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A Guide to Building Better Data Products

Juice Analytics

There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable. Predictive models to take descriptive data and attempt to tell the future. Bake your knowledge of the problem and the data into a problem-solving application. Reporting — To track usage of the data product.

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DNV Illuminates the Utilities Industry with Insights and Data

Sisense

This process necessitated us getting a handle on the data we were already collecting, making sense of the constant stream of new information our clients were pulling in, and presenting it all in an easy-to-understand interface. The right data, the right platform, the right partner.

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How to Display Your Data So Everyone Understands

TIBCO

White House for her contributions to education, illustrates the importance of clearly displaying your data with a couple of examples: John Snow’s (not the Game of Thrones character, but an English physician) work on the great cholera outbreak of 1854, and the Challenger space shuttle. Over the counter medicine is high stakes as well.

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Top Data Analytics Terms You Should Know

The BAWorld

Top Data Analytics terms are explained in this article. Learn these to develop competency in Business Analytics. Data Analytics Terms & Fundamentals. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms. Also, see data visualization.

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Data Analytics Projects Life Cycle

The BAWorld

How are the Data Analytics projects executed? In this article, I am going to discuss and explain Data Analytics Projects Life Cycle. Over the last two years alone, 90 percent of the data in the world was generated! Looking at the sheer volume of data generated every minute across the globe can be mind-boggling.

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How can we do no harm with data? A conversation with the authors of the Do No Harm Guide

Tableau

Applying a DEI lens to how we analyze, visualize, and communicate data requires empathizing with both the communities whose data we are visualizing as well as the readers and target audiences for our work. Jonathan became interested in data viz in 2012 while working as an economist at the Congressional Budget Office.

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How can we do no harm with data? A conversation with the authors of the Do No Harm Guide

Tableau

Applying a DEI lens to how we analyze, visualize, and communicate data requires empathizing with both the communities whose data we are visualizing as well as the readers and target audiences for our work. Jonathan became interested in data viz in 2012 while working as an economist at the Congressional Budget Office.