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NHL turns to venue metrics data to drive sustainability

CIO Business Intelligence

To reduce its carbon footprint and mitigate climate change, the National Hockey League (NHL) has turned to data and analytics to gauge the sustainability performance of the arenas where its teams play. Mitchell says the league is thinking of NHL Venue Metrics in the same way. “We

Metrics 144
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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

Data analysis and interpretation have now taken center stage with the advent of the digital age… and the sheer amount of data can be frightening. In fact, a Digital Universe study found that the total data supply in 2012 was 2.8 Data analysis and interpretation, in the end, help improve processes and identify problems.

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Data Science, Past & Future

Domino Data Lab

Coming into the 2010s, we had data science practice, we had evolution of big data tooling, we had a lot more sophisticated use of the big data and what was going on in the cloud. I went to a meeting at Starbucks with the founder of Alation right before they launched in 2012, drawing on the proverbial back-of-the-napkin.

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Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees. We had big surprises at several turns and have subsequently published a series of reports. Let’s look through some of the insights gained from those reports. Who builds their models?

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Mobile Marketing 2015: Rethink Customer Acquisition, Intent Targeting

Occam's Razor

To fit surfing into my three concurrent jobs, two small kids, and one magnificent spouse lifestyle I need a surf reports app that will give me precise information about the waves. Snow, skate, surf and motox reports are perfectly targeted to the potential audience's tastes. Let me give you an example. Closing Thoughts.

Marketing 144
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Unintentional data

The Unofficial Google Data Science Blog

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation. And for good reason!