Learn Analytics with AWS Athena and Quicksight

Is SQL limited to Relational database, where you can perform CRUD operation with table. Then you're wrong. In the world of data science, after Python and R programing language, SQL is most used programming language. This is true, SQL is used in data science as well.

Google Bigquery, AWS Athena uses SQL for analyzing big data. A big data consists might be petabytes (1,024 terabytes) or exabytes (1,024 petabytes) of data consisting of billions to trillions of records of millions of people. To analyze such a huge data is challenging and with RDBS is impossible. A big data may be structured, semi structured or unstructured data.

In this learning journey, you'll learn and practice about AWS Athena.

What is AWS Athena?

AWS Athena, is an interactive data analysis tool offered by AWS. It uses standard SQL to analyze big data. The reason behind its popularity in industries are mentioned in following points:

• Athena is server-less, there is no infrastructure to manage, and you pay only for the queries that you run.

• Athena uses standard SQL (Presto) to analyze data stored in an AWS S3 bucket.

• It is easy to use AWS analytics tool.

• In comparison to other analytics tools, it fetches results very quickly.

• Easily integrate with BI tools like Tableau

Additionally, you'll also learn about AWS Quicksight, a BI tool offered by Amazon AWS, makes it easy to deliver rich, interactive insights. With the help of ML algorithms you will also able to find hidden insights from the data into charts.

Enroll now and upgrade your data analytics skills.