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Build a domain‐aware data preprocessing pipeline: A multi‐agent collaboration approach

Flipboard

The end-to-end workflow features a supervisor agent at the center, classification and conversion agents branching off, a humanintheloop step, and Amazon Simple Storage Service (Amazon S3) as the final unstructured data lake destination. Make sure that every incoming data eventually lands, along with its metadata, in the S3 data lake.

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2024 Governance Trends for Data Leaders

phData

This blog is a collection of those insights, but for the full trendbook, we recommend downloading the PDF. With that, let’s get into the governance trends for data leaders! Just click this button and fill out the form to download it. Chief Information Officer, Legal Industry For all the quotes, download the Trendbook today!

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning Blog

We work backward from the customers business objectives, so I download an annual report from the customer website, upload it in Field Advisor, ask about the key business and tech objectives, and get a lot of valuable insights. I then use Field Advisor to brainstorm ideas on how to best position AWS services.

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Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

AWS Machine Learning Blog

In the following sections, we demonstrate how to import and prepare the data, optionally export the data, create a model, and run inference, all in SageMaker Canvas. Download the dataset from Kaggle and upload it to an Amazon Simple Storage Service (Amazon S3) bucket. Explore the future of no-code ML with SageMaker Canvas today.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

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What Is a Data Catalog?

Alation

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

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Mainframe Data: Empowering Democratized Cloud Analytics

Precisely

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions. Secure data exchange takes on much greater importance.