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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.” And all this by relying on a talented team of IT professionals, data scientists, analysts, researchers and consultants working together to deliver the best results for the company and its clients.

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IT leaders turn to HBCUs for future IT talent

CIO Business Intelligence

They point to statistics that highlight challenges in IT workforce recruitment and diversity. White, a 2001 Morgan State University graduate with a bachelor’s in computer science, speaks from experience: He had two pivotal internships that propelled his professional career. There’s nothing like gametime experience,” he adds.

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Self-Service BI vs Traditional BI: What’s Next?

Alation

As Business Objects founder Bernard Liautaud notes in e-Business Intelligence: Turning Information Into Knowledge Into Profit (McGraw-Hill, 2001), the lack of ad hoc data access causes IT staff to drown in requests. Slow requirements led technology leaders to demand proactive business intelligence.

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Data Science, Past & Future

Domino Data Lab

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. The ones that don’t fare well tend to rely on external consultants. I can point to the year 2001. Tukey did this paper.

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

For example, an exec from a large, well-known consulting firm explained to me how they rarely send staff to in-person courses. 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! NASA persistently misspells Jupyter.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Consider the following timeline: 2001 – Physics grad students are getting hired in quantity by hedge funds to work on Wall St. Putting discussions about security aside, the statistics competency required to confront fairness and bias issues for machine learning models in production set quite a high bar. machine learning?

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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.” We consult with the journalists, we try to be useful when we can be helpful but those people have deadlines, and I’m already submitting papers to NeurIPS and other stuff. Bell Labs basically was the “data science” of the day.