Poor data ‘biggest hurdle’ for analytics pros

Poor quality and unorganised data has been identified as the biggest day-to-day challenge for IT experts working with large amounts of information – though despite this, the vast majority are satisfied with their jobs.

This is according to research conducted by CloudFlower, which found two-thirds of data scientists stated cleaning and organising information is their most time-consuming task. 52.3 per cent of professionals added poor quality of data is their biggest daily obstacle.

Another issue to come out of the survey was a struggle with limited resources. Four out of five of respondents agreed there are not enough data scientists working in the field, which may leave them trying to manage more work than they can handle.

What’s more, 40 per cent of professionals cited limited analysis time as a problem, while 30 per cent highlighted limited technology tools and limited ability to model data. Some 54.3 per cent of data scientists said that providing additional resources was on their list of steps their organisations should be taking to better empower their big data teams.

Setting clearer goals was another key wish for these professionals, with 52.3 per cent rating this as a priority. This was followed by investing more in training (47.7 per cent), setting more realistic timelines for projects (41.2 per cent) and hiring more data scientists (23.5 per cent).

However, overall satisfaction with their roles remained high, some 79.1 per cent of professionals saying there are happy in their jobs. When it comes to specific tasks, 56.3 per cent said they are happiest when performing predictive analytics operations, while 52.3 per cent derive satisfaction from mining data for patterns and 49.7 per cent highlighted interacting with data dynamically.