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Build generative AI–powered Salesforce applications with Amazon Bedrock

AWS Machine Learning Blog

In Part 1 and Part 2 , we show how Salesforce Data Cloud and Einstein Studio integration with SageMaker allows businesses to access their Salesforce data securely using SageMaker’s tools to build, train, and deploy models to endpoints hosted on SageMaker. Ravi Bhattiprolu is a Sr. Partner Solutions Architect at AWS.

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Predicting the Future of Data Science

Pickl AI

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. As we move forward, several emerging trends are shaping the future of Data Science, enhancing its capabilities and applications.

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The Modern Data Stack Explained: What The Future Holds

Alation

It began when some of the popular cloud data warehouses — such as BigQuery, Redshift , and Snowflake — started to appear in the early 2010s. Later, BI tools such as Chartio, Looker, and Tableau arrived on the data scene. Powered by cloud computing, more data professionals have access to the data, too.

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Democratize ML on Salesforce Data Cloud with no-code Amazon SageMaker Canvas

AWS Machine Learning Blog

In Part 1 and Part 2 , we show how the Salesforce Data Cloud and Einstein Studio integration with SageMaker allows businesses to access their Salesforce data securely using SageMaker and use its tools to build, train, and deploy models to endpoints hosted on SageMaker. Ravi Bhattiprolu is a Sr. Partner Solutions Architect at AWS.

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