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Practical Skills for The AI Product Manager

O'Reilly on Data

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.

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The Race For Data Quality in a Medallion Architecture

DataKitchen

It is a layered approach to managing and transforming data. Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning. For businesses requiring near-real-time insights, the time taken to traverse multiple layers may also introduce delays.

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Announcing Open Source DataOps Data Quality TestGen 3.0

DataKitchen

Now With Actionable, Automatic, Data Quality Dashboards Imagine a tool that can point at any dataset, learn from your data, screen for typical data quality issues, and then automatically generate and perform powerful tests, analyzing and scoring your data to pinpoint issues before they snowball. DataOps just got more intelligent.

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Drug Launch Case Study: Amazing Efficiency Using DataOps

DataKitchen

data quality tests every day to support a cast of analysts and customers. Small, manageable increments marked the projects delivery cadence. DataKitchen loaded this data and implemented data tests to ensure integrity and data quality via statistical process control (SPC) from day one.

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Generative Logic

O'Reilly on Data

That seemed like something worth testing outor at least playing around withso when I heard that it very quickly became available in Ollama and wasnt too large to run on a moderately well-equipped laptop, I downloaded QwQ and tried it out. How do you test a reasoning model? But thats hardly a valid test. So lets go!

Testing 256
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Navigating the cloud maze: A 5-phase approach to optimizing cloud strategies

CIO Business Intelligence

First, cloud provisioning through automation is better in AWS CloudFormation and Azure Azure Resource Manager compared to the other cloud providers. This involves identifying which components can be lifted and shifted directly to the cloud and which might require re-architecture for cloud optimization.

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Unlock the power of optimization in Amazon Redshift Serverless

AWS Big Data

Although traditional scaling primarily responds to query queue times, the new AI-driven scaling and optimization feature offers a more sophisticated approach by considering multiple factors including query complexity and data volume. Consider using AI-driven scaling and optimization if your current workload requires 32 to 512 base RPUs.