AWS Data Warehouse - Build with Redshift and QuickSight | Liya Peng | Skillshare

AWS Data Warehouse - Build with Redshift and QuickSight

Liya Peng, IT Consultant/Business Mentor/Blogger

Play Speed
  • 0.5x
  • 1x (Normal)
  • 1.25x
  • 1.5x
  • 2x
34 Videos (2h 4m)
    • 1.0 Welcome

      5:55
    • 1.1 Why build a data warehouse?

      3:00
    • 1.2 End-to-End Analytics Processing on AWS

      2:42
    • 1.3 Deploy Data Warehouse on Redshift

      2:22
    • 1.4 Prerequisites and Sample Flow

      0:55
    • 1.5 AWS Data Warehouse Overview Summary

      0:41
    • 2.0 Redshift Architecture Overview

      2:55
    • 2.1 Performance - Columnar Data Storage

      2:44
    • 2.2 Performance - Data Compression

      1:58
    • 2.3 Performance - Massively Parellel Processing

      1:58
    • 2.4 Redshift System Overview Summary

      0:40
    • 3.0 Cluster Management Overview

      0:50
    • 3.1 Database Review

      1:16
    • 3.2 Lab: Launch Redshift Cluster

      11:29
    • 3.3 Cluster Node Types

      1:48
    • 3.4 Lab: Manage Cluster

      3:11
    • 3.5 Cluster Summary

      1:37
    • 4.0 Monitoring and Logs Overview

      0:48
    • 4.1 Lab: Cluster Monitoring

      8:31
    • 4.2 Lab: Workload Management

      5:02
    • 4.3 Lab: Auditing Logs

      3:50
    • 4.4 Monitoring and Logs Summary

      0:58
    • 5.0 Data Operations Overview

      0:30
    • 5.1 Design Database

      3:50
    • 5.2 Load, Unload, Backup and Restore

      3:29
    • 6.0 AWS QuickSight

      1:58
    • 6.1 Lab: Analytics and Visualization

      12:40
    • 7.0 Redshift Security

      3:06
    • 8.0 Congratulations!

      2:00
    • Bonus: AWS Machine Learning on AWS Redshift Data Part I

      8:13
    • Bonus: AWS Machine Learning on AWS Redshift Data Part II

      7:18
    • Bonus: Redshift Spectrum Overview

      3:15
    • Bonus: Redshift Spectrum Query Life

      3:27
    • Bonus Lab: Query Data From Redshift Spectrum

      8:57

About This Class

This course AWS Data Warehouse - Build with Redshift and QuickSight covers all of the main concepts you need to know about Data Warehouse and Redshift. This course assumes you have no experience on Redshift but are eager to learn AWS solution on Data Warehouse. This course has seven hands-on labs from launching Redshift cluster, loading data, managing cluster, monitoring performance to visualizing data on QuickSight. The advanced experimental bonus sections focus on the latest Redshift features. You will learn Redshift essentials, QuickSight visualization, and Machine Learning prediction. You will also get the basic knowledge of other associated AWS services (e.g. S3, IAM, VPC, CloudWatch, and CloudTrial) during this step-by-step deploying and analytical processing. Plus the advanced knowledge of Redshift usage on data streaming and machine learning.

Once you have completed this course, you should be able to deploy your data warehouse on Redshift, operate and maintain data, analyze and visualize data on Quicksight, and set up security for Redshift.  

Advanced Bonus Sections:

  • Hands-on lab: AWS Machine Learning on Redshift Data (published 07/2018)
  • Redshift Spectrum (published 09/2018)
  • Redshift with Kinesis (incoming Q1/2019)

11

Students

--

Projects

  • --
  • Beginner
  • Intermediate
  • Advanced
  • All Levels
  • Beg/Int
  • Int/Adv

Level

Community Generated

The level is determined by a majority opinion of students who have reviewed this class. The teacher's recommendation is shown until at least 5 student responses are collected.

Liya Peng

IT Consultant/Business Mentor/Blogger

Liya Peng is an IT consultant, certified business mentor, and blogger. With 20 years of experience in the financial service industry, Ms. Peng focused on various multi-million dollar projects to support global financial transactions; the technical infrastructure refresh to enhance overall performance and functionalities; project management and team building/mentoring to ensure a successful consistency of on-time and under budget result; and so...

See full profile

Report class