Knowledge and Understanding

At the end of the apprenticeship, apprentices should be able to demonstrate knowledge in:

K01. The strategic importance of technology enabled business processes, and how they are designed and managed to determine a firm’s ability to compete effectively;

K02. The principles of business transformation and how organisations integrate different management functions in the context of technological change;

K03. Own employer’s business objectives and strategy, its position in the market and how own employer adds value to its clients through the services and/or products they provide;

K04. How to justify the value of technology investments and apply benefits management and realisation;

K05. The role of learning and talent management in successful business operations.

K06. The role of leadership in contemporary technology based organisations;

K07. The personal leadership qualities that are required to establish and maintain an organisation's technical reputation.

K08. The role of leaders as change agents and identify contributors to successful implementation;

K09. How to monitor technology related market trends and research and collect competitive intelligence;

K10. Technology road-mapping concepts and methods and how to apply them;

K11. How key algorithms and models are applied in developing analytical solutions and how analytical solutions can deliver benefits to organisations;

K12. The information governance requirements that exist in the UK, and the relevant organisational and legislative data protection and data security standards that exist. The legal, social and ethical concerns involved in data management and analysis;

K13. The principles of data driven analysis and how to apply these. Including the approach, the selected data, the fitted models and evaluations used to solve data problems;

K14. The properties of different data storage solutions, and the transmission, processing and analytics of data from an enterprise system perspective. Including the platform choices available for designing and implementing solutions for data storage, processing and analytics in different data scenarios;

K15. How relevant data hierarchies or taxonomies are identified and properly documented;

K16. The concepts, tools and techniques for data visualisation, including how this provides a qualitative understanding of the information on which decisions can be based.

Cognitive Skills

At the end of the apprenticeship, apprentices should be able to demonstrate knowledge, skills and behaviours to:

1. Have an understanding and appreciation of the scientific approach to data science and its relevance to society and everyday life;

2. Data comprehension and analytics through knowledge and understanding gained from the programme;

3. Independent and collaborative problem-solving by applying the knowledge and understanding of concepts, theories, methodologies and techniques gained from the programme;

4. Critical analysis and evaluation of solutions and software tools through an understanding of their strengths and limitations, their suitability in problem solving, and any trade-off issues ;

5. Model and solution testing through use of recognised and appropriate criteria and rigorous procedures and draw objective conclusions;

6. Developing understanding and appreciation of professional issues in relation to proper use of data science technology and related GDPR guidelines in the UK

Practical/Transferable Skills

Subject Related Practical Skills:

At the end of the apprenticeship, apprentices should be able to demonstrate skills to:

S01. Identify, document, review and design complex IT enabled business processes that define a set of activities that will accomplish specific organisational goals and provides a systematic approach to improving those processes;

S02. Design and develop technology roadmaps, implementation strategies and transformation plans focused on digital technologies to achieve improved productivity, functionality and end user experience in an area of technology specialism;

S03. Deliver workplace transformations through planning and implementing technology based business change programmes including setting objectives, priorities and responsibilities with others in an area of technology specialism;

S04. Negotiate and agree digital and technology specialism delivery budgets with those with decision-making responsibility;

S05. Develop and deliver management level presentations which resonate with senior stakeholders, both business and technical;

S06. Professionally present digital and technology solution specialism plans and solutions in a well-structured business report;

S07. Demonstrate self-direction and originality in solving problems, and act autonomously in planning and implementing digital and technology solutions specialist tasks at a professional level;

S08. Be competent at negotiating and closing techniques in a range of interactions and engagements, both with senior internal and external stakeholders;

S09. Evaluate the significance of human factors to leadership in the effective implementation and management of technology enabled business processes;

S10. Develop own leadership style and professional values that contributes to building high performing teams;

S11. Apply broader technical knowledge combined with an understanding of the business context, and how it is changing, to deliver to the company’s business strategy;

S12. Demonstrate effective technology leadership and change management skills for managing technology driven change and continuous improvement;

S13. Create and implement innovative technological strategies to support the development of new products, processes and services that align with the company’s business strategy, and develop and communicate compelling business proposals to support these.

S14. Identify and select the business data that needs to be collected and transitioned from a range of data systems; acquire, manage and process complex data sets, including large-scale and real-time data;

S15. Undertake analytical investigations of data to understand the nature, utility and quality of data, and developing data quality rule sets and guidelines for database designers;

S16. Formulate analysis questions and hypotheses which are answerable given the data available and come to statistically sound conclusions;

S17. Conduct high-quality complex investigations, employing a range of analytical software, statistical modelling & machine learning techniques to make data driven decisions solve live commercial problems;

S18. Document and describe the data architecture and structures using appropriate data modelling tools, and select appropriate methods to present data and results that support human understanding of complex data sets;

S19. Scope and deliver data analysis projects, in response to business priorities, create compelling business opportunities reports on outcomes suitable for a variety of stakeholders including senior clients and management.



Behavioural and Transferable Skills:

At the end of the apprenticeship, apprentices should be able to demonstrate the following behaviours:

B01. Inspire and motivate others to create strong positive relationships with team members to produce high performing technical teams.

B02. Establish high levels of performance and be results and outcomes driven to achieve digital and technology solutions objectives;

B03. Be results and outcomes driven to achieve high key performance outcomes for digital and technology solutions objectives;

B04. Promote a high level of cooperation between own work group and other groups to establish a technology change led culture;

B05. Develop and support others in developing an appropriate balance of leadership and technical skills;

B06. Create strong positive relationships with team members to produce high performing technical teams


They should be able to demonstrate the following transferable skills:

1. Intellectual skills in critical thinking, information literacy, putting forward a sound argument;

2. Research skills such as collecting, selecting, analysing and documenting literature regarding relevance and recency;

3. Autonomy and independence in self-guided learning, self-management, reflection and dealing with deadlines ;

4. Communication skills in conversing ideas to people of various backgrounds effectively, and being able to convince others;

5. Teamwork in tackling problems of complex natures, being able to compromise and negotiating acceptable conclusions;

6. Contextual awareness of the needs of individual and community, the working environments of business organisations, opportunities and challenges created by computer based solutions;