Book Image

AWS for Solutions Architects - Second Edition

By : Saurabh Shrivastava, Neelanjali Srivastav, Alberto Artasanchez, Imtiaz Sayed
4 (2)
Book Image

AWS for Solutions Architects - Second Edition

4 (2)
By: Saurabh Shrivastava, Neelanjali Srivastav, Alberto Artasanchez, Imtiaz Sayed

Overview of this book

Are you excited to harness the power of AWS and unlock endless possibilities for your business? Look no further than the second edition of AWS for Solutions Architects! Imagine crafting cloud solutions that are secure, scalable, and optimized – not just good, but industry-leading. This updated guide throws open the doors to the AWS Well-Architected Framework, design pillars, and cloud-native design patterns empowering you to craft secure, performant, and cost-effective cloud architectures. Tame the complexities of networking, conquering edge deployments and crafting seamless hybrid cloud connections. Uncover the secrets of big data and streaming with EMR, Glue, Kinesis, and MSK, extracting valuable insights from data at speeds you never thought possible. Future-proof your cloud with game-changing insights! New chapters unveil CloudOps, machine learning, IoT, and blockchain, empowering you to build transformative solutions. Plus, unlock the secrets of storage mastery, container excellence, and data lake patterns. From simple configurations to sophisticated architectures, this guide equips you with the knowledge to solve any cloud challenge and impress even the most demanding clients. This book is your one-stop shop for architecting industry-standard AWS solutions. Stop settling for average – dive in and build like a pro!
Table of Contents (19 chapters)
17
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18
Index

Components of a data lake

The concept of a data lake can vary in meaning to different individuals. As previously mentioned, a data lake can consist of various components, including both structured and unstructured data, raw and transformed data, and a mix of different data types and sources. As a result, there is no one-size-fits-all approach to creating a data lake. The process of constructing a clean and secure data lake can be time-consuming and may take several months to complete, as there are numerous steps involved in the process. Let’s take a look at the components that need to be used when building a data lake:

  • Data ingestion: The process of collecting and importing data into the data lake from various sources such as databases, logs, APIs, and IoT devices. For example, a data lake may ingest data from a relational database, log files from web servers, and real-time data from IoT devices.
  • Data storage: The component that stores the raw data in its original...