WM9A9-15 Big Data Analytics & Optimisation 24/25SQL

Java Python 

Module title & code	WM9A9-15 Big Data, Analytics & Optimisation 24/25
Assessment type	Essay
Weighting of mark	70%

Assignment brief

You have been hired by a chained-brand hotel group called Stellar Hotel Group to provide consultancy in big data and analytics technology. The company owns and operates six midscale hotels in the UK. These hotels are: · Stellar Resort Hotel - Cornwall · Stellar City Hotel - London · Stellar Coastal Hotel - Brighton · Stellar Highland Hotel - Inverness · Stellar Lakeside Hotel - Windermere · Stellar Urban Hotel - Manchester The company is based in London, while each hotel has its own independent operation team on site. Each hotel uses its own Property Management Systems (PMS), which manages daily operations such as bookings, check-ins/check-outs, and billing. These systems store data locally, making it challenging to gain a unified view of operations across all properties. They are also using HubSpot for managing customer interactions and data. Google Analytics is being used now in the company for tracking the performance of marketing campaigns, but it is not integrated with the booking and CRM system. Overall, data is currently stored in disparate systems, and there is limited use of advanced analytics. Basic reporting is done using tools like Excel and basic SQL queries, which are insufficient for deriving deep insights. Under such context, the company is now facing some challenges. The company collects customer data separately at each hotel, resulting in a fragmented view of guest preferences and behaviour. This lack of integration prevents the company from fully understanding their customers, leading to missed opportunities for effective marketing and consistent customer experience. The company also struggles to optimise the room pricing due to limited analytics capability. Room rates are often set based on historical data. In addition, the data is not well tracked and analysed within the company. There is lack of consistent way of data tracking and analysis, which is leading to inefficient allocation of resources and budgets. Given the challenges, the company is seeking opportunities of applying big data analytics technology. As a consultant, you are expected to provide a report with solutions for the application of big data technologies in the company. In particular, your report should include: · A critical evaluation of the current data technology setting of the company and the new opportunities of applying big data analytics technologies in this company · Recommendation(s) of big data analytics technology for addressing the existing issue(s) with consideration of potential challenges/risks associated with extended use of big data and analytics technology by the company. Some guidance shdai 写WM9A9-15 Big Data, Analytics & Optimisation 24/25SQL ould be provided to mitigate the risks while implementing the new technologies within the company · A dashboard solution for the company to track the data more efficiently and support decision making. You are required to use given dataset to build a demo dashboard, along with some explanation and evaluation. Here are some instructions for providing your dashboard solution: § A clear target of your dashboard § A demonstration of your dashboard on how it follows best practices of data visualisation § An evaluation of your dashboard on how it would effectively help tracking data and support decision-making within the organisation § Any plan for future improvement (i.e. getting more data or deployment plan) You are allowed to make more assumptions about the company as you like to help you answer the questions more realistically. Please state clearly what your assumptions are, and they should be integrated well with the given information. Additional document along with dataset for dashboard design will be accessible from the module's Moodle site. References from both academic and commercial sources should be included.

Word count	Suggested word count ~ 2,800 words for the main body of content, not including executive summary, table of contents and reference list. Plus or minus 10% of the word limit is acceptable.
Module learning outcomes (numbered)	L1. Demonstrate a comprehensive understanding of the key differences between Big Data technologies and analysis methods and traditional approaches. L2. Evaluate real-world scenarios and devise appropriate analytical solutions. L3. Demonstrate a comprehensive understanding of the core concepts of visual communication and data visualisation. L4. Collaboratively analyse digital business requirements and practically implement analytics and optimisation techniques in real-world settings
Learning outcomes assessed in this assessment (numbered)	L1, L2, L3
Marking guidelines	See below
Academic guidance resources	Time will be reserved during the module to review the module assignment and for students to raise questions, and students are permitted to ask the Module Leader questions about the assignment up to the submission deadline