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Now that you’re sold on the power of data analytics in addition to data-driven BI, it’s time to take your journey a step further by exploring how to effectively communicate vital metrics and insights in a concise, inspiring, and accessible format through the power of visualization. Datavisualization: What You Need To Know.
Alberto Cairo, datavisualization expert and author of How Charts Lie Whether you are reading a social post, news article or business report, it’s important to know and evaluate the source of the data and charts that you view. Two line graphs showing the same data with different intervals on the axis. Know the Source.
Some more examples of AI applications can be found in various domains: in 2020 we will experience more AI in combination with big data in healthcare. For example, in October 2016 Wells Fargo and The Commonwealth Bank of Australia made history by using blockchain to facilitate paying for a shipment of cotton from the U.S.
Now that we’ve put the misuse of statistics in context, let’s look at various digital age examples of statistics that are misleading across five distinct, but related, spectrums: media and politics, news, advertising, science, and healthcare. 2) Examples of misleading statistics in healthcare. 4) Misleading datavisualization.
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