Big Data Analysis on AWS and Microsoft Azure

In this course you will learn about various cloud services on AWS and Microsoft Azure that can be used for simple Data Analytics and Big Data Analytics. You can choose a combination of cloud resources and methods that can be integrated together to build a solution and various use cases. This course begins with lessons on Amazon Glue that is widely used by developers to build a crawler that can span through a variety of data sources and fetch some useful data from them and store those information in Amazon Athena as datasets. Later on, we can perform various types of operations and run SQL queries on Athena just any other database for finding useful insights from dataset. Moreover, you can also prepare a dataset by transforming it using SQL.What You'll Learn:Introduction to Cloud-Based Data Analytics: Understand the significance of cloud platforms in today's data-driven world and how AWS and Microsoft Azure stand out in this domain.Exploring AWS Services:Amazon Glue: Discover how developers leverage Amazon Glue to craft crawlers that can navigate through diverse data sources, extracting valuable data. These datasets are then stored in Amazon Athena.Amazon Athena: Dive into the functionalities of Athena, which allows you to execute SQL queries and operations, akin to traditional databases, to derive meaningful insights from your datasets. Learn the art of data transformation using SQL.Amazon S3: Get hands-on experience in creating an S3 bucket, adding datasets, and understanding its integration with other AWS services.AWS Glue Advanced Features: Delve deeper into configuring output database names for crawlers, customizing schemas, understanding table details in Glue, and exploring log groups in the cloud.Practical SQL with Athena: Run SQL queries on Athena, s