Data Literacy: What it is and why it matters

Data literacy has several components, which together add up to someone becoming a data-literate person. One of the formal definitions states that data literacy is "the ability to read, work with, analyse, and argue with data." Being data literate means possessing an understanding of what data is and its characteristics (sources, types, formats and features), data applications (for analysis, business intelligence, data science, artificial intelligence and analytics), data techniques (such as pattern discovery, pattern recognition and prediction), and data communication (storytelling, evidence-based reasoning and visualisation).

Data literacy is growing in importance for multiple reasons. These can be grouped into three categories:

Individuals - There are huge career opportunities and numerous job openings. Most students become fascinated with the topic once they understand what it is and why it is important.

Organisations - For organisations, there is pressure to use their data for business insight, innovation and value creation. An organisation's data is one of its most valuable assets, and it is a renewable asset – so the same data can be used and re-used in different applications to fuel various projects and to enrich multiple value streams across the enterprise.

Market forces - In addition, market forces are rewarding organisations that are data-driven with a data-literate workforce. Organisations that lag in these areas are also beginning to lag in competitiveness, becoming less likely to attract top talent and experiencing a downturn in market value.

The key to a data-driven culture within the modern workplace

This four-week programme provides the core data literacy skills that most employers are looking for. Over approximately eight hours, the self-guided lessons present the key skills of data awareness, data collection, data quality, data validation and data ethics. You will be introduced to data visualisation whilst exploring the misrepresentation and distortion of data.

Learning Schedule

For the duration of the programme, you should expect to spend approximately one hour per day to complete the course materials and end of module quizzes - approximately eight hours in total.

Extended Learning

Further self-study materials are referenced within the final module should you wish to extend your learning beyond this course.

You will gain an awareness of:

• Where data comes from
  
• How it is collected
• How data is used
• Data quality
• Data governance
• Basic data visualisation and charts
• How to interpret data visualisations
• How to recognise misleading representations.

Learning outcomes are aligned to the UK Government’s Digital, Data and Technology skills & capability framework.

What experience do I need to complete the free SAS STEP Data Literacy learning pathway?

The Data Literacy learning pathway is ideally suited for anybody who is currently unemployed and holds the following qualifications and skills:

• GCSE Maths (or equivalent)
• GCSE English (or equivalent)
• IT Literate
  (You should be proficient in using a computer (or other internet-enabled device) to:

- search the internet
- access and navigate websites
- communicate and collaborate with others using email or social media
- locate, open, edit and save files
- follow instructions for basic computing tasks
- solve problems and find solutions using digital tools, e.g. using online tutorials to learn / teach yourself simple tasks