Monthly Archives: February 2014

ProSIS – pro-social information systems

All too often big data and data science can look like solutions searching for a problem. By starting with problems and issues we can think about what is important (and why) and then ask how ICT, big data, and data … Continue reading

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Doing Data Science

I’ve been reading an excellent book by Cathy O’Neil and Rachel Schutt. “Doing Data Science: straight talk from the frontline” (O’Reilly, 2013). The book contains many practical examples of data science, in many instances accompanied by R code. The technical … Continue reading

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Data determinism – can data really speak for itself?

It’s tempting to think that data can somehow speak for itself, that we can abandon theory because (as Anderson said in 2008): There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking … Continue reading

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Time for a Data Science MSc?

To help meet the demand for data scientists I am thinking about a Masters programme. One essential question is what to call the program – Business Analytics? Predictive Analytics? Big data? Business Intelligence? I want to avoid being a fashion … Continue reading

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Data scientists

According to Thomas Davenport, being a data scientist is the Sexiest Job of the 21st Century. ┬áThe Economist says that data scientists are the New Rock Stars, that they will be in short supply – McKinsey is already forecasting the … Continue reading

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