Duration: 2.5 hours | Video: h264 1920×1080 | Audio: AAC 44kHz 2Ch | 633 MBGenre: eLearning | Language: English | 20 LessonsA practical introduction to designing, creating, and analyzing tables on Amazon Redshift, AWS’s data warehousing solution.

For decades, traditional data warehousing has been integral to business intelligence.

But now, we have a new service category in this space: the cloud data warehouse.

Cloud data warehouses like Amazon Redshift let you implement data warehousing solutions quickly, at scale, and at a lower cost than traditional data warehousing solutions … all with significant gains in performance.

In this introductory course, you’ll learn the ins-and-outs of designing, creating, and analyzing tables on Amazon Redshift.

Redshift makes it fast, simple, and cost-effective to analyze your data using standard SQL and your existing Business Intelligence tools.

And in this age of Big Data, it’s no wonder that Amazon Redshift is one of AWS’ fastest-growing services.

Best of all, Redshift is “self-service.

” It’s fully-managed by AWS, so you’ll never need to procure expensive hardware or worry about lengthy hardware deployment cycles.

And disk management, hardware updates, and software patches are handled for you, freeing you to concentrate on finding and analyzing the data that matters to you.

This self-service, “pay-as-you-go and grow” model helps companies avoid large capital expenditures and allows them to deploy data warehouses at much lower risk and cost.

And Redshift scales almost infinitely: as your data grows, so can your Redshift data warehouse.

Redshift is an extremely powerful service.

But, to take full advantage of everything it has to offer, effective table design is a must.

And this introductory course will show you how that’s done.

In this course, you will learn:The basics of creating and launching a Redshift clusterBest practices for table designHow to improve query performanceHow to perform analysis to determine if your queries are affected by poor table designNo SQL or coding experience is required.

SQL queries and shell scripts are provided.