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AWS for Solutions Architects - Second Edition

You're reading from AWS for Solutions Architects - Second Edition

Product type Book

Published in Apr 2023

Publisher Packt

ISBN-13 9781803238951

Pages 692 pages

Edition 2nd Edition

Languages

Concepts

Cloud Computing

Authors (4):

Saurabh Shrivastava

Neelanjali Srivastav

Alberto Artasanchez

Imtiaz Sayed

View More author details

Table of Contents (19) Chapters

Preface

1. Understanding AWS Principles and Key Characteristics

2. Understanding the AWS Well-Architected Framework and Getting Certified

3. Leveraging the Cloud for Digital Transformation

4. Networking in AWS

5. Storage in AWS – Choosing the Right Tool for the Job

6. Harnessing the Power of Cloud Computing

7. Selecting the Right Database Service

8. Best Practices for Application Security, Identity, and Compliance

9. Driving Efficiency with CloudOps

10. Big Data and Streaming Data Processing in AWS

11. Data Warehouses, Data Queries, and Visualization in AWS

12. Machine Learning, IoT, and Blockchain in AWS

13. Containers in AWS

14. Microservice Architectures in AWS

15. Data Lake Patterns – Integrating Your Data across the Enterprise

16. Hands-On Guide to Building an App in AWS

17. Other Books You May Enjoy

18. Index

Lakehouse in AWS

A lakehouse architecture is a modern data architecture that combines the best features of data lakes and data warehouses, while a data lake is a large, centralized repository that stores structured and unstructured data in its raw form. To have a structured view of data, you need to load data into the data warehouse. The lakehouse architecture combines a data lake with a data warehouse to provide a consolidated view of data.

The key difference between a lakehouse and a data lake is that a lakehouse architecture provides a structured view of the data in addition to the raw data stored in the data lake, while a data lake only provides the raw data. In a lakehouse architecture, the data lake acts as the primary source of raw data, and the data warehouse acts as a secondary source of structured data. This allows organizations to make better use of their data by providing a unified view of data while also preserving the scalability and flexibility of the data lake...

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Authors (4)

Saurabh Shrivastava

Saurabh Shrivastava is a technology leader, author, inventor, and public speaker with over 18 years of experience in the IT industry. He currently works at Amazon Web Services (AWS) as a Global Solutions Architect Leader and enables global consulting partners and enterprise customers on their journey to the cloud. Saurabh led the AWS global technical partnerships, set his team's vision and execution model, and nurtured multiple new strategic initiatives. Saurabh has authored various blogs and whitepapers across a diverse range of technologies, such as big data, IoT, machine learning, and cloud computing. He is passionate about the latest innovations and their impact on our society and daily life. He holds a patent in the area of cloud platform automation. Before AWS, Saurabh worked as an enterprise solution architect, software architect, and software engineering manager in Fortune 50 enterprises, start-ups, and global product and consulting organizations.

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Neelanjali Srivastav

Neelanjali Srivastav is a technology leader, product manager, agile coach, and cloud practitioner with over 16 years of experience in the software industry. She currently works at Amazon Web Services (AWS) as a Senior Product Manager and enables global customers on their data journey to the cloud. Neelanjali evangelizes and enables AWS customer and partners in AWS database, analytics, and machine learning services. She sets the product vision and cultivates new products in incubation. Before AWS, Neelanjali led teams of software engineers, solutions architects, and systems analysts to modernize IT systems and develop innovative software solutions for large enterprises. Neelanjali has held multiple roles in the IT services industry and R&D, focusing on enterprise application management, cloud service management, and orchestration.

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Alberto Artasanchez

Alberto Artasanchez is a solutions architect with expertise in the cloud, data solutions, and machine learning, with a career spanning over 28 years in various industries. He is an AWS Ambassador and publishes frequently in a variety of cloud and data science publications. He is often tapped as a speaker on topics including data science, big data, and analytics. He has a strong and extensive track record of designing and building end-to-end machine learning platforms at scale. He also has a long track record of leading data engineering teams and mentoring, coaching, and motivating them. He has a great understanding of how technology drives business value and has a passion for creating elegant solutions to complicated problems.

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Imtiaz Sayed

Imtiaz (Taz) Sayed leads the Worldwide Data Analytics Solutions Architecture community at AWS. He is a Principal Solutions Architect, and works with diverse customers engaging in thought leadership, strategic partnerships and specialized guidance on building modern data platforms on AWS. He is a technologist with over 20 years of experience across several domains including distributed architectures, data analytics, service mesh, databases, and DevOps.

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