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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

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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. In other words, #adulting. Cynical Perspectives.

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Data Science, Past & Future

Domino Data Lab

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Then we roll out a decade later.

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11 Digital Marketing “Crimes Against Humanity”

Occam's Razor

When a majority of your budget is invested in tools and data warehouses, rather than smart people to use them, you are saying you prefer to suck. Your website was created in 1996, updated slightly in 2001, and left to rot ever since. You will almost die of happiness when the results come in.

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