lake skills to their skillset

Data Lake Mastery: The Key to Big Data & Data Engineering

What you'll learn

Explore related topics

Course content

Introduction11 lectures • 57min

Data Lake Architecture & Components5 lectures • 28min

Data Ingestion16 lectures • 1hr 46min

Data Storage Management18 lectures • 1hr 50min

Processing and Transformation8 lectures • 1hr 11min

Workflow Orchestration6 lectures • 35min

Analytics in a Data Lake6 lectures • 58min

Monitoring6 lectures • 42min

Access Control6 lectures • 31min

Security & Additional Governance7 lectures • 40min

Requirements

Description

Who this course is for: