I'm looking for a whimsical large data set. Something bizarrely specific, or just an area you'd never guess there was that much to measure. For example, the amount of materials used by the Teddy Bear industry or the shifting volume of animal feces at major zoos. I've been searching through the many big data set sites to no avail. The ideal set would contain around a million nodes and, if relational, a few hundred thousand connections. A factor of ten either way would be reasonable though.
I'm an experienced software engineer and manager. I have a number of successful projects under my belt and some really great companies on my resume. However, I'm really, really bad at the traditional whiteboard interview. I'm getting ready to start looking for a new job. Would it be worthwhile to request an alternative interview format? [more inside]
I'm curious to learn what major scientific (or other) advances have been made using data mining of extremely large datasets (a.k.a. "big data")? [more inside]
Looking for extra practice exams for the CCA-505 exam and finding a bunch of sites that make guarantees but don't look very credible. [more inside]
So, "big data" is all the rage among technologists and venture capitalists. Intuition suggests that as the amount of data analyzed increases, so too does the amount of spurious correlations. Have there been any good studies (academic or otherwise) that try to resolve this problem? Or feel free to tell me why my intuition is wrong. Thanks.
I've long suspected that the professional networking site LinkedIn may be using information such as my mobile phone records to make recommendations for connections. But today they really freaked me out. What gives? [more inside]
Can you point me to the best resources to learn about these new-fangled things they call data science and big data? I just started a new job as a data scientist and need to get up to speed. [more inside]
What examples are out there on the web of interactive charts with thousands of data points that can be scrolled through smoothly with little interruption or skipping? [more inside]