Remove Data Collection Remove Risk Remove Uncertainty Remove Visualization
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How to Ensure Single Source of Truth Reporting for PeopleSoft

Jet Global

Members of the finance or IT teams have to go hunting through multiple data sources, identifying and integrating the metrics they need to build reports. Since so much of the process is manual, there’s a high risk of human error. Automated Data Collection. Here’s how. Download Now. How accessible?

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Real-Time Insights Help Eliminate Common Financial Reporting Issues

Jet Global

Much of the financial reporting process, including data collection, integration, analysis, and visualization, can now run on autopilot. Contending with Data Errors. Any reporting process that relies on users manually manipulating data is at risk of typos and other human errors compromising that data.

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Pluck the Low-Hanging Fruit

Darkhorse

Add to these all of the decisions that they could be making (but aren’t) because of uncertainty or laziness. We’ll do so by eliminating those with high risk in data inputs, research, and implementation. Remind them that your solutions won’t tell them what to do, but will simply reduce uncertainty. That’s a good thing.

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Data Science, Past & Future

Domino Data Lab

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. How could that make sense?

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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.

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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. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity!