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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The company has been on a continuous journey to adapt its internal and external processes to new business needs and opportunities since 2001.” Following this, in 2002, it began delivering its knowledge to customers in online format, using dashboards and interactive reports that provided easier and faster access to data and analysis.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. Welcome back to our monthly burst of themes and conferences.

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Data Science, Past & Future

Domino Data Lab

Greg Linden ‘s article about splitting the website on Amazon. We have an article on this on Domino. I can point to the year 2001. It was also the year, 2001, when “ Agile Manifesto ” was published. By that point, they had all reached the same conclusion. We’ve just done three. All righty.

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

In terms of teaching and learning data science, Project Jupyter is probably the biggest news over the past decade – even though Jupyter’s origins go back to 2001! See the 2013 article in Nature , “ MOOCs taken by educated few, ” and also some extended discussion at an ACM meetup on the topic. NASA persistently misspells Jupyter.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. If you’ve never participated in a Foo event, check out this article by Scott Berkun. Introduction. In mid-July I got to attend Sci Foo , held at Google X.

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Data Science at The New York Times

Domino Data Lab

In 2001, Bill Cleveland writes this article saying, “You are doing it wrong.” This was one of several such articles, but that’s another talk. Then we can drill down and say what are the individual articles that over-index for that group or for that topic. That is an example of a descriptive tool. .”