By Jordan Morrow, Global Head of Data Literacy, Qlik
Adapted from his presentation at the Southern Africa Qlik Summit 2018
“Data literacy” is a term we’ve heard many times – and one we will definitely hear more and more in the future. We’re living in a world of data, and in the last two years we’ve amassed more data than in the history of the world. Yet, as more money means more problems, so more data can mean more problems.
To overcome these issues, we need to consume data properly. This is what data literacy is all about. If you don’t have data literacy you are going to hit road blocks in the digital transformation journey.
Why Data Literacy?
There are not enough people in this world to house the data scientist jobs needed. Just two years ago, this wasn’t a term that mattered. While not everyone needs to be a data scientist, data literacy is the in-between link – absolutely everyone needs to be data literate. Data literacy is the key to succeeding in this world.
According to a Qlik survey of over 7000 respondents, the following people are data literate:
- 24% of business decision makers (this means three in four managers are not data literate)
- 32% of C-level executives
- 21% of 16 to 24-year-olds
There’s a big difference between knowing what to do with technology and being data literate.
- Over 90% of those saying they were data literate were performing very well in their jobs
- 75% of them wanted to take training/would be interested in training for data literacy
Data Related Skills Gaps
We are producing data at rates that are completely unfathomable. Massive skills gaps are created due to:
- Data production – we are producing data in so many different ways. The collection of data from various sources is rapidly increasing (even drawing data from our smart fridges). Most people don’t go to school to do stats or quantitative analysis. Most people don’t have the skills to analyse all of this data that is being produced. It is essential that we build the skills needed to get insights from, and make actionable decisions on, this data.
- The Democratisation of Data (self-service) – we’re putting data the hands of so many people, but can they analyse it? Now they have the tools, but do they have the skills? They can build a chart, but they don’ know why they are using the chart. Analysis skills and self-service need to be married and coupled with data literacy – which must be part of business intelligence decisions.
- Digital Transformation – everything is becoming digitised in the world – watches, phones, etc. We need the skills to manage this digitised world effectively.
In 2018, the human element has caught up to technology. This reveals the actual data literacy skills gaps. Once you know your comfort level with data literacy (or lack thereof) then you can move forward.