Big Data Trends Briefing

Big Data Trends Briefing: Key Takeaways from Econsultancy’s Digital Cream 2013 from TagMan:

http://eu.tagman.com/big-data-trends-briefing/

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Business intelligence meets web analytics

A best practice guide from Econsultancy:

http://econsultancy.com/uk/blog/62801-business-intelligence-meets-web-analytics

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Data scientist, or analytics expert?

There’s been a lot of hoo-ha about ‘data science’ and ‘big data’ recently. There is no need for these neologisms; especially as the former isn’t a science (except in the jocular sense) and the second begs the question, what is a ‘big datum’ ?

The following article on Econsultancy was brought to my attention by the MBN Recruitment February 2013 newsletter:

What is a data scientist and do you need one?
Posted 05 December 2012 15:04pm by Patricio Robles

http://econsultancy.com/uk/blog/11262-what-is-a-data-scientist-and-do-you-need-one

It is argued therein that ‘data scientists’—in contrast to ‘analytics experts’—‘[m]ay be involved in the design and development of systems that collect and process large amounts of data’. Whereas back in 2004–05, whilst employed as a ‘marketing analyst’ and subsequently as a ‘senior business analyst’ I worked on a project in which I was involved in the collection, and undertook the processing, of two data streams: one with tens of thousands of records weekly, the other with over 10 million records weekly.

Secondly, that ‘data scientists … [n]eed to have a deep understanding of statistics and probability’. This was a requirement of my first ever role after leaving academia, that of ‘quantitative analyst’—my line manager in that case having previously been a lecturer in statistics—, and of other roles since, and has been something I have looked for in candidates when recruiting.

Thirdly, ‘data scientists … [a]re capable of designing and testing predictive models’; as if that hasn’t been a requirement of every role I’ve held with ‘analyst’ in the title, and of countless similarly titled roles in all areas of industry, commerce, and research.

The fourth and fifth points made in the article capture some of the changes in what is expected of an analyst, but the situation is nowhere near as clear cut as implied. It is claimed that ‘data scientists … [p]rovide the greatest value by answering the questions “Where are we likely going?” and “What would we need to do to go somewhere else?”’ and that they ‘[w]ill realistically need to acquire a high level of domain expertise’, in contrast to ‘analytics experts’, who ‘[a]re best capable of answering the questions “Where have we been?” and “Where are we today?”’ and ‘[s]hould have some domain expertise’.

Unless one intends to employ an ‘analytics expert’ and a ‘data scientist’, whoever fills the role will need to answer the second pair of questions before she/he can answer the first pair of questions; and in doing so will require domain expertise, the level of which will be contingent on the duration of the project, whether this is a short-term contract or a permanent position, the overlap between the domain in question and the core business, etc. The role title ‘insight analyst’ perhaps emphasizes the last two points, but one would expect such capabilities in a ‘senior marketing analyst’, ‘customer strategy and insight analyst’, and a host of other job titles I and thousands of other ‘analytics experts’ have held over the last ten-or-so years.

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