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New AI Applications Unlock the Value of AI

DataRobot

If you’re a regular reader of the DataRobot blog, you likely fall into one of two categories. You also might be a citizen data scientist – someone who is proficient with data and analytics tools like Excel or Tableau and wants to incorporate data science into your analysis (even though you haven’t had formal training like a data scientist).

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Self-Service BI vs Traditional BI: What’s Next?

Alation

These so-called “citizen data scientists” remained a roadblock between business users and data — and between data and decision making. Business teams still had to request data. But at its core, it’s about making data discoverable, trustworthy, and shareable. Subscribe to Alation's Blog.

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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

The rise of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML) , and Big Data analytics is reshaping industries and creating new opportunities for Data Scientists. Understanding real-time data processing frameworks, such as Apache Kafka, will also enhance your ability to handle dynamic analytics.

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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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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.