We live in an era where data defines business and is also growing exponentially, specifically in the cloud. Organizations that can empower their business with easy-to-use, fast, and real-time data will have a competitive edge over their peers; it is estimated that such organizations will save over $430 billion by 2020 compared to their peers.
Amazon QuickSight is an innovative next-generation cloud-powered BI service that makes it easy for anyone to build visualizations, perform ad hoc analysis, and quickly get business insights from their data. QuickSight delivers fast and responsive insights on big data and can scale to hundreds of users at a fraction of the cost when compared to traditional BI tools.
This practical example-rich guide begins by introducing you to Amazon QuickSight and reviewing what makes it unique, and explains how to get started building your first analysis on QuickSight. Moving ahead, you will get to know the entire AWS big data ecosystem, right from ingesting the data into various storage services and then use QuickSight's features to gain insights. We will next review how to perform lightweight transformations of the data within QuickSight in order to easily enrich your data and insights. Next, we will check out the various visualizations supported by QuickSight including analyses, dashboards, and story features that enable collaboration with your peers. We will next look at the QuickSight mobile application that empowers you with dashboards on the go. We will next look at how to build an end-to-end architecture for big data analytics using AWS Data Lake solution, which packages the most commonly needed components to jump-start such projects. Towards the end, you will learn what features the product is lacking and what's on the roadmap.
Throughout the book, you will be guided with step-by-step instructions, screenshots, data flow, and architecture models that you can reuse for your initiatives.
Chapter 1, A Quick Start to QuickSight, gives an overview of Amazon QuickSight and how it differs to traditional BI tools.
Chapter 2, Exploring Any Data, explains that QuickSight can analyze data from various sources including AWS data stores, files in common format, Salesforce, and popular database engines. QuickSight has a simple interface to connect to these sources and create datasets from them that can be stored in SPICE for subsequent analysis. In this chapter, we will first look at Amazon's big data ecosystem and then review how QuickSight can be used to connect to the various data stores.
Chapter 3, SPICE up Your Data, explores SPICE which is the accelerator of QuickSight, delivering interactive visualizations on large data sets in less than 60 seconds. SPICE is engineered with parallelism, automatic replications, and a rich calculation engine to serve thousands of users who can simultaneously perform fast interactive queries.
Chapter 4, Intuitive Visualizations, looks at visualization capabilities in detail. QuickSight can create a wide variety of visuals on different datasets imported to SPICE.
Chapter 5, Secure Your Environment, explains that to secure your BI environment you need to control which users have access to QuickSight and also what resources QuickSight has permissions to read.
Chapter 6, QuickSight Mobile, covers the QuickSight iOS mobile app. It allows you to stay connected to your data from anywhere, anytime, on your iPhone, iPad, or iPod touch. You can visualize, explore, and share your analyses, dashboards, and stories with an intuitive user experience and get answers to business questions in your palm.
Chapter 7, Big Data Analytics Mini Project, has a real-life use case leveraging the AWS Data Lake solution. Modern data architectures are moving to a data lake solution that has the ability to ingest data from various sources, transform, and analyze at big data scale. Amazon now offers a data lake solution that packages the most commonly needed big data components along with a web application to jump-start the data lake build out.
Chapter 8, QuickSight Product Shortcomings, covers some shortcomings of QuickSight. While the product is revolutionary and has a bold vision, there are several shortcomings in the current version for it to replace enterprise solutions, which are discussed in this final chapter.