Hands-On Amazon Redshift for Data Warehousing

Hands-On Amazon Redshift for Data Warehousing
Hands-On Amazon Redshift for Data Warehousing
English | MP4 | AVC 1920Ă—1080 | AAC 48KHz 2ch | 2h 14m | 472 MB

Build scalable, serverless data warehouses with machine learning and massively parallel processing in the cloud with Amazon Redshift

Amazon Redshift is a low-cost cloud data platform that can scale from gigabytes to petabytes on a high-performance, column-oriented SQL engine. Amazon Redshift brings the power of scale-out architecture to the world of traditional data warehousing.

In this course, you will explore this low-cost, cloud-based storage, which can be scaled up or down to meet your true size and performance needs. You will learn to configure a sample data warehouse. Next, you will explore Redshift’s internal workings and architecture, and learn what makes it so fast. You will get hands-on experience connecting, querying, and building BI and data viz products and learn how to secure, maintain, and administer your new platform.

By the end of this course, you will be able to scale from gigabytes to petabytes on this high-performance, column-oriented SQL engine.

This course will help you understand the need for data warehousing—how data warehousing differs from an application database, with practical examples of each. You will learn to drive different architectural styles and choices via an example that shows how one approach doesn’t solve both problems. Our author will help you tackle challenges head-on, and applies-cutting edge techniques to accelerate the development of data warehouses on the cloud with practical examples showing how query performance is dramatically accelerated.

What You Will Learn

  • Understand data warehousing principles and how Redshift is challenging the traditional way of thinking
  • See how Redshift integrates with the AWS Cloud ecosystem
  • Learn how Redshift leverages the latest technology to provide up to 10x the performance of competing technologies
  • Create a cloud native, fully managed data warehouse and use it to join together disparate data sets
  • Connect your new data warehouse with disjointed data stored on Amazon S3 with Redshift Spectrum
  • Visualise your newly connected data sets with Amazon Quicksight
  • Dive headfirst into building a Redshift data warehouse using a diversified data set
  • Connect to and optimize your data warehouse and join data sets together
  • Connect data in your data warehouse with data on Amazon S3 with Redshift spectrum
Table of Contents

01 The Course Overview
02 Do We Still Need a Data Warehouse
03 Data Technologies Compared – Relational, Data Warehouse, NoSQL, and Big Data
04 Providing Business Intelligence on Internet-Scale Data
05 Cloud-Native Data Warehousing
06 Launching a Redshift Data Warehouse on AWS
07 Launching a Redshift Data Warehouse Using Cloudformation
08 Redshift Technology Deep Dive – Columnar Filesystem
09 Redshift Technology Deep Dive – Massively Parallel Processing
10 Sourcing Appropriate Data Sets
11 Ingesting Various Sizes of Data Set into Redshift
12 Connecting to and Querying the Data Warehouse
13 Redshift Technology Deep Dive – Query Caching
14 Ingesting Enormous Volumes of Data by Copying Directly from S3
15 Optimizing Redshift Data Types for Query Performance at Scale
16 Evenly Distributing Data Across Your Cluster to Improve Filters and Joins
17 Exploratory Analytics for Disconnected Data
18 Loading a Disconnected Dataset
19 Glue Data Catalog – Creating a Schema for the External Dataset
20 The BI Use Case for Data Warehousing
21 Introducing Amazon Quicksight
22 What Is Spice and How Can It Be Used to Accelerate Analysis
23 Loading Data into SPICE