Data Sharing and Machine Learning using Amazon Redshift - AWS Analytics in 15

Data that you need for insights is not just growing in volume, but also getting more diverse (log data, click stream, voice, video). It often sits in various data silos, even third party organizations. Amazon Redshift provides deep integration into the AWS data ecosystem, across data lakes and purpose built data stores, third party data warehouses, and delivers on data sharing capabilities to share transitionally consistent data securely across regions, organizations, and data providers. Conduct Machine learning on this data for predictive insights right within your data warehouse, in familiar SQL, and cut down time to real time and predictive insights.

Learning Objectives:
* Objective 1: Learn about Redshift's data sharing and machine learning capabilities and become an expert in these use cases.
* Objective 2: Get an understanding of how Amazon Redshift helps you break through data silos and enable data sharing across regions and accounts.
* Objective 3: Understand how the Amazon Redshift integration with AWS Data Exchange and Amazon SageMaker brings together predictive insights through SQL based machine learning models, working on shared data.

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