Top Five Most Read Big Cloud Articles of 2016

Revisit your favourite Big Cloud articles of the year.


#1 The 22 Skills Of A Data Scientist


Our most viewed article of 2016 was Matt Reaney’s piece covering the primary skills of different types of Data Scientist.

My first article on “How To Become A Data Scientist” explored the basic four different types of Data Scientist – Data Business People, Data Creatives, Data Developers and Data Researchers (as per the O’Reilly study “Analysing the Analysers”). It highlighted the need for a data science team with diverse and complementary skill sets. It is clear that no one superstar can fulfil all the required roles, and it is up to us as recruiters to understand the requirements of any organisation to ensure that there aren’t any gaps in their capability.Read more…


#2 The One Language A Data Scientist Must Master


“The field is developing so dynamically that many of the industry buzzwords will not have existed until a few short years ago. Just a short list of some programming languages is enough to make most business leaders dizzy. R, C, Python, Java, Julia, Scala, Ruby …  just a few of the languages that our grandchildren might be learning at high school.” Read more…


#3 How To Become A Data Scientist


Part of the field of predictive analytics has recently been thrust into the spotlight under a new name: Big Data. As specialist recruiters in this fast developing sector, we often fulfil an educational role with our clients – helping them define role requirements and understanding what sort of candidate would fit their business. However, we always come up against the same problem. There aren’t many quality Data Scientists out there who are available…” Read more…


#4 The Impact Of Big Data Analytics In Football


“Football is a booming business. You only have to look at the latest TV deal, worth £5.14bn to see how hot it really is. Football clubs are seeing an unprecedented influx of money and are trying to ensure they stay at the top, to make sure they turn this windfall into a regular income. This has paved the way for Big Data & Analytics to play its part in aiding success on and off the field, much like its impact in other business sectors and industries.” Read more…



#5 4 Ways Big Data and Machine Learning Are Helping Conservation


“The interdisciplinary field of computational sustainability is using machine learning algorithms to analyse and extract valuable insights from sets of Big Data gathered from environmental fields. It’s not just about having large data sets or advanced pattern finding algorithms – it’s how we use them. The following projects highlight how Machine Learning and Big Data are helping conservation efforts of all kinds.” Read more…


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