Free Big Data Tutorial – Big Data Analysis on AWS and Microsoft Azure
Learn about cloud services for Data Analytics on AWS and Microsoft Azure. Build solutions and gain insights from datasets using Glue, Athena, HDInsight, and more. Perfect for students and IT professionals interested in Cloud Computing and Data Analytics careers.
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.
On AWS, you will learn about-
Create a S3 bucket and add dataset
Create a Crawler using AWS Glue
Configuring output database name for crawler
Customize Schema, find table details in Glue and Log groups in Cloud
Run SQL Queries on Athena and store output in S3 bucket
Create and Save Custom Query in AWS Athena
After covering AWS Glue, S3 and Athena, you would learn about various Data Analysis services on Microsoft Azure. You will learn with hands-on practical lessons first on Azure HDInsight followed by Streaming Analysis.
On Microsoft Azure, you will learn about-
Stream Analytics
HDInsight
Who this course is for:
- Anyone who is curious to learn Data Analysis on AWS Cloud
- Students and IT professionals interested in learning AWS Glue, Athena
- Interested in creating a Crawler in AWS Glue to create a dataset with schema
- Would be interested in learning various Big Data Analytics services and options available on Microsoft Azure.
- Want to make a career in Cloud Computing and Data Analytics.
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