Over the last half decade, Big Data has shaken up business practices and the workplace. The vast amount of data that companies compile from their customers allows them – in theory – to provide a more responsive and more specific service, as well as enabling them to construct better informed marketing strategies and long-term business plans.
In addition to collecting data on customers, HR teams are increasingly using data analytics when recruiting employees. Findings such as – according to CNBC reports – the best predictor that people will stay in their jobs is whether or not they have friends amongst their colleagues, and, felons perform better in call centers than those with a clean record, are now shaping strategies in the recruitment process.
However when conclusions are being made by those without the necessary training, false assumptions and dodgy conclusions can easily be made.
This had led to the demand for data analysts (sometimes referred to as ‘data scientists’) to rapidly increase. As almost every company with an online presence is continuously amassing data, the imbalance between demand and supply in regard to the ability to read this data – spotting patterns, making insights – is huge.
Subsequently, the money that the few data analysts can ask for is very high – CNBC reporting it as up to $125 000 for those straight out of college. Those who have a passing knowledge of data analytics – which is more than most of us can lay claim to – are subsequently attempting to cash in on this surge in demand; separating the wheat from the chaff is proving a challenge in itself. With top colleges in the US and Europe only lately beginning to offer courses in data analytics and business intelligence, it is likely to be a long wait until there are enough qualified individuals able to sort the truck loads of data conglomerated by businesses each day.
This has led to companies, such as Berlin-based startup datapine, stepping in to fill the gaping hole in the market. Though software offering SQL (Structured Query Language – the language used for dealing with relational databases) editing services has been available for years, the vast majority is only operational by IT specialists and – those elusive beings – business intelligence experts. Where these nippy new startups are excelling, is in offering an SQL editor that is can be used by the average man or woman working in business; enabling them to translate vast amounts of data into readable graphs, images and dashboards in real time, cutting out the need for a middle man.
With data management back into the hands of regular employees, business managers are able to make instant and accurate conclusions from their databases. Apart from anything else, this may mean that by the time those bright young things studying Data Analytics graduate, they will no longer be able to stroll into easy employment, whatever practices the HR department are using.
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