This involves looking at different types (qualitative/quantitative) and features of data, such as accuracy, completeness and sample size, helping to assess its quality, spot errors, and interpret it into meaningful findings.
Many organisations are at an early stage of their data journey. Before they can truly embark on this, they first need to gain an understanding of how data can transform their organisation or sector.
Learners will be able to assess the ethical implications of using data to drive decision making, including an understanding of bias/prejudice and what impact this can have on data science work.
Using data analysis tools to explore and take meaning from data, make calculations (from taking averages to advanced analytical models) and select suitable visualisations, using commonly used platforms (particularly Excel at Citizen and Worker level).
After gaining this skill, learners will have an understanding of why data is becoming more important, its impact, common sources of data, and how it is used (and misused) by individuals, organisations and across society.
This will ntroduce learners to the vocabulary used in data science and analytics and give them an understanding of the different data roles in an organisation.
