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Data Engineering with AWS Cookbook: A recipe-based approach to help you tackle
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Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- Book Title
- Data Engineering with AWS Cookbook: A recipe-based approach to he
- Publication Date
- 2024-11-29
- ISBN
- 9781805127284
About this product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1805127284
ISBN-13
9781805127284
eBay Product ID (ePID)
19072886929
Product Key Features
Language
English
Publication Name
Data Engineering with AWS Cookbook : A Recipe-Based Approach to Helping You Tackle Data Engineering Problems with AWS Services
Subject
Engineering (General), Data Modeling & Design, Data Processing, Databases / Data Mining
Publication Year
2024
Type
Textbook
Subject Area
Computers, Technology & Engineering
Format
Trade Paperback
Dimensions
Item Length
92.5 in
Item Width
75 in
Additional Product Features
Intended Audience
Trade
Dewey Edition
23
Dewey Decimal
006.78
Synopsis
Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations Key Features Get up to speed with the different AWS technologies for data engineering Learn the different aspects and considerations of building data lakes, such as security, storage, and operations Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning Purchase of the print or Kindle book includes a free PDF eBook Book Description Performing data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction.Through clear explanations and hands-on exercises, you'll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you'll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges.Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence. What you will learn Define your centralized data lake solution, and secure and operate it at scale Identify the most suitable AWS solution for your specific needs Build data pipelines using multiple ETL technologies Discover how to handle data orchestration and governance Explore how to build a high-performing data serving layer Delve into DevOps and data quality best practices Migrate your data from on-premises to AWS Who this book is for If you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended. ]]>, Master AWS data engineering services and techniques for orchestrating pipelines, building layers, and managing migrations Key Features: - Get up to speed with the different AWS technologies for data engineering - Learn the different aspects and considerations of building data lakes, such as security, storage, and operations - Get hands on with key AWS services such as Glue, EMR, Redshift, QuickSight, and Athena for practical learning - Purchase of the print or Kindle book includes a free PDF eBook Book Description: Performing data engineering with Amazon Web Services (AWS) combines AWS's scalable infrastructure with robust data processing tools, enabling efficient data pipelines and analytics workflows. This comprehensive guide to AWS data engineering will teach you all you need to know about data lake management, pipeline orchestration, and serving layer construction. Through clear explanations and hands-on exercises, you'll master essential AWS services such as Glue, EMR, Redshift, QuickSight, and Athena. Additionally, you'll explore various data platform topics such as data governance, data quality, DevOps, CI/CD, planning and performing data migration, and creating Infrastructure as Code. As you progress, you will gain insights into how to enrich your platform and use various AWS cloud services such as AWS EventBridge, AWS DataZone, and AWS SCT and DMS to solve data platform challenges. Each recipe in this book is tailored to a daily challenge that a data engineer team faces while building a cloud platform. By the end of this book, you will be well-versed in AWS data engineering and have gained proficiency in key AWS services and data processing techniques. You will develop the necessary skills to tackle large-scale data challenges with confidence. What You Will Learn: - Define your centralized data lake solution, and secure and operate it at scale - Identify the most suitable AWS solution for your specific needs - Build data pipelines using multiple ETL technologies - Discover how to handle data orchestration and governance - Explore how to build a high-performing data serving layer - Delve into DevOps and data quality best practices - Migrate your data from on-premises to AWS Who this book is for: If you're involved in designing, building, or overseeing data solutions on AWS, this book provides proven strategies for addressing challenges in large-scale data environments. Data engineers as well as big data professionals looking to enhance their understanding of AWS features for optimizing their workflow, even if they're new to the platform, will find value. Basic familiarity with AWS security (users and roles) and command shell is recommended. Table of Contents - Managing Data Lake Storage - Sharing Your Data Across Environments and Accounts - Ingesting and Transforming Your Data with AWS Glue - A Deep Dive into AWS Orchestration Frameworks - Running Big Data Workloads with Amazon EMR - Governing Your Platform - Data Quality Management - DevOps - Defining IaC and Building CI/CD Pipelines - Monitoring Data Lake Cloud Infrastructure - Building a Serving Layer with AWS Analytics Services - Migrating to AWS - Steps, Strategies, and Best Practices for Modernizing Your Analytics and Big Data Workloads - Harnessing the Power of AWS for Seamless Data Warehouse Migration - Strategizing Hadoop Migrations - Cost, Data, and Workflow Modernization with AWS
LC Classification Number
TK5105.88813.P4 2024
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Seller feedback (522,375)
- l***1- Feedback left by buyer.Past monthVerified purchasebook was on good condition
- 9***9 (1)- Feedback left by buyer.Past monthVerified purchaseBook was like new!
- a***c (254)- Feedback left by buyer.Past monthVerified purchaseGood price . Good quality dvd . Fast delivery and a Good Seller.