In this course you would learn to create Visualization Charts and Data Preparation in AWS Quicksight. It is a powerful Business Intelligence tool that can be used perform a wide range of tasks such as-

• Importing Dataset form multiple sources such as direct upload, S3 bucket, Redshift and other databases in multiple formats such as csv, xls and more.

• Data Cleaning- by removing unwanted rows, columns or fields, from the dataset based on a given condition by using Filters and Excluded lists

• Data Preparation- by adding custom columns or fields by either using a mathematical function or by customizing some existing fields using various function such as concat, ceil and much more

• Changing Field type among String, Integer, Decimal, Country, State, Date, Time and other formats

• Visualization Charts- by taking multiple fields and arranging them in Dimensions and Measures.

• Analytics Dashboard- by creating various visualization charts and combining them on a single page to create a BI report or Analytics dashboard. It could be used to find insights from the dataset and identify trends, outliers and critical information

• Conditional Formatting- by customizing the visual charts in terms of colors, data values, date range, value range and others

You will learning these data skills in this course. Data Science involves various phases from data extraction, data preparation, data cleaning, modelling to data visualization and analysis. With AWS Quicksight, we can perform most of these Data science tasks and you will learn about some of them in the step wise manner. Firstly, you will learn to create a analytics dashboard right from the dataset. You will learn to import a dataset on AWS. Next you will learn to create some of the basic visualization charts such as bar, pie, treemap and other charts. After getting familiar with the Quicksight interface, you will learn to prepare your dataset so that only useful and relevant information in passed to the visualization phase. You will learn to create Filters, Excluded lists and Calculated fields where you could add, remove or modify any of the data element.

After learning data preparation, you will learn to create some of the advanced visualization charts such as Map chart, Pivot table and Sankey chart. Using various charts you can create a analytics dashboard to find useful insights from the dataset.