Big Data - Data Visualization
In this course, we learn how to determine the appropriate techniques for delivering the results/output of a query or analysis. We examine how to design and create a visualization using AWS services, and how to optimize visualization services to present results in an effective and accessible manner. We introduce and outline the core AWS analysis tools and then work through how to integrate and output data to enable business decisions using QuickSight.
Amazon QuickSight makes it easy to build visualizations, perform ad hoc analysis, and quickly get business insides from your data. It has a number of pre-configured reports which take out the undifferentiated heavy lifting of creating visual reports. A benefit of QuickSight is that it's integrated into our AWS dashboard and our AWS account, and this is where reports and graphs can be viewed by team members, staff, etc.
QuickSight also makes it easy for business teams to create and share interactive graphs and reports as stories, and if we have any additional data sources added in the future, those can just simply be added as Amazon QuickSight database sources. When we create visuals using QuickSight, the style and format of graphs are automatically selected by the QuickSight engine, which saves time and improves the quality of reports and visuals.
- Recognize and explain how to determine the appropriate techniques for delivering the results/output of a query or analysis
- Recognize and explain how to design and create data visualizations
- Recognize and explain the operational characteristics to gain simple and timely results from Amazon QuickSight
- [Instructor] Hello, welcome to Data Visualization. In this course, we learn how to determine the appropriate techniques for delivering results or outputs of a query or analysis. So we examine how to design and create a visualization platform using AWS services and how we might optimize visualization services to present results in an effective and accessible manner. So we're going to briefly outline the core visualization tools and then we'll get into how to integrate an output data to enable business decisions using tools like Athena and Amazon Quicksight. Now please allow me to take a moment to introduce myself. My name is Andrew Larkin. I am the AWS Content Lead at Cloud Academy. I'm happy to be your instructor for this course. So please feel free to reach out to me at Andrew.Larkin@CloudAcademy.com if you have any questions or comments and also contact support at CloudAcademy.com if you have any questions or feedback about the content. This course is intended for students wanting to extend their knowledge of how to deliver and present big data results using AWS services. While there are no formal pre-requisites for this course students, I think, will benefit from having a working understanding of big data processing and data analytics. So you might wanna consider completing the following courses first Analytics Fundamentals is a great introduction to how analytics works. And I'd also recommend completing the Big Data Specialty Learning Path if you haven't already done so. Now the core components from that that I think will help you with this course are the Big Data Storage, the Big Data Collection, and Big Data Processing. Our learning objectives for this course are as follows, we wanna be able to recognize and explain how to determine the appropriate techniques for delivering results or outputs of a query or analysis. We wanna be able to recognize and explain how to design and create data visualizations and we wanna be able to recognize and explain the operational characteristics that can helps us get simple and timely results from services like Amazon Quicksight. The focus of this course is to show you how to use the service rather than outline how that service works.
About the Author
Head of Content
Andrew is an AWS certified professional who is passionate about helping others learn how to use and gain benefit from AWS technologies. Andrew has worked for AWS and for AWS technology partners Ooyala and Adobe. His favorite Amazon leadership principle is "Customer Obsession" as everything AWS starts with the customer. Passions around work are cycling and surfing, and having a laugh about the lessons learnt trying to launch two daughters and a few start ups.