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NCFE Level 4 Unit 04 Stakeholder Engagement and User Experience in Data Analytics (H/651/0927) Asignment Brief 2026
| University | Northern Council for Further Education (NCFE) |
| Subject | Unit 04 Stakeholder Engagement and User Experience in Data Analytics (H/651/0927) |
NCFE Level 4 Unit 04 Assignment Brief
| Qualification | NCFE Level 4 Diploma: Data Analyst (603/7751/3) |
| Unit Reference Code | H/651/0927 |
| Unit Title | Stakeholder engagement and user experience in data analytics |
| Unit Number | 04 |
| Unit Level | 4 |
Unit Summary
This unit explores the critical aspects of optimising user experience and adopting effective stakeholder engagement within the realm of data analytics. This unit empowers learners to understand the factors that influence user experience and to adeptly define stakeholder requirements to ensure meaningful and impactful data analysis outcomes.
Learning Outcomes
| Learning outcomes (LOs) | Mandatory teaching content |
| 1. Examine how to plan and deliver an effective analysis for a range of stakeholders | Knowledge:
Identifying internal and external stakeholders Approaches to collecting stakeholder requirements (for example, interviews) The importance of identifying the scope of data analysis, including timescales, purpose, expected outcomes and the impact of scope creep The role and structure of use cases, user stories and scenarios in documenting user requirements Factors that could influence data analytic planning (for example, constraints and resource availability) The importance of identifying dataset needs and where these will be sourced, including internal and external data |
| 2. Demonstrate how to collate and display data using the most appropriate visualisation tools and assess the impact on user
experience
|
Skills:
Use of visualisation tools: • infographics • reports • tables • dashboards • charts/graphs Assess the impact of the user experience on the data analysis activity |
| Learning outcomes (LOs) | Mandatory teaching content |
| 3. Explore factors that can impact user experience in relation to data analytics | Knowledge:
Accessibility measures that can be applied to improve end-user experience (for example, colour, font, layout) The application of usability theories to improve end-user experience: • Fitts’ Law • Miller’s Law • Nielsen’s Usability Heuristics How end-user requirements influence the way that data is presented The potential impacts of not meeting end-user requirements when presenting data Skills: Undertake analysis based on stakeholder requirements Implement findings of data analytics into planning and document outputs Collaborate and communicate with stakeholders to understand requirements, taking into account: • stakeholder type (for example, internal, external) • appropriate styles and behaviours • utilisation of technology |
Grading Criteria
| Learning outcomes (LOs) | Pass | Merit | Distinction |
| LO1: Examine how to plan and deliver an effective analysis for a range of stakeholders | P1: Identify internal and external stakeholders and list techniques used to gather user requirements | M1: Discuss the role and structure of user requirement documenting methods
within the data analytic planning process |
D1: Evaluate internal and external stakeholder needs in each stage of a data analysis and the impact of not adhering to these
needs
|
| P2: Describe factors that could influence data analytic planning and outline the significance of defining the scope of data analysis | |||
| P3: Explain the importance of identifying dataset | |||
| Learning outcomes (LOs) | Pass | Merit | Distinction |
| needs and how these will be sourced | |||
| P4: Demonstrate the ability to undertake analysis based on stakeholder requirements and clearly communicate findings | M2: Simplify the insights of an analysis and effectively communicate findings to stakeholders | ||
| LO2: Demonstrate how to collate and display data using the most appropriate
visualisation tools and assess the impact on user experience
|
P5: Collect and present data using the most appropriate visualisation tools | M3: Demonstrate how amending user requirements shapes data approaches, stating the impact of not meeting these requirements, and demonstrate the ability to use visualisation tools strategically and determine their impact
on the user experience
|
D2: Analyse how amending user requirements shapes data presentation approaches, whilst evaluating the significant impact of not
meeting user requirements on data presentations. Demonstrating proficiency in using visualisation tools on the user experience |
| P6: Describe how a visualisation impacts user experience | |||
| P7: Explain how enduser requirements shape data presentation approaches and state the impact of not meeting these requirements | |||
| LO3: Explore factors that can impact user experience in relation to data analytics
|
P8: Explore a range of accessibility measures and usability theories and describe how these can be applied to improve the user experience | M4: Examine the role of user experience in data analytics and discuss the techniques required to produce effective data visualisations | D3: Assess how accessibility measures can be utilised in a variety of ways and evaluate how they can vary in their impact regarding individual needs |
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