Remove Data Collection Remove Data-driven Remove Measurement Remove Uncertainty
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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. Data architecture coherence. Putting data in the hands of the people that need it.

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What you need to know about product management for AI

O'Reilly on Data

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Machine learning adds uncertainty.

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Human-centered design and data-driven insights elevate precision in government IT modernization

IBM Big Data Hub

Government executives face several uncertainties as they embark on their journeys of modernization. What makes or breaks the success of a modernization is our willingness to develop a detailed, data-driven understanding of the unique needs of those that we aim to benefit.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.

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Product Management for AI

Domino Data Lab

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. A few highlights from the session include.

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Viral, Social, Sentiment, Mobile: 4 Delightful Web Analytics Solutions

Occam's Razor

I want to constantly be in the know of new and more clever ways of working with data, tools that are often solutions to problems we don't know we have yet or tools that are sometimes seeking problems to solve!! Well not crap… lots of data that no one cared about or actioned. More desire to be data driven.

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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist.