Data technician Level 3
Develop the skills needed to turn data into valuable business insights with our Level 3 Data Technician Apprenticeship. Designed for individuals looking to start or advance a career in data, this programme combines practical workplace experience with industry-relevant training to build confidence in collecting, analysing, managing, and presenting data.
Throughout the apprenticeship, learners will gain a strong understanding of data quality, data protection, reporting, visualisation, and business intelligence. They will develop the technical and professional skills required to work with data effectively, using tools and techniques that support informed decision-making across a wide range of industries.
Key Information
Duration
24 month programme followed by a 3-month End Point Assessment phase.
Funding options.
If you pay into the apprenticeship levy this is 100% funded at £13,000.
Or
a maximum £650 (5% contribution) if you are a non-levy employer.
Fully funded for a 16-21 year old within a non-levy employer
Knowledge
Data Fundamentals
Develop an understanding of different types of data including structured and unstructured data, qualitative and quantitative information, and common data formats such as numeric, text and compound data types. Learn about internal and external data sources, open datasets, and how organisations store and manage information using databases, spreadsheets, digital applications and other data storage formats.
Data Analysis and Visualisation
Develop knowledge of data analysis techniques, statistical methods and visualisation tools used to identify trends, patterns and insights. Understand how spreadsheets, dashboards, charts and reporting tools can support data-driven decision making and improve organisational performance.
Data Quality and Validation
Understand common data quality issues such as duplicate records, inconsistencies, mis-classification and obsolete information. Learn techniques for validating, cleansing and auditing data to ensure accuracy, completeness, consistency and traceability.
Data Technologies and Emerging Trends
Develop an understanding of how data supports technologies such as Artificial Intelligence (AI), Machine Learning, Generative AI and the Internet of Things (IoT). Explore the relationship between data quality, bias, automation and ethical technology use.
Prompt Engineering and Data Transformation
Understand how prompt engineering techniques can be used to research, identify and evaluate effective data transformation methods while maintaining data quality, integrity and compliance.
Data Collection and Management
Understand how to access, extract, collate and format data from identified sources in line with organisational standards. Learn the importance of selecting appropriate data formats to support accurate analysis, effective communication and data integrity.
Data Privacy, Security and Compliance
Understand why data may need to be anonymised and the methods used to protect personal and sensitive information. Gain knowledge of legal and regulatory requirements including GDPR, the Data Protection Act, intellectual property rights, data sharing regulations and sector-specific standards.
Communication and Stakeholder Engagement
Learn how to communicate data findings effectively using a range of methods, formats and technologies. Understand how different audiences require different levels of detail and how to tailor data communications for technical and non-technical stakeholders.
Sustainability, Diversity and Inclusion
Understand sustainable data practices, including responsible data storage and environmental considerations. Learn the importance of cultural awareness, accessibility, equity, diversity and inclusion when working with data and within organisations.
Skills
Data Collection and Preparation
Select, extract and migrate data from identified sources, ensuring information is accurately formatted, organised and stored for analysis. Apply organisational standards when preparing and managing datasets.
Data Integration
Combine data from multiple sources and transform it into formats suitable for reporting, analysis and operational requirements. Utilise appropriate tools and techniques to ensure consistency and accuracy across datasets.
Data Visualisation and Reporting
Present data and findings clearly using dashboards, charts, reports and other visualisation tools. Adapt communication methods to suit different audiences and stakeholder requirements.
Sustainable Data Practices
Apply sustainable approaches to data management, including efficient storage, version control, cloud-based collaboration and reduction of unnecessary duplication and resource usage.
Planning and Prioritisation
Manage workloads effectively by prioritising tasks, organising activities and considering the impact of work on colleagues, stakeholders and organisational objectives.
Data Analysis and Interpretation
Summarise, analyse and explain data using appropriate tools and statistical techniques. Identify trends, patterns and insights that support decision-making and business objectives.
Data Quality Management
Identify, investigate and resolve data quality issues including gaps, duplicates, inconsistencies and outliers. Validate and audit datasets to maintain accuracy, completeness and reliability.
Documentation and Compliance
Produce clear and consistent documentation of data processes, outputs and actions taken. Store, manage and distribute data in accordance with organisational policies, legislation and industry standards.
Collaboration and Stakeholder Working
Work effectively with colleagues and stakeholders to achieve shared goals. Collaborate across teams, contribute to data-related activities and communicate findings in a professional and accessible manner.
AI and Data Transformation
Use appropriate tools, technologies and prompt engineering techniques to research, apply and evaluate data transformation methods, ensuring data quality and integrity are maintained throughout the process.
Behaviours
Professional Responsibility
Take ownership of tasks and responsibilities, working independently and methodically to deliver accurate and reliable outcomes while meeting deadlines and stakeholder expectations.
Collaboration and Inclusion
Work inclusively with colleagues, valuing diverse perspectives and supporting accessibility and social inclusion within the workplace and when communicating data findings.
Adaptability and Continuous Improvement
Remain open to feedback, new technologies and changing business needs. Seek opportunities to improve processes, develop skills and enhance the value of data within the organisation.
Attention to Detail
Demonstrate a structured and thorough approach to working with data, ensuring high standards of accuracy, consistency and quality in all activities.
Sustainability
Act responsibly to reduce environmental impact through sustainable working practices, including efficient data storage, minimising waste and promoting responsible use of digital resources.
Ethical Working
Demonstrate integrity and professionalism when handling data, ensuring compliance with legal, regulatory and ethical standards while maintaining confidentiality and trust.
Who is it the Data Technician (Level 3) suitable for?
- Employees responsible for maintaining databases, spreadsheets, records or management information systems.
- School leavers, career changers or existing employees seeking a recognised qualification in data management and analysis.
- Individuals beginning a career in data, analytics, business intelligence or reporting.
Find the full qualification specifications here
Whether you are a learner or employer, National Upskill are here to assist you.
If you have any questions for our team, please get in touch at info@nationalupskill.co.uk.
You can also call us at 0333 772 9534.
