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The DataOps Vendor Landscape, 2021

DataKitchen

A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. Comet.ML — Allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility.

Testing 300
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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). Media-Mix Modeling/Experimentation. Mobile content consumption, behavior along key metrics (time, bounces etc.) And again, a custom set of metrics.

Metrics 141
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How to use experiments to find your way to success

Aryng

“To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.”

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Generative AI copilots: What’s hype and where to drive results

CIO Business Intelligence

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. As copilot technology capabilities are changing rapidly, leaders should frequently identify metrics and evaluate strategies.

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Large Pharma Achieves 5X Productivity Gain With DataOps Process Hub

DataKitchen

The business analysts creating analytics use the process hub to calculate metrics, segment/filter lists, perform predictive modeling, “what if” analysis and other experimentation. It also minimizes the need for outside consultants who tend to rely upon heroism and tribal knowledge. Requirements continually change.

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AI Product Management After Deployment

O'Reilly on Data

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

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7 secrets of successful digital transformations

CIO Business Intelligence

While it’s critical for tech leaders to communicate throughout a digital project, it’s also important to communicate appropriately, says Rich Nanda, US strategy and analytics offerings leader, at Deloitte Consulting. Rich Nanda, US strategy and analytics offerings leader, Deloitte Consulting. Deloitte Consulting. “In