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Invoking IT to help revitalize Indigenous languages at risk of extinction

CIO Business Intelligence

Data collection on tribal languages has been undertaken for decades, but in 2012, those working at the Myaamia Center and the National Breath of Life Archival Institute for Indigenous Languages realized that technology had advanced in a way that could better move the process along.

Risk 98
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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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Global Multichannel Consumer Behaviour (Research/Purchase) Analysis

Occam's Razor

The cost of failure in the offline world is so high that even when the cost of failure is low (online), they don't want to take the smallest risk. The data was collected in the first part of 2012, between January and May for the Barometer and between January and February for the Enumeration. We don't.

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet. If unaccounted for, these data points can have an adverse impact on forecast accuracy by disrupting seasonality, holiday, or trend estimation.

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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

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.