Remove Data Analytics Remove Data Collection Remove Data Processing Remove Metadata
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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

If you occasionally run business stands in fairs, congresses and exhibitions, business stands designers can incorporate business intelligence to aid in better business and client data collection. Business intelligence tools can include data warehousing, data visualizations, dashboards, and reporting.

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Preprocess and fine-tune LLMs quickly and cost-effectively using Amazon EMR Serverless and Amazon SageMaker

AWS Big Data

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run. You’re now ready to query the tables using Athena.

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Themes and Conferences per Pacoid, Episode 13

Domino Data Lab

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. You might have millions of short videos , with user ratings and limited metadata about the creators or content. If you can’t walk, you’re unlikely to run.

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Summing Up Three Days at Gartner’s Data and Analytics Conference in Orlando, Florida, USA

Andrew White

A workshop that helps diagnostically map specific data to specific business outcomes. I hosted 25 1-1s in between the meetings and presentations. Data mesh versus data fabric I am not the expert here but in lay terms, I believe both fabric and mesh include a semantic inference engine that consumes active metadata.