• Mark Monfort

Databilities - the data literacy framework


As I rounded out the first week into my new job back home in Sydney, Australia I could see even more clearly that I need to do more to advocate the ways in which data analytics can positively transform businesses and their workers. My first-hand observations have shown me that whilst businesses have made some inroads into implementing better data usage, there is still a gap in the data literacy of the workforce. I mentioned this in my previous blog post ‘The first step towards better data literacy’ and it was on this topic that I was pointed towards an organisation doing great work in this space. During a conversation with Qlik software advocate Dalton Ruer (see his blog here: QLIK DORK) he mentioned the work being done by ‘Data to the People’. Their mission is all about addressing the ‘growing divide between those who have and have not’ in the world of data literacy. They see Data Literacy as crucial to success in an increasingly knowledge-based economy and one their ‘Databilities’ project does a very good job at doing that.

‘Databilities’ establishes a competency framework which measures core data literacy skills. The beset thing is that they distribute it under a Creative Commons license which makes it even easier to share and spread the word.

As you can see from this sample page, there are various levels of competency and these are measured across a variety of data skills such as data collection, manipulation, conversion, analysis etc. Measurement is the only way towards improvement and I when I took their online test (which asks you to self-assess where you believe your data skills to be) it was really quite cool to see where my own skills gap lie. Depending on the work you are required to do or the skills you want to achieve, having a framework and tests like this can be very useful to show you where to start. Even if you’re starting from the bottom, the framework gives you the guidelines as to where to start.


Typically, in data consulting engagements I’ve witnessed, there is specific training on how to achieve certain tasks and how to use specific software but we often don’t take the time to look at our employees skillsets. Having knowledge of where the skills gaps are should not be cause for concern but we should look positively at information like this as it allows us to better understand our employees and ensure they get the training they need, especially if we desire the best from them.

In any case, it’s data literacy and the skills needed to achieve it that I’ll be considering highly when I talk to my clients about their data strategies.

Over and out.

#analytics #dataliteracy #dataanalytics #frameworks

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