BUSINESS STRATEGY
science is a fairly broad term , owing to the nature of data science as an inter-disciplinary field – drawing on a mix of hard mathematical , scientific skills and softer business skills .
For this reason , rather than pointing at an example of data literacy , it ’ s often easier to spot the absence of certain data skills and work backwards from there . For data scientists and analysts , this process is happening organically . As they increasingly collaborate with business leaders , stakeholders and less-technical colleagues , they discover the areas where a little more knowledge would go a long way in easing communication .
Much of the time , what is missing is not hard technical know-how . Rather , it is more generalised data-driven problem-solving skills that constitute ‘ data science literacy ’. At the most basic level , this can be manifested simply by asking the right questions – understanding which available datasets and variables are relevant to the task at hand .
THE FIRST STAGE IN ENCOURAGING DATA LITERACY CAN SIMPLY BE TO RAISE AWARENESS OF ITS IMPACT .
This diagnostic ability to identify data is the first step in becoming data science literate . The next step is interpretation . Once the relevant data is identified , it must be interpreted – the meaningful needs to be separated from the meaningless and useful insights need to be highlighted . The third and final component of data science literacy is the ability to communicate effectively using data . This aspect is the most vital for businesses . If those working within the growing data function of companies are going to talk coherently with the other functions , the employees across the company need to understand what is being said . to learn from . The first stage in encouraging data literacy can simply be to raise awareness of its impact – share use-cases with employees , examples of how data has informed company strategies or driven powerful decision making .
Raising awareness is one thing , however a company that wants to get serious about creating a data literate culture should consider incorporating at least some basic training – setting a minimum level of competence from the C-suite down . It ’ s a worthy investment as it allows you to future-proof both your employees and your business . The tide of Digital Transformation is irresistible and it ’ s important not to get left behind .
This training could take the form of an in-house platform , for example , a library of open-source learning materials for employees to access , perhaps with an incentive to do so . This kind of broad , long-term solution is well-suited to large companies with many employees , but a smaller company may want something more bespoke . For smaller companies , the most accessible way to boost data science literacy could be to schedule a few immersive training days . In as little as four days , it ’ s possible to acquire all the necessary skills to be considered literate with data science . If
For our purposes then , we might define data science literacy in business as : ‘ A functional proficiency in the identification , interpretation and communication of meaningful data and datasets ’.
How is data science literacy created and encouraged ?
Data is everywhere . ‘ Data is the new oil ’, as first pointed out by mathematician , entrepreneur and , among other things , inventor of the Tesco Clubcard , Clive Humby . For businesses looking to boost their data science literacy , this means that there ’ s no shortage of examples for employees
26 www . intelligentcxo . com