[PDF] Data Engineering with AWS: Learn how to

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS.

Data-Engineering-with-AWS.pdf
ISBN: 9781800560413 | 482 pages | 13 Mb

• Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS
• Page: 482
• Format: pdf, ePub, fb2, mobi
• ISBN: 9781800560413
• Publisher: Packt Publishing

Download Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS

Google book download link Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS 9781800560413 by

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 Book Description: 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 by 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 by 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. By 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 Who this book is for: This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone who is new to data engineering and wants to learn about the foundational concepts while gaining practical experience with common data engineering services on AWS will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book but is not needed. Familiarity with the AWS console and core services is also useful but not necessary.

Using cloud-based, data-informed, power system models to
However, to extract the full value of AWS, one must reinvent and transform the field of grid model-based engineering by leveraging a cloud-based 
Learn Amazon SageMaker: A guide to building, training, and
Build, train, and deploy machine learning models quickly using Amazon Data Engineering with AWS: Learn how to design and build cloud-based data 
Modern Data Engineering in Cloud Platform - Tech Blost
To modernize data pipelines and manage the workload in cloud-based understanding of using AWS data analytics services to design, build, secure, 
New Releases in Data Modeling & Design - Amazon.com
Data Engineering with AWS: Learn how to design and build cloud-based data Building Big Data Pipelines with Apache Beam: Use a single programming model 
The best-selling new & future releases in Databases & Big Data
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale Data Engineering with AWS: Learn how to design and build cloud-based data 
Data Engineering with AWS, Published by Packt - GitHub
This is the code repository for Data Engineering with AWS, published by Packt. Learn how to design and build cloud-based data transformation pipelines using 
Etleap: ETL and Data Pipelines
Perfect data pipelines from day one. Create perfect data pipelines and data warehouses with an analyst-friendly and maintenance-free ETL solution.
Data Engineering using AWS Analytics Services | Udemy
Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lake or Data Warehouse and then from Data Lake or Data 
The Data Engineering Cookbook - Kindle Store - Amazon.com
Amazon.com: The Data Engineering Cookbook: Mastering The Plumbing Of Data Data Engineering with AWS: Learn how to design and build cloud-based data 

Other ebooks:
DOWNLOAD [PDF] {EPUB} Seven Girls Gone (Quinn & Costa Thriller #4) by Allison Brennan, Allison Brennan
[PDF EPUB] Download Look Smart by Smartypants Romance, Aly Stiles, Smartypants Romance, Aly Stiles Full Book
{pdf download} The Conjure-Man Dies by Rudolph Fisher
[Descargar pdf] KIM JI-YOUNG, NACIDA EN 1982
INDIGNO DE SER HUMANO leer pdf
DOWNLOADS Bescherelle poche Mieux rédiger - L'essentiel pour améliorer son expression
Marvel Classic Novels - Wolverine: Weapon X Omnibus by Marc Cerasini, David Alan Mack, Hugh Matthews on Iphone New Format