Building Data Lakes on AWS in Nigeria
Intermediate-level training from AWS
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
Enjoy easy installment options
Flexible training available
4.34/57955 EnrolledEnrolled Learners
4.34/57955 EnrolledEnrolled Learners
Overview
What will you learn from us:
- Identify the fundamental elements that make up a modern data lake
- Examine typical architectural patterns for building data lakes on AWS
- Utilize AWS Glue to collect, cleanse, and structure data efficiently
- Create detailed data catalogs using AWS Glue crawlers
- Use AWS Lake Formation to handle and process large datasets
- Run SQL queries directly on your data lake with Amazon Athena
- Set up detailed access controls and permissions using tags and fine-grained policies
Upcoming sessions
Curriculum
1
Describe the value of data lakes
2
Compare data lakes and data warehouses
3
Describe the components of a data lake
4
Recognize common architectures built on data lakes
1
Describe the relationship between data lake storage and data ingestion
2
Describe AWS Glue crawlers and how they are used to create a data catalog
3
Identify data formatting, partitioning and compression for efficient storage and query
1
Recognize how data processing applies to a data lake
2
Use AWS Glue to process data within a data lake
3
Describe how to use Amazon Athena to analyze data in a data lake
4
Lab 01: Building a Data Lake with AWS Lake Formation
1
Describe the features and benefits of AWS Lake Formation
2
Use AWS Lake Formation to create a data lake
3
Understand the AWS Lake Formation security model
4
Lab 2: Build a data lake using AWS Lake Formation
1
Explain the available built-in Blueprints to create and populate a new Lake Formation
2
Describe methods for applying advanced permissions to secure data access and workflow
3
Describe fine-grained row/cell access control
4
Explain the Lake Formation Tag-based access control mechanism and the different use cases for Named access control vs. Tag-based access control
5
Describe access flow that enforces fine-grained access policies to both catalog metadata and underlying data resource for analytics services connecting to Lake Formation
1
Explain capabilities of a modern data architecture: Scalable data lakes, Purpose-build analytics services, Seamless data movement, unified governance and performance and cost-effectiveness
2
Articulate the typical data movement within a modern data architecture: Inside out, Outside in, Around the perimeter and Sharing across
3
Describe focus of building and maintaining data products as a service
4
Describe a typical Data Mesh architecture using Lake Formation and the key enablers supporting this methodology
5
Lab 3: Building and publishing a data product in Lake Formation
1
Post course knowledge check
2
Architecture review
3
Course review
Meet your Trainer
Our Trainers
We take immense pride in our skilled instructors and trainers who excel in their chosen fields. Our trainers are globally recognised for their expertise and experience.Learners Point adopts a data driven research approach to learning so the experience is highly customizable and thoroughly engaging for learners from all walks of life. The sessions are classroom-based and led by an instructor. For those who seek more flexibility, we also offer high quality live and interactive sessions online.
Learning Outcomes
After finishing the course, you will be able to:
1
Discover the advantages of data lakes in modern data management strategies
2
Contrast data lakes with conventional data warehouse approaches
3
Utilize AWS Glue crawlers to generate searchable metadata catalogs
4
Perform direct data analysis within lakes using Amazon Athena
5
Build secure and scalable data lakes using AWS Lake Formation
6
Enforce detailed access permissions with Lake Formation
7
Develop and deploy data products using Lake Formation’s built-in tools
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Prerequisites
Before enrolling in the Building Data Lakes on AWS in Dubai, 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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Frequently asked questions
Our course, Building Data Lakes on AWS in Nigeria, teaches you how to design and build efficient data lakes using core AWS services. You learn about data ingestion, cataloging, security, and governance. This training includes hands-on experience with tools like AWS Lake Formation, Amazon S3, AWS Glue, and AWS Redshift. We help you create scalable, secure, and cost-effective data lake solutions.
This course is designed for professionals who work with large volumes of data in cloud environments. It’s ideal for data engineers, cloud architects, analysts, and IT professionals who want to build or manage data lakes on AWS. If you're looking to improve your cloud data handling and analytics skills, this course provides the right foundation.
Our program covers all essential aspects of building data lakes. You start by understanding what data lakes are and how they differ from traditional systems. Topics include data ingestion, cataloging with AWS Glue, secure lake creation with Lake Formation, data governance, and analysis using tools like Amazon EMR and Redshift. You also learn how to design modern, scalable data architectures.
This AWS Data Lakes course in Nigeria boosts your career by giving you practical skills in cloud-based data management. You gain expertise in building and managing data lakes, which are critical for handling big data and analytics. These skills open up opportunities for roles like Data Engineer or Cloud Architect and are valuable in sectors such as finance, healthcare, and technology.
Yes, after completing the course, you receive a certificate of completion. This certificate confirms your knowledge of AWS data lake tools and architecture. It’s a useful credential to show your expertise in cloud data solutions. It enhances your professional profile in Nigeria when applying for roles that require AWS data management experience.
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