This week’s curator, Sam Thomas, looks at some of the DOs and DON’Ts of Big Data analytics, especially as it pertains to enterprise social networks; he also picks 5 links for further reading on the topic.

How do we traverse the minefield of Enterprise Social Network data?

Do you want meaningful insights from your enterprise social network data? Tread carefully!

Look at data too broadly – without initial direction, purpose or hypotheses – and you’ll rarely find insights that connect to your strategic objectives (and therefore add business value). Look too narrowly and you’ll only confirm your preconceived ideas. After all, who doesn’t love being right? If we see one instance of data that confirms our beliefs, then our brains are programmed to ignore any data that disagrees. And we rarely recognise spurious correlations unless they are truly absurd. (Total US crude oil imports correlate with the total per capita consumption of chicken. Who knew?)

Enterprise social network packages come with an abundance of accessible metrics. Many help us gauge levels of collaboration or strengths of networks within our organisation. However, unless you know how your associates really engage with the platform, this data will be riddled with red herrings and false conclusions.

You must build an understanding of the intent behind the data points. Then formulate a working hypothesis that you can prove – or disprove. Failing to do so means your analysis will contain unacceptable amounts of guesswork and assumption. This approach still leaves room for discovery: unexpected patterns can raise questions and spark new branches of investigation.

Weekly Linklog

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