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How does Tableau power Salesforce Genie Customer Data Cloud?

Tableau

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98
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How does Tableau power Salesforce Genie Customer Data Cloud?

Tableau

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98
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From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

Many organizations store their data in structured formats within data warehouses and data lakes. Amazon Bedrock Knowledge Bases offers a feature that lets you connect your RAG workflow to structured data stores. In her free time, she likes to go for long runs along the beach.

AWS 92
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What is Salesforce Data Cloud for Tableau?

Tableau

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Salesforce Data Cloud for Tableau solves those challenges.

Tableau 55
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How Q4 Inc. used Amazon Bedrock, RAG, and SQLDatabaseChain to address numerical and structured dataset challenges building their Q&A chatbot

Flipboard

The dataset Our structured dataset can reside in a SQL database, data lake, or data warehouse as long as we have support for SQL. She speaks in internal and external conferences such re:Invent, Women in Manufacturing West, YouTube webinars and GHC 23. In her free time, she likes to go for long runs along the beach.

SQL 166
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Join the Alation MLDC World Tour!

Alation

“Enterprises are… turning to data catalogs to democratize access to data, enable tribal data knowledge to curate information, apply data policies, and activate all data for business value quickly.”. In a recent webinar,“ Ready for a Machine Learning Data Catalog?

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Your Complete Roadmap to Become an Azure Data Scientist

Pickl AI

Storage Solutions: Secure and scalable storage options like Azure Blob Storage and Azure Data Lake Storage. Key features and benefits of Azure for Data Science include: Scalability: Easily scale resources up or down based on demand, ideal for handling large datasets and complex computations.

Azure 52