Data Engineering Immersion Day

About This Program

Join Wizeline Academy for a free, virtual Immersion Day experience that takes attendees on a journey to build a cloud-native and future-proof Serverless Data Lake solution on AWS. 

In this Immersion Day you will learn about: 

  • AWS Big Data solutions
  • Analytics services including Amazon Kinesis Services for streaming data ingestion and analytics
  • AWS Data Migration service for batch data ingestion
  • AWS Glue for data catalog and run ETL on Data lake
  • Amazon Athena to query data lake and Amazon Quicksight for visualization. 
  • Shift the focus from traditional server-based setup using AWS foundation services to more sophisticated and higher-level managed services.


Join us to expand your knowledge of AWS, roll up your sleeves, and explore these technologies through a variety of talk topics and hands-on lab sessions. 

Why Attend?

  • Learn at your own speed, from the comfort of your home 
  • Have access to certified AWS experts and an AWS Partner Ambassador to get your questions answered in real-time  
  • The main idea of an Immersion Day is to inspire development teams to think outside the box, get hands-on with AWS services, and spread the idea of serverless applications inside the organization



Who should take this course?

  • Data Engineers
  • Developers
  • Data Architects


Franchesco Romero

Staff Site Reliability Engineer

Franchesco has over 17 years of experience in software development and infrastructure automation in the health care, media, retail and financial industries. He is currently the lead of Wizeline’s Cloud and DevOps practice.
At Wizeline, he is most passionate about creating a culture of data-driven continuous improvement through automation in the Cloud.
In his free time, he enjoys experimenting with new cloud technologies and taking CrossFit classes


May 20
Module 0 - Intro
09:45 - 10:00
Module 1 - Overview of the Data Lake
10:00 - 10:30
Module 2 - Hydrating the Data Lake
10:30 - 11:00
Break / Q&A
11:00 - 11:15
Module 3 - Hydrating the Data Lake with Kinesis Lab
11:15 - 11:45
Module 4 - Working within the Data Lake
11:45 - 12:15
Module 5 - Transforming and Querying Data in the Data Lake
12:15 - 12:45
Break / Q&A
12:45 - 13:00
Module 6 - Consuming the Data Lake - Reporting, Analytics, Machine Learning
13:00 - 13:30
Module 7 - Extending, Consuming Data Lake for Machine Learning
13:30 - 14:00
Module 8 - Automating the Data
14:00 - 14:30
Break / Q&A
14:30 - 14:45
Module 9 - Data Lake Automation
14:45 - 15:15
Closing / Q&A
15:15 - 15:30

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