Finding Nemo’s Silver Lining: Using Big Data to Analyze Big Weather

For those of you who live in a data cave on the West Coast like I do, it may come as a surprise that there was a blizzard this past weekend—a BIG one.  The ‘Nemo’ blizzard, caused by a merging of two low pressure systems that originated in the central and southeast US, then migrated to the north-eastern seaboard—affected millions of people in the US Northeast, with heavy snow and multiple power-outages.

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Monday matters: how day of week affects online shopping for four major retailers

In my last blog, I demonstrated how the noise in online sales data could be correlated (to some extent) to the weather. What I didn’t tell you was that I was saving my more interesting findings for a separate post.

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What happens with online shopping when it rains? Linking online shopping to weather and exploring drivers of noise in sales data

Countless factors affect online shopping, many of which aren’t well known, classified, or understood. Much like the climate system, online sales vary across different time periods–year, month, week, day, hour–with smaller levels of variability often dismissed as so much ‘noise’.

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