What is Data Science Literacy?
What is data science literacy and why is it so important?
Simply put, data science literacy is understanding what data means. This includes the ability to read graphs and charts, work with the data, analyze it, and draw conclusions from data.
We live in a data-driven world. Sometimes this data is cherry-picked, taken out of context, or misrepresented. People constantly make data-based decisions for themselves and for their companies, so understanding how to recognize whether data is good or bad is critical.
Between August 2017 and February 2018, data analytics software company Qlik conducted a study regarding data literacy with respondents from Asia, Europe, and the United States. This study showed that only 24% of business decision makers are confident in their data literacy skills. How can an organization thrive if less than a quarter of leadership is data literate? The short answer is, it can’t.
So, how do you improve your data literacy? It starts with a few simple steps.
- Improve your data analytical skill set by learning the basic concepts.
- Familiarize yourself with data fallacies and think differently about data.
Challenge yourself to make decisions based on data that supports the proposition and not your intuition. If you can do this, then you’re already beginning to embrace data literacy by asking the right questions.
In order to maintain their value and create competitive advantage, companies across all industries need employees to gain insights from data. Data literate employees are essential for transforming business and this kind of productivity reinforces workforce resilience.