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Visualizing COVID-19 Data Responsibly: An Interview with Amanda Makulec

Depict Data Studio

Amanda went through some of the top considerations, from data quality, to data collection, to remembering the people behind the data, to color choices. COVID-19 Data Quality Issues. It’s really hard to make these apples to apples comparisons, as easy as it might seem since the data is so accessible.”.

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The Role of Data Governance During A Pandemic

Anmut

As a result, concerns of data governance and data quality were ignored. The direct consequence of bad quality data is misinformed decision making based on inaccurate information; the quality of the solutions is driven by the quality of the data. COVID-19 exposes shortcomings in data management.

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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . And the problem is not just a matter of too many copies of data.

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. Measurement challenges Assessing reliability is essentially a process of data collection and analysis.

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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. A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process.

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Product Management for AI

Domino Data Lab

If you have a user facing product, the data that you had when you prototype the model may be very different from what you actually have in production. This really rewards companies with an experimental culture where they can take intelligent risks and they’re comfortable with those uncertainties.