Building Data Lakes on AWS Course

Intermediate-level training from AWS

7 specialised modules with real-time projects

Use AWS Lake Formation to build a data lake

Learn with course lectures & hands-on labs

Gain access to high-quality study materials

Expert guided preparation with mock exams

Hassle-free payment options

Flexible training available

4.9/5

6694 Enrolled

Overview

What our training includes:

Explore key components of data lakes
Understand common lake-based architecture designs
Ingest and organise data using AWS Glue
Build data catalogs with AWS Glue crawlers
Use AWS Lake Formation to process data
Query lake data with Amazon Athena
Configure advanced permissions and tag-based policies

Learning Outcomes

After finishing the course, you will be able to:

Understand the core value and purpose of building data lakes

Compare key differences between data lakes and data warehouses

Use AWS Glue crawlers to create an organised data catalog

Analyse data within the lake using Amazon Athena and queries

Create and secure scalable data lakes using AWS Lake Formation

Implement fine-grained access control using AWS Lake Formation features

Build and share data products using Lake Formation and governance tools

Ready to get started?

Prerequisites

Before enrolling in the Building Data Lakes on AWS, the eligibility requirements are as follows:

Completed the AWS Technical Essentials classroom course
One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course

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Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Describe the value of data lakes
Compare data lakes and data warehouses
Describe the components of a data lake
Recognize common architectures built on data lakes

Describe the relationship between data lake storage and data ingestion
Describe AWS Glue crawlers and how they are used to create a data catalog
Identify data formatting, partitioning and compression for efficient storage and query

Recognize how data processing applies to a data lake
Use AWS Glue to process data within a data lake
Describe how to use Amazon Athena to analyze data in a data lake
Lab 01: Building a Data Lake with AWS Lake Formation

Describe the features and benefits of AWS Lake Formation
Use AWS Lake Formation to create a data lake
Understand the AWS Lake Formation security model
Lab 2: Build a data lake using AWS Lake Formation

Explain the available built-in Blueprints to create and populate a new Lake Formation
Describe methods for applying advanced permissions to secure data access and workflow
Describe fine-grained row/cell access control
Explain the Lake Formation Tag-based access control mechanism and the different use cases for Named access control vs. Tag-based access control
Describe access flow that enforces fine-grained access policies to both catalog metadata and underlying data resource for analytics services connecting to Lake Formation

Explain capabilities of a modern data architecture: Scalable data lakes, Purpose-build analytics services, Seamless data movement, unified governance and performance and cost-effectiveness
Articulate the typical data movement within a modern data architecture: Inside out, Outside in, Around the perimeter and Sharing across
Describe focus of building and maintaining data products as a service
Describe a typical Data Mesh architecture using Lake Formation and the key enablers supporting this methodology
Lab 3: Building and publishing a data product in Lake Formation

Post course knowledge check
Architecture review
Course review

Frequently asked questions

Building Data Lakes on AWS Course is a specialized intermediate-level course that teaches you how to build and manage scalable data lakes using Amazon Web Services. Our course helps you utilise the full potential of AWS services to store, organize and analyse massive datasets. A data lake is a centralized repository that allows you to store structured and unstructured data.

To enrol in the AWS Data Lake course, you need to complete these eligibility requirements. These requirements are as follows:

1. Completed the AWS Technical Essentials classroom course
2. One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course

Our Data Lake Course is ideal for professionals who are looking to deepen their expertise in cloud-based data architecture on AWS. Suitable candidates are as follows:

1. Data Engineers
2. Cloud Architects
3. Data Analysts and Scientists
4. Database Administrators (DBAs)
5. IT Professionals

You will learn about several core subject areas related to building a data lake in our training in AWS. These topics will enable professionals to build, secure and analyse data in the AWS cloud. These topic are:

1. Introduction to data lakes
2. Data ingestion
3. Data cataloging and metadata management
4. Data preparation
5. Security and access control
6. Querying and analytics
7. Data lake optimization and performance

After completing the Building Data Lakes on AWS training, you can avail several high-demand career roles in cloud data management, analytics and engineering. These job roles are:

1. Data Engineer
2. Cloud Data Architect
3. Big Data Engineer
4. Data Analyst
5. Machine Learning Engineer
6. ETL Developer
7. Data Platform Engineer
8. Solutions Architect

As a fresher, you can enrol in the Building Data Lakes on AWS training, if you have a strong interest in data engineering, cloud technologies or analytics. However, you must follow the eligibility criteria mentioned before enrolling in this course, as it is an intermediate-level training.

Our course begins with an introduction to data lakes, architecture and core AWS services, which makes it beginner-friendly for the candidates. You get the chance to work with real AWS tools like S3, Glue, Lake Formation, Athena. Our course prepares you with valuable cloud data handling capabilities.

The most suitable AWS service for building data lakes is Amazon S3 (Simple Storage Service). However, we build a data lake using a combination of several AWS services such as using Lake Formation, Glue and Athena to manage, prepare and analyse the data.

Yes, our Building Data Lakes on AWS training is available across different GCC countries. This helps the candidates earn this certification. The several GCC regions include: