Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS
Author: Gareth Eagar
Publisher finelybook 出版社: Packt Publishing (December 29,2021)
Language 语言: English
Print Length 页数: 482 pages
ISBN-10: 1800560419
ISBN-13: 9781800560413
Book Description
By finelybook
Start your AWS data engineering journey with this easy-to-follow,hands-on guide and get to grips with foundational concepts through to building data engineering pipelines using AWS
Key Features
Learn about common data architectures and modern approaches to generating value from big data
Explore AWS tools for ingesting,transforming,and consuming data,and for orchestrating pipelines
Learn how to architect and implement data lakes and data lakehouses for big data analytics
Knowing how to architect and implement complex data pipelines is a highly sought-after skill. Data engineers are responsible for building these pipelines that ingest,transform,and join raw datasets – creating new value from the data in the process.
Amazon Web Services (AWS) offers a range of tools to simplify a data engineer’s job,making it the preferred platform for performing data engineering tasks.
This book will take you through the services and the skills you need to architect and implement data pipelines on AWS. You’ll begin Author: reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer’s toolkit. You’ll then architect a data pipeline,review raw data sources,transform the data,and learn how the transformed data is used Author: various data consumers. The book also teaches you about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later,you’ll be introduced to AWS tools for analyzing data,including those for ad-hoc SQL queries and creating visualizations. In the final chapters,you’ll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data.
Author: the end of this AWS book,you’ll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.
What you will learn
Understand data engineering concepts and emerging technologies
Ingest streaming data with Amazon Kinesis Data Firehose
Optimize,denormalize,and join datasets with AWS Glue Studio
Use Amazon S3 events to trigger a Lambda process to transform a file
Run complex SQL queries on data lake data using Amazon Athena
Load data into a Redshift data warehouse and run queries
Create a visualization of your data using Amazon QuickSight
Extract sentiment data from a dataset using Amazon Comprehend
