Build scalable, serverless data warehouses with machine learning and massively parallel processing in the cloud with Amazon Redshift
About This Video
Kick traditional data warehouse technologies into touch with a combination of cloud hosting and cutting-edge optimization algorithms
Go from data warehouse fundamentals to a fully functioning peta-scale data warehouse in just 3 hours, and learn everything you need to build your own …
Hands-On Amazon Redshift for Data Warehousing
Video description
Build scalable, serverless data warehouses with machine learning and massively parallel processing in the cloud with Amazon Redshift
About This Video
Kick traditional data warehouse technologies into touch with a combination of cloud hosting and cutting-edge optimization algorithms
Go from data warehouse fundamentals to a fully functioning peta-scale data warehouse in just 3 hours, and learn everything you need to build your own cloud data warehouse
Learn the do's and don'ts of data warehousing with this simple hands-on guide to building data warehouses on AWS
In Detail
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.
Audience
If you are a data analyst, data scientist, or AWS professional and are looking for a data warehouse solution using AWS services, then this course is for you! It is also suitable for professionals using DynamoDB, RDS, or any other AWS Database services. Familiarity with AWS is assumed.
Data Technologies Compared: Relational, Data Warehouse, NoSQL, and Big Data
Providing Business Intelligence on Internet-Scale Data
Cloud-Native Data Warehousing
Chapter 2 : Getting Started with Redshift
Launching a Redshift Data Warehouse on AWS
Launching a Redshift Data Warehouse Using Cloudformation
Redshift Technology Deep Dive: Columnar Filesystem
Redshift Technology Deep Dive: Massively Parallel Processing
Chapter 3 : Creating a Redshift Data Warehouse from Disparate Datasets
Sourcing Appropriate Data Sets
Ingesting Various Sizes of Data Set into Redshift
Connecting to and Querying the Data Warehouse
Redshift Technology Deep Dive: Query Caching
Chapter 4 : Optimizing Redshift for Scale
Ingesting Enormous Volumes of Data by Copying Directly from S3
Optimizing Redshift Data Types for Query Performance at Scale
Evenly Distributing Data Across Your Cluster to Improve Filters and Joins
Chapter 5 : Connecting Redshift with Disconnected Data Using Redshift Spectrum
Exploratory Analytics for Disconnected Data
Loading a Disconnected Dataset
Glue Data Catalog - Creating a Schema for the External Dataset
Chapter 6 : Visualizing Your Results with Amazon QuickSight
The BI Use Case for Data Warehousing
Introducing Amazon Quicksight
What Is Spice and How Can It Be Used to Accelerate Analysis?
Loading Data into SPICE
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