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Build a financial research assistant using Amazon Q Business and Amazon QuickSight for generative AI–powered insights

Flipboard

According to a Gartner survey in 2024 , 58% of finance functions have adopted generative AI, marking a significant rise in adoption. Their information is split between two types of data: unstructured data (such as PDFs, HTML pages, and documents) and structured data (such as databases, data lakes, and real-time reports).

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AWS re:Invent 2024 Highlights: Top takeaways from Swami Sivasubramanian to help customers manage generative AI at scale

AWS Machine Learning Blog

We spoke with Dr. Swami Sivasubramanian, Vice President of Data and AI, shortly after AWS re:Invent 2024 to hear his impressionsand to get insights on how the latest AWS innovations help meet the real-world needs of customers as they build and scale transformative generative AI applications. Q: What made this re:Invent different?

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Query structured data from Amazon Q Business using Amazon QuickSight integration

AWS Machine Learning Blog

Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content (such as PDFs, Word documents, and HTML pages), and structured data (real-time data and reports stored in databases or data lakes).

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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

Using data versioning can make it possible to have the snapshot of the training data and experimentation results to make the implementation easier at each iteration. The above challenges can be tackled by using the following eight data version control tools. Most developers are familiar with Git for source code versioning.

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning Blog

We discuss how our sales teams are using it today, compare the benefits of Amazon Q Business as a managed service to the do-it-yourself option, review the data sources available and high-level technical design, and talk about some of our future plans.

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Building an Effective OSS Management Layer for Your Data Lake

ODSC - Open Data Science

Be sure to check out her talk, “ Don’t Go Over the Deep End: Building an Effective OSS Management Layer for Your Data Lake ,” there! Managing a data lake can often feel like being lost at sea — especially when dealing with both structured and unstructured data.

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Open Data Lakes, Safeguarding Images From AI, Free Data Viz Tools, and 50% Off ODSC East

ODSC - Open Data Science

The Future of the Single Source of Truth is an Open Data Lake Organizations that strive for high-performance data systems are increasingly turning towards the ELT (Extract, Load, Transform) model using an open data lake. To DIY you need to: host an API, build a UI, and run or rent a database. See them here!