Book Image

The Self-Taught Cloud Computing Engineer

By : Dr. Logan Song
Book Image

The Self-Taught Cloud Computing Engineer

By: Dr. Logan Song

Overview of this book

The Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure Cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.
Table of Contents (24 chapters)
1
Part 1: Learning about the Amazon Cloud
9
Part 2:Comprehending GCP Cloud Services
14
Part 3:Mastering Azure Cloud Services
19
Part 4:Developing a Successful Cloud Career

Amazon Data Analytics Services

Amazon provides analytics tools and services for many forms of data. Continuing from the Amazon Web Services (AWS) database discussions in the previous chapter, we will focus on the AWS big data analytics services in this chapter.

What is big data? In a nutshell, big data refers to big and complex datasets that are difficult to process using traditional data analytics tools. Big data is typically characterized by its volume, velocity, and variety:

  • Volume: Big data refers to datasets that are too large to be processed using traditional database management systems. The size of big data can range from terabytes to petabytes, and it is often generated in real time.
  • Velocity: Big data is often generated at a high velocity, meaning that it is created and collected rapidly. This requires real-time or near-real-time processing and analysis to turn the data into meaningful insights.
  • Variety: Big data comes in many different forms, including...