Research conducted by US analytics automation firm Alteryx highlights that businesses in the GCC are being hindered by inconsistently applied training programmes when it comes to working with data.

Despite potential for innovation, the region's success will be hampered by the growing risk of data literacy gaps and a 'data ethics' disaster.

In a survey comissioned by Alteryx and conducted by UK-based market research firm YouGov, nearly 97 per cent of respondents said that training needs to be made available to all data workers in the region to "truly unlock business value". The respondents surveyed were 300+ data workers based in the UAE and Saudi Arabia. 

Only existing experts, such as qualified data scientists and business analysts, receive regular data upskilling. Employees that lack formal data training are increasingly operating in the dark – further overloading at-capacity data science teams.

With so many workers excluded from data training, the region is primed for a data ethics disaster. Workers are now gravitating towards informal mentoring (39 per cent) and informal user groups (24 per cent) to train, increasing the risk of unintentional bias creeping into algorithms and models.

Moreover, a third of MEA business leaders surveyed said that solving this challenge is someone elses problem, indicating these issues will linger for some time.

The research further highlights that data scientists spend a disproportionate amount of their time each week on tasks that could be completed by workers with less advanced skillsets using automation technology, and are stuck in a continuous loop of day-to-day tasks. Findings show that:

• 27 per cent of data scientists spend at least nine hours each week on basic data tasks such as cleansing, blending, and shaping
• 14 per cent of the data scientists surveyed spend at least 30 hours on the same tasks
• 54 per cent of these data scientists say their business is “not making full use of the data”, and 49 per cent say that employees are “lacking the lata literacy skills needed to meet today’s business challenges

"Big data needs context and human intelligence when applied to AI," says Alan Jacobson, chief data and analytic officer at Alteryx. "What we now see is an AI ethics conundrum. If not driven by data science, unintentional data biases can creep in, leading to perpetuated discriminatory practices, as well as inaccurate and inconsistent AI models.”