Building a Serverless Data Lake on AWS is a one-day, advanced-level bootcamp designed to teach you how to design, build, and operate a serverless data lake solution with AWS services.
Each participant will leave with a recognised certificate
The bootcamp will include topics such as ingesting data from any data source at large scale, storing the data securely and durably, enabling the capability to use the right tool to process large volumes of data, and understanding the options available for analyzing the data in near-real time.
This course teaches you how to: Collect large amounts of data using services such as Kinesis Streams and Firehose and store the data durably and securely in Amazon Simple Storage Service.
Create a metadata index of your data lake.
Choose the best tools for ingesting, storing, processing, and analyzing your data in the lake.
Apply the knowledge to hands-on labs that provide practical experience with building an end-to-end solution.
This course covers the following concepts:
Key services that help enable a serverless data lake architecture
A data analytics solution that follows the ingest, store, process, and analyze workflow
Repeatable template deployment for implementing a data lake solution
Building a metadata index and enabling search capability
Setup of a large scale data ingestion pipeline from multiple data sources
Transformation of data with simple functions that are event-triggered
Data processing by choosing the best tools and services for the use case
Options available to better analyze the processed data
Best practices for deployment and operations
Our clients have included prestigious national organisations such as Oxford University Press, multi-national private corporations such as JP Morgan and HSBC, as well
as public sector institutions such as the Department of Defence and the Department of Health.