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I like Big Data and I can not lie!

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I like Big Data and I can not lie!
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56
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188
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CC Attribution - ShareAlike 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this
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Data analysis can be fun – and horrible all at the same time. So here's a perspective from a network researcher, sociologist and former business analyst on how to improve our daily approach to data. What traps can be avoided? How do we know when we're biased? Is there such a thing as "good"/"bad" data? Let's talk, discuss and maybe change our approach. The talk will cover some foundations: what's a bias – and how do our biases get reflected in our data collection, analysis and interpretation? The way we tackle our own biases with regards – but not limited – to gender, race, social origin, abilities, nationality and other factors shapes not only the quality of data collected, but also directly the outcome of data analysis and interpretation!