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Business Consultancy Project
5,000 words
Business Consultancy Project – Summative Coursework
This assessment requires students to complete a 5,000-word Business Consultancy Project designed to replicate the work of a professional consultant. The project accounts for 100% of the module assessment and requires students to investigate a clearly defined business issue, challenge or problem identified in the earlier Consultancy Project Proposal. Students must use the same client, topic and issue proposed in the previous submission unless a change has been strongly recommended through feedback or endorsed by the supervisor or tutor. The consultancy project requires deep and independent research using credible secondary sources, including recent peer-reviewed academic journals, industry reports and reputable business publications. The analysis should translate evidence into meaningful insights and actionable recommendations that create strategic value for the client organisation. The report must critically analyse the selected business problem rather than simply describe the organisation or relevant theories. The report should contain an Executive Summary, Introduction, Company/Client Overview, Problem Definition and Consultancy Focus, Stakeholder Analysis, Data Analysis and Framework Application, Recommendations and Conclusion, and a 500-word Employability Reflection. The Data Analysis and Framework Application section carries the largest indicative allocation at approximately 1,800 words and requires students to apply two or three relevant models or frameworks. Examples provided in the brief include SWOT, PESTLE, Porter’s Five Forces and the Balanced Scorecard. Students are also expected to present and interpret secondary data using appropriate tables, charts, Excel outputs or pivot tables. The Recommendations and Conclusion section should provide three actionable and prioritised recommendations supported by evidence, while considering implementation risks, barriers and anticipated benefits. The Employability Reflection should consider research, analytical, problem-solving, project management and communication skills, together with teamwork, leadership, ethical awareness, sustainability, personal development, career relevance and future professional growth. The assessment requires Harvard referencing throughout. The report should use professional formatting, third-person academic writing, numbered pages, correctly labelled tables and figures, and accurate in-text citations and references. The brief emphasises the use of recent and credible sources, with the majority of references expected to come from publications within the previous 6–12 months.
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Big Data and Cloud Computing
2,500 words
Big Data and Cloud Computing: FieldVision Cloud-Based Big Data Solution for AgroNova
This assessment is a 2,500-word individual report for the Big Data and Cloud Computing module within the MSc Management with Data Analytics programme at BPP University. The report is based on a fictional agricultural technology company, AgroNova, and its FieldVision project. AgroNova provides climate change and crop monitoring services to farmers in the UK and intends to expand internationally. However, its existing ageing infrastructure and manual processes present challenges to international expansion and the development of data-driven decision-making. The FieldVision project aims to use Internet of Things (IoT) technology and cloud-based big data solutions to collect, store and analyse real-time information from agricultural environments. The report requires students to act as a big data and cloud solution consultant and provide recommendations to senior management at AgroNova. The project involves IoT devices such as CropCam aerial cameras supplied by HydroSense and SmartHarvester solar-powered sensors supplied by SoilTech. These technologies collect information including crop imagery, soil moisture, temperature and humidity. The resulting data can support crop monitoring, risk assessment, early warning alerts, irrigation decisions, crop-failure claims validation and other farming-related insights. The first task focuses on Big Data Requirements and Storage Solutions. Students must identify the requirements arising from the scenario and critically evaluate a range of cloud-based big data storage solutions. The evaluation should consider factors such as capacity, functionality and costs. The second task requires students to propose one appropriate cloud-based solution architecture supported by an architecture diagram showing the essential components from data sources through to reporting. The selected architecture must be analysed in relation to AgroNova's requirements and the storage solutions considered in Task 1. The third task addresses Project Risks and Issues. Students must critically appraise the risks and issues associated with deploying the proposed cloud-based big data solution and identify appropriate mitigation approaches. These issues should be connected directly to the storage solutions and proposed architecture. The scenario highlights concerns from AgroNova's CISO, CFO and Chief Reputation Officer regarding potential data breaches, high costs and poor returns on investment, making security, financial viability and organisational risk important considerations. The report should contain an approximately 200-word introduction, an 800-word analysis of Big Data Requirements and Storage Solutions, a 500-word Proposed System Architecture section supported by relevant diagrams, an 800-word Project Risks and Issues section, and an approximately 200-word conclusion. Harvard referencing, academic research and appropriate supporting appendices are also required. The assessment addresses three learning outcomes: designing an architecture that supports complex data collection, critically evaluating data storage solutions from an enterprise systems perspective, and critically appraising issues involved in enterprise-system deployment.
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Business Management / Consultancy / Strategic Management
5,000 words
Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations
This Business Consultancy Project assessment requires students to produce a professional 5,000-word consultancy report addressing a strategically important issue, challenge or problem facing a client organisation. The project must normally continue from the topic and client proposed in the earlier Consultancy Project Proposal, ensuring continuity between the proposal and final consultancy work. The assessment is designed to replicate professional consultancy practice through independent research, critical analysis and the development of actionable recommendations. Copy of Apr 25 Onwards brief_EE… Copy of Apr 25 Onwards brief_EE… The report begins with an Executive Summary, followed by an introduction and company/client overview. Students must define one clear business problem, establish the overall project aim and purpose, and specify the consultancy focus, which may relate to areas such as strategy, human resources, marketing or sustainability. The selected issue should be clearly connected to the organisation’s wider strategic and industry context. Copy of Apr 25 Onwards brief_EE… A dedicated Stakeholder Analysis section requires identification and evaluation of internal and external stakeholders. Students must assess stakeholder interests, influence, expectations, conflicts and power relationships, and are encouraged to apply a framework such as Mendelow’s Matrix. The purpose is to show how stakeholder dynamics influence the consultancy problem and the feasibility of proposed solutions. Copy of Apr 25 Onwards brief_EE… The largest section is Data Analysis and Framework Application, where students critically evaluate secondary evidence and apply two or three relevant management frameworks. Suitable approaches may include SWOT, PESTLE, Porter’s frameworks and the Balanced Scorecard. The analysis should incorporate credible company and industry evidence, Excel outputs, tables or charts where relevant, and connect patterns in the data to strategic, operational or HR implications. Ethical and sustainability considerations should be embedded where appropriate. Copy of Apr 25 Onwards brief_EE… The project concludes with three prioritised and evidence-based recommendations. Recommendations should be practical, justified, risk-aware and linked directly to the findings. Students must explain expected benefits and demonstrate how the proposed actions create strategic value for the client organisation. Copy of Apr 25 Onwards brief_EE… The final assessed section is a 500-word Employability Reflection covering skills developed through the project, application of theory to practice, professional behaviours, personal strengths and weaknesses, career relevance and specific future-development actions. Copy of Apr 25 Onwards brief_EE… Overall, the assessment integrates consultancy problem definition, stakeholder analysis, strategic frameworks, secondary-data interpretation, ethics, sustainability, recommendations and professional reflection within a Masters-level business project. The marking criteria reward criticality, current evidence, intellectual originality, professional consultancy thinking and accurate Harvard referencing. Copy of Apr 25 Onwards brief_EE… One important point: the brief states that the majority of references should come from sources published within the last 6–12 months, so the final project is expected to use very current company, industry and academic evidence. Copy of Apr 25 Onwards brief_EE…
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Multimodal Sentiment Intelligence Platform for Dynamic Market Insights
This assignment presents the development of a Multimodal Sentiment Intelligence Platform for Dynamic Market Insights. The project addresses the need for real-time market sentiment analysis by combining text and visual data through an AI-driven multimodal approach. Traditional sentiment analysis methods may have limitations when dealing with diverse data modalities, and this project aims to address this gap by integrating multiple artificial intelligence and deep learning techniques. The primary objective is to develop an AI-driven platform capable of performing real-time sentiment analysis and supporting market trend prediction. The proposed system also aims to generate business intelligence insights that can support applications in marketing, finance, and customer service. The project incorporates deep learning, large language models, and multimodal fusion techniques to improve sentiment understanding. For text-based sentiment analysis, the assignment identifies BERT and GPT-2 for sentiment classification. For visual sentiment analysis, YOLOv8 is used for object detection while DeepFace is incorporated for facial emotion recognition. Feature-level and decision-level fusion strategies are applied to combine information from different modalities and improve the overall sentiment analysis process. Retrieval-Augmented Generation (RAG) is also incorporated to provide context-aware sentiment insights. The proposed platform uses Amazon reviews and IMDb reviews as text datasets. For image or video-based multimodal data, the assignment references the CMU-MOSEI dataset and an Amazon-Reddit merged reviews dataset. Overall, the work focuses on combining natural language processing, computer vision, deep learning, large language models, multimodal fusion, and retrieval-augmented generation to create a platform capable of producing dynamic sentiment and market insights.
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Cloud Computing / Big Data Technologies / Cyber Security
2,500 words
Cloud and Big Data Security Application: Design, Implementation and Evaluation
This assessment for the Cloud and Big Data Technologies module requires students to design, implement and evaluate an individual cloud-based or distributed data application. The project focuses on practical solutions involving the complex transformation, processing, storage and security of big data within cloud environments. Students are expected to demonstrate how distributed data can be organised in the cloud, how data pipelines can be used to access or process distributed databases, and how appropriate security controls can be incorporated into the resulting architecture. Students have considerable freedom when selecting their application. Suggested project directions include developing a data-science solution using SQL or MongoDB with cloud storage and an appropriate security policy; implementing privacy-preserving distributed processing using techniques such as Differential Privacy; creating multi-party authentication and group-based access-control mechanisms; or designing Multi-Level Security, Attribute-Based Encryption or Role-Based Access Control solutions. Projects may also examine distributed or cloud applications using security protocols such as SSH, SSL or IPsec. Creativity and originality are explicitly encouraged. The written component is a Design and Implementation Document of no more than approximately 2,500 words. It should present the project aims and objectives, application concept, cloud and security technologies, functional and security requirements, architecture and design decisions, protocols, access-control mechanisms, implementation process, achievements, problems encountered and overall evaluation. Relevant diagrams, such as interaction or sequence diagrams, may be used to explain system behaviour and architecture. The assessment also requires submission of the functioning Cloud and Big Data Security application and a 7-minute highlight demonstration video. The video should demonstrate the application's major features, implementation details, security functionality and, where appropriate, attack scenarios. Assessment places strong emphasis on the quality of the design and implementation documentation, originality, use of advanced features, and the overall effort and technical quality of the completed application. Students are therefore expected to demonstrate independent development rather than simply reproduce an existing tutorial.
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