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Building Data Lakes on AWS
Your analyses depend on available, well-organised data. With AWS, connect collection, transformation and delivery to structure your data flows. Strengthen your ability to design processing aligned with application and business needs.
- Duration
- 1 day 7 hours
- Code
- AWS25FR Code
Presentation
Building data lakes on AWS provides a modern approach to ingesting, storing, transforming and analysing structured and unstructured data. It uses AWS components and services to create scalable, high-performing data architectures.
This intensive course develops practical skills in building and operating data lakes with AWS Lake Formation, AWS Glue and Amazon Athena. Explore essential AWS tools and services for data catalogues, ingestion, transformation and large-scale analysis. Through practical workshops, learn to design and implement data lake solutions, optimise storage and processing, and secure data access.
By the end of this one-day program, you will have the expertise to design high-performing, secure AWS data lake solutions. Master AWS Lake Formation to automate data lake creation and management, and best practices to unlock your cloud data’s potential.
As an Amazon Web Services-approved premium training partner (ATP), Oo2 offers skills development and certification courses meeting AWS’s rigorous quality standards.
Objectives
By the end of this AWS data lake course, you will be able to:
- apply data lake methodologies to planning and design;
- describe the components and services needed to build an AWS data lake;
- secure a data lake with appropriate permissions;
- ingest, store and transform data in a data lake;
- query, analyse and visualise data in a data lake.
Program
Module 1: understanding data lake fundamentals
- Data lake benefits.
- Differences between a data lake and a data warehouse.
- Data lake components.
- Key elements of a typical data lake-based architecture.
Module 2: ingesting, cataloguing and preparing data
- The relationship between data lake storage and ingestion.
- Using AWS Glue crawlers to create a data catalogue.
- Identifying data formatting, partitioning and compression for efficient storage and querying.
Lab:
- Configure a simple data lake.
Module 3: processing and analysing data for the data lake
- Recognising data processing applications.
- Using AWS Glue to process data.
- Using Amazon Athena to analyse data.
Module 4: building the data lake with AWS Lake Formation
- AWS Lake Formation features and benefits.
- Using AWS Lake Formation to create a data lake.
- Features of the AWS Lake Formation security model.
Lab:
- Build a data lake using AWS Lake Formation.
Module 5: advanced AWS Lake Formation configuration
- Automating AWS Lake Formation using blueprints and workflows.
- Implementing security and access controls.
- Record matching with AWS Lake Formation FindMatches.
- Data visualisation with Amazon QuickSight.
Lab:
- Automate data lake creation using AWS Lake Formation blueprints.
- Visualise data with Amazon QuickSight.
Module 6: architecture review and course conclusion
- Knowledge assessment.
- Review of data lake architecture and key course points.
Audience
This course is intended for:
- data platform engineers planning, designing and implementing AWS data lakes;
- solution architects designing and implementing data lake architectures and analytics solutions;
- IT professionals seeking skills in data lake construction, security and analysis;
- data engineers and analysts seeking to query, transform and visualise data in an AWS data lake.
Prerequisites
The following background is recommended:
- completion of AWS Technical Essentials;
- 1 year of experience building data analytics pipelines or completion of Data Analytics Fundamentals.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
Course highlights
- Expert AWS-certified instructors: recognised instructors with in-depth knowledge of AWS data lake construction and analytics services.
- Interactive practical application: master AWS data lake tools and techniques through demonstrations and workshops that prepare you for ingestion, storage, transformation and analysis challenges.
- Key skills: carefully designed content covering data lake planning and design, AWS Lake Formation, AWS Glue data cataloguing and Amazon Athena analysis.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
AWS, AWS Lake Formation, AWS Glue, Amazon Athena, Amazon QuickSight and other AWS brands are registered trademarks of Amazon.com, Inc. or its affiliates.