In this workshop, you`ll learn how SQL Server big data clusters implements machine learning, and how to select and plan for the proper architecture to enable machine learning to train your models using Python, R, Java or Scala to operationalize these models, and how to deploy your intelligent apps side-by-side with their data.

The focus of this course is to understand how to deploy an on-premise, hybrid or local environments of a big data cluster, and understanding the components of the big data solution architecture.

  • You`ll start by understanding the concepts of big data analytics and data virtualization in SQL Server 2019
  • You`ll get an overview of the technologies (such as containers, Kubernetes, Spark and HDFS, machine learning, and when to use which language) that you will use throughout the course.
  • You`ll also learn how to create external tables over other data sources to unify your data
  • and how to use Spark to run big queries over your data in HDFS or do data prep.
  • You`ll learn to extrapolate what you have learned to create other solutions on your own.

NOTE: If you want to follow along (optional) then there are a few pre-requisites for this course to ensure you have the proper environment to work with big data. Please follow the instructions here, they must be completed before arrival.


Pre-requisites

Laptop Required:Optional - Laptop pre-requisites at Buck`s Github page

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