QuickSight

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Introduction
1
Introduction
PREVIEW3m 11s
2
Analytics Concepts
PREVIEW12m 48s

The course is part of this learning path

AWS Big Data – Specialty Certification Preparation for AWS
course-steps 14 certification 1 lab-steps 4
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Overview
DifficultyBeginner
Duration1h 20m
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Description

In this course, we will explore the Analytics tools provided by AWS, including Elastic Map Reduce (EMR), Data Pipeline, Elasticsearch, Kinesis, Amazon Machine Learning and QuickSight which is still in preview mode.

We will start with an overview of Data Science and Analytics concepts to give beginners the context they need to be successful in the course. The second part of the course will focus on the AWS offering for Analytics, this means, how AWS structures its portfolio in the different processes and steps of big data and data processing.

As a fundamentals course, the requirements are kept simple so you can focus on understanding the different services from AWS. But, a basic understanding of the following topics is necessary:

- As we are talking about technology and computing services, general IT knowledge is necessary, by general IT I mean the basics about programming logic, algorithms, and learning or working experience in the IT field.
- We will give you an overview of data science concepts, but if these concepts are already familiar to you, it will make your journey smoother.
- It is not mandatory but it would be helpful to have a general knowledge about AWS, most specifically about how to access your account and services such as S3 and EC2.

I would like to recommend that you take 2 courses from our portfolio that can help you better understand the AWS basics if you are just beginning with it:

AWS Technical Fundamentals
AWS Networking Fundamentals

If you have thoughts or suggestions for this course, please contact Cloud Academy at support@cloudacademy.com.

Transcript

Welcome to the AWS Analytics Fundamentals course. In this video, we are going to cover the Amazon QuickSight Service.

Amazon QuickSight is a cloud-based business intelligence platform. These run off the newest services from AWS launched on AWS re:invent 2015. As record of this video, the service is not yet available to the public, restricted only to a preview. Amazon QuickSight has been viewed to allow very fast visualizations from your data. It has focus on simplicity, so business users can perform investigations on data and get insights from the data. It's built on SPICE, a new super-fast calculation platform built from scratch by AWS. The focus is that a new user can get started in a very few seconds.

Other important innovations that QuickSight brings are the easy exploration from the data that you already have on AWS, the SPICE platform, intuitive graphs, and transitions with AutoGraph. This is worth a mention, as usually it's hard to decide the best way to aggregate your data. So QuickSight does this for you. If it's a time series, it will show a time series-based graph, like bars or lines. If you have a market share data, it will display in a suitable format for human understanding. It's mobile ready and you can share your dashboards to view, here named as StoryBoards, with your colleagues in a secure way.

One of the main benefits is that QuickSight can index all data you already have on AWS and correlate them from different back ends and services, including also on-premise, third party BI tools. You can get sites from data on EMR, RDS databases, DynamoDB tables, Kinesis streams, S3 buckets, and Redshift clusters. Additionally, you can import your files in CSV or text format, and connect with other BI tools.

QuickSight, after pointed to one or more data services, will correlate and index all this data ready for your investigations. One of the highlights of QuickSight is its brand new processing engine. The SPICE, or super-fast parallel in memory calculation engine, which provides fast replies to the query submitted. In short, a SPICE processing takes place after you point QuickSight to one or more data sources, make questions, so the data will make SPICE to run over the entire data set, correlate, analyze, and provide answers for you by displaying the results on the QuickSight user interface or on third party BI tools that you can easily connect to SPICE.

Let's talk a little bit about pricing. As a BI platform usually takes a lot of time and big investments. So you pay a lot before even seeing the first results or dashboards. With QuickSight, this is dramatically reduced and shaped the cloud the way. You have two versions of QuickSight, the Standard and Enterprise. The main difference is the integration and advanced security settings, which are available only on the Enterprise version. Another feature from QuickSight is the StoryBoard, where you can let your data tell stories by aggregating several tables and graphs covering the same topic. For example, the sales accumulated for the period, generating a story that can be played back in the future and shared among colleagues.

In this graphic, we show briefly internal from QuickSight where we have a starting point, the data which comes from several AWS sources or externals. This data is then submitted to QuickSight, which exposes an API for connecting other tools or generating analyses by SPICE. The results are then played back on the QuickSight user interface, or you can connect it with other BI tools that you already have. All this power available to the business users. So what comes next? If you want to experiment QuickSight, you need to request a preview. So get a credential where you can later on have access to the URL quicksight.aws.amazom.com.

Thanks for watching this video. I hope you have learned and enjoyed a little bit about Amazon QuickSight. Thanks.

About the Author

Fernando has a solid experience with infrastructure and applications management on heterogeneous environments, working with Cloud-based solutions since the beginning of the Cloud revolution. Currently at Beck et al. Services, Fernando helps enterprises to make a safe journey to the Cloud, architecting and migrating workloads from on-premises to public Cloud providers.