Building Data Lakes on AWS Course
- Duration: 8 Hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The Building Data Lakes on AWS Course delivers comprehensive training on creating, managing, and leveraging data lakes on the AWS cloud platform. It helps learners understand the value of data lakes, differentiate them from traditional data warehouses, and identify the components of effective data lake architectures. The course covers data ingestion, cataloguing, preparation, processing, and analytics using services like AWS Lake Formation, AWS Glue, and Amazon Athena. Through hands‑on labs, participants gain real‑world experience in building and automating data lakes and visualizing insights using tools like Amazon QuickSight.
Course Details
- Grasp foundational and advanced data lake concepts and cloud analytics architectures
- Learn to ingest, catalog, prepare, and process data using AWS native services
- Gain hands on experience creating operational data lakes with AWS Lake Formation
- Understand data querying and analysis with Amazon Athena
- Develop skills to automate data lake creation and integrate analytics workflows
- Strengthen capabilities for data engineering and analytics centric cloud roles
- Targeted at data engineers, analytics professionals, BI developers, cloud architects, and IT professionals focused on data management
- Familiarity with AWS fundamentals and data processing concepts is beneficial
- Prior experience with SQL, cloud infrastructure, or analytics workflows enhances learning outcomes
- No mandatory certification required, though AWS Technical Essentials and Data Fundamentals knowledge aids comprehension
- Articulate the value and architecture of data lakes versus data warehouses
- Configure AWS services for data ingestion, cataloging, and preparation
- Build and manage data lakes using AWS Lake Formation and AWS Glue
- Perform data cataloging and transformation operations
- Query and analyze data through Amazon Athena
- Automate data lake workflows and visualize results using Amazon QuickSight
- Apply best practices in security, governance, and performance for data lake solutions
- Introduction to data lakes: purpose, components, and architectures
- Data ingestion, cataloguing, and preparation techniques
- Data processing and analytics workflows
- Building operational data lakes with AWS Lake Formation
- Security, access control, and governance in data lakes
- Automation and orchestration of data lake operations
- Querying data with Amazon Athena
- Hands on labs with AWS Glue, Lake Formation, and QuickSight demonstrations
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