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Building Data Lakes on AWS Training
Live Online & Classroom Enterprise Certification Training
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Building Data Lakes on AWS is a course that teaches how to design, build, and manage scalable data lakes using AWS services like Amazon S3, AWS Glue, Lake Formation, and Athena for efficient data storage, cataloging, and analytics.
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What is Building Data Lakes on AWS Certification Training about?
What are the objectives of Building Data Lakes on AWS Certification Training ?
Who is Building Data Lakes on AWS Certification Training for?
What are the prerequisites for Building Data Lakes on AWS Certification Training?
Available Training Modes
Live Online Training
Classroom Training
1 DaysCourse Outline Expand All
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- 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-effectivness
- 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
Who is the instructor for this training?
The trainer for this Building Data Lakes on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.
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