Data Management Fundamentals: Beginner’s Guide to Data Success

Description

Professional Learning: Complete online at your own pace, supported by weekly online discussion sessions

The key to the effective use of data is managing it well. Learn how to care for and use your data effectively with The Data Lab’s Data Management Fundamentals course.

Who is it for?

The course provides an excellent introduction to data management for learners of all levels. This course is for people who collect, store, manage and analyse data as part of their job but whose primary job function may be outside the field of data. For example:

• Managers, technicians, clerical support workers
• People working in a data-related role but who are unfamiliar with data management

What will you learn?

By the end of the course, you will be able to:

• Describe ways in which data can be cared for, and how organisations benefit from caring for their data
• Identify the features of high-quality data and suggest ways in which the quality of a dataset could be improved
• Know how to protect your personal data and understand how organisations can keep their data safe
• Describe how data can be misused and the ethical risks with using data and explain what data bias is, its causes and how it can be mitigated against

Delivery format

Over five weeks you’ll follow a self-paced online programme, with weekly group discussions hosted by one of the Data Lab’s experts to guide your learning and answer any questions. Group size is limited to a maximum of ten learners.

You will receive access to the Data Lab’s online platform from 16 February 2026.

The online discussions will take place from 11:00-12:00 on 23 February, the 2, 9, 16 and 23 March 2026.

More course details can be found here – Data Management Fundamentals Course | The Data Lab

Completion requirements

Students are required to complete all modules.

Module 1: Introduction

• An introduction to data management
• Caring for different types of datasets, reference data, main data, transactional data and metadata
• How to create a data dictionary
• The data lifecycle
• Data governance, security, and quality
• Data architecture, modelling and design
• Data storage, operations, integration and interoperability

Module 2: Data Quality

• Understanding high and low quality data
• The impacts and dimensions of high and low quality data
• Improving the quality of data

Module 3: Data Security

• Keeping your personal data secure
• Password managers and extra protection
• Device security, firewalls, WiFi and protecting your information online
• Keeping organisational data secure
• Understanding data breaches and how the law can protect your data
• GDPR roles and right of access
• Encryption and other methods of data protection

Module 4: Data Ethics

• Understanding data ethics
• Understanding data misuse
• Malicious data misuse for personal, political or commercial gain
• What to do if you misuse, or see data misuse
• Understanding data, sampling and algorithmic bias
• Causes of bias and how to mitigate bias

Module 5: Wrap Up

• Final thoughts and review of key concepts
• Further resources and next steps

Fees and funding

This is a fully funded course

Additional information

This online course is self-directed and you can complete it in your own time. It is supported by online discussions with the Data Lab to guide your learning and help answer any questions.

The course is open for enrolment from 16 February 2026. All learning must be completed by 31 March 2026.

Places are fully funded places for individuals working in Scottish public sector organisations.

Learners are expected to complete the course within the specific timescale. Regular reminders will be sent to ensure timely progress.

Learners are required to complete the course evaluation once they finish the course.

Failure to engage with the course may result in a £100 fee being recovered to cover costs and allow places to be offered to other learners.

Once you register (see top of page), you will receive an email with joining instructions from The Data Lab. Your place on the course is not confirmed until you accept the invitation to join from The Data Lab. If you do not accept the invitation, your place may be reallocated to another learner.