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.
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.
“As an IT professional I need accredited training and your courses meet that criteria with the bonus of great customer care”
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.