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

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

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

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 EngineeringAre 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!

Overview

Section 1: Introduction

Lecture 1 Welcome & About This Course

Lecture 2 All slides & files

Lecture 3 What is a Data Lake?

Lecture 4 Benefits of a Data Lake

Lecture 5 Key Terms & Concepts

Lecture 6 Data Lake vs. Data Warehouse vs. Lakehouse

Lecture 7 Understanding the different Tiers in AWS

Lecture 8 AWS Account Setup

Lecture 9 Setting a budget

Lecture 10 Creating S3 buckets

Section 2: Data Lake Architecture & Components

Lecture 11 Essential Elements of a Data Lake

Lecture 12 High Level Overview of Data Flow

Lecture 13 Different Zones in Data Lake

Lecture 14 Tools for the different zones

Lecture 15 Data Formats used In a Data Lake

Section 3: Data Ingestion

Lecture 16 Data Ingestion Methods

Lecture 17 Basics of Batch Ingestion

Lecture 18 Data Catalog & Profiling

Lecture 19 Project Scenario

Lecture 20 Note: Cost of running Glue Jobs

Lecture 21 Hands-on: Data Catalog & Crawlers

Lecture 22 Batch Ingestion with AWS Glue

Lecture 23 Ingestion Patterns

Lecture 24 Event-Driven Ingestion

Lecture 25 Data Profiling

Lecture 26 In-Place Querying

Lecture 27 Athena In-Place Querying

Lecture 28 Understand Data Streaming

Lecture 29 AWS Kinesis Streaming

Lecture 30 Monitoring and Troubleshooting

Lecture 31 Hands-on: Monitoring & Troubleshooting

Section 4: Data Storage Management

Lecture 32 Key Concepts for Data Storage Management

Lecture 33 Environment Overview

Lecture 34 Partitioning

Lecture 35 Folder Structure

Lecture 36 Automatic Partition Creation

Lecture 37 Manually Updating the Data Catalog

Lecture 38 Schema Changes

Lecture 39 Data Lifecycle Management

Lecture 40 Hands-on: Storage Classes

Lecture 41 Hands-on: Lifecycle Rules

Lecture 42 Intelligent Tiering

Lecture 43 Hands-on: Versioning in S3

Lecture 44 Replication

Lecture 45 Cross-Region Replication

Lecture 46 Backups & Recovery

Lecture 47 Hands-on: Backup & Recover

Lecture 48 Hands-on: Backup Plan

Section 5: Processing and Transformation

Lecture 49 Understanding Data Processing in Data Lakes

Lecture 50 Hadoop

Lecture 51 Spark

Lecture 52 Data Integration with AWS Glue

Lecture 53 Hands-on: Data Transformations

Lecture 54 Incremental Loads

Lecture 55 Processing a Stream

Lecture 56 Cost optimization in Data Lakes

Section 6: Workflow Orchestration

Lecture 57 Understand Workflow Orchestration

Lecture 58 Scenario Automating Retailer Data Lake

Lecture 59 Creating the individual tasks

Lecture 60 Create Workflow Logic

Lecture 61 Conditional Logic

Section 7: Analytics in a Data Lake

Lecture 62 Understanding Analytics in a Data Lake

Lecture 63 Data Exploration & adhoc Queries

Lecture 64 Connecting BI Tool (Power BI)

Lecture 65 Business Analytics with QuickSight

Lecture 66 Creating Jupyter Notebooks

Lecture 67 Data Exploration using Notebooks

Section 8: Monitoring

Lecture 68 The Need for Monitoring in Data Lake

Lecture 69 Toolset for Monitoring

Lecture 70 Monitoring Using Metrics

Lecture 71 Setting up Dashboards

Lecture 72 Setting up alarms

Lecture 73 Using Logs

Section 9: Access Control

Lecture 74 Access Control in Data Lakes

Lecture 75 Principle of Least Privilege (PoLP)

Lecture 76 Role-Based Access Control (RBAC)

Lecture 77 Implementation of RBAC

Lecture 78 Testing RBAC

Lecture 79 Custom policies

Section 10: Security & Additional Governance

Lecture 80 Multi-Layered Security Strategy

Lecture 81 Cloud Trail

Lecture 82 Encryption

Lecture 83 Hands-on: Encryption

Lecture 84 Using Tags

Lecture 85 Hands-on: Setting up Tags

Lecture 86 Cost & Lifecycle Management with Tags

Section 11: Data Lake Strategy & Leadership

Lecture 87 Data Lake Strategy & Leadership

Lecture 88 Vision & Assessment of Needs in Data Lake

Lecture 89 Identifying and Involving Key Stakeholders

Lecture 90 Data Governance Framework & Team

Lecture 91 Defining Governance Standards

Lecture 92 Setting up Data Lake Team

Lecture 93 Roadmap Development

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