This individual assignment focuses on real-time data ingestion and storage in a Big Data environment. Building on concepts of big data patterns covered in the first half of the course, students will design and implement a scalable data storage solution that supports efficient data ingestion while handling continuous data streams. Through completing this assignment, students will demonstrate their understanding by implementing a real-time data ingestion process, storing data in a structured format, and ensuring the system can handle continuous data streams effectively. The submission includes a self-contained Python implementation in a Google Colab or Jupyter Notebook (.ipynb) and a written report (max. 1,500 words) detailing the design, implementation, challenges, and key insights. This assignment provides practical experience in handling real-time data, designing scalable storage architectures, and applying business intelligence principles in a data-driven environment.

The assignment will be assessed based on several key criteria. Database Setup & Configuration (10%) evaluates the selection, setup, and schema design of a suitable storage system. Implementation of Real-Time Data Ingestion (30%) focuses on successfully connecting to a real-time data source, ensuring continuous and efficient ingestion while maintaining data integrity. Storage Solution Effectiveness (30%) assesses the system’s ability to handle continuous data streams, its scalability, reliability, and how it improves upon previous limitations. Written Report (20%) requires a well-structured explanation of the solution, justification of design choices, and reflection on challenges, limitations, and improvements. Finally, Code Documentation & Organization (10%) considers the clarity, structure, and readability of the Python code. 

This group assignment (2-3 students per team) is the first part of a two-part assessment, leading into Assignment 3. In this phase, students will develop a Business Intelligence (BI) strategy for a chosen industry scenario and present it as a pitch to stakeholders through a recorded presentation (8-12 minutes) and a written executive summary (max. 1,000 words). The focus is on outlining how Big Data can be leveraged for decision-making, covering data ingestion, storage, analytics, and visualisation while aligning the strategy with key business objectives and performance indicators. This assignment emphasises strategic thinking, BI planning, and effective communication. In Assignment 3, students will move from strategy to execution by implementing their BI solution, creating a functional artefact in Python that demonstrates the proposed approach. The artefact, along with a final report and presentation, will be submitted to showcase the practical application of the BI strategy developed in this phase.

The assessment for Assignment 2 evaluates the depth and clarity of the proposed Business Intelligence (BI) strategy, the quality of analysis, and the effectiveness of communication in both the written executive summary and recorded presentation. Industry & Business Problem Analysis (25%) assesses how well the chosen scenario and business challenges are articulated. BI Strategy (40%) focuses on the design of the BI architecture, covering data ingestion, storage, analytics, and visualisation, along with the selection of relevant tools and technologies. Presentation Quality & Communication (25%) considers the clarity, professionalism, and engagement of the recorded presentation, ensuring all team members contribute meaningfully. Finally, Report Structure & Clarity (10%) ensures the executive summary is well-organised, concise, and professional. 

This group assignment (same teams as Assignment 2) is the second part of a larger assessment, focusing on implementing the BI strategy developed in Assignment 2. Students will develop a working prototype that demonstrates Big Data ingestion, processing, analytics, and visualisation to support decision-making. The assessment includes a Python-based implementation, a written report (max. 1,500 words), and a final presentation delivered in Week 12 in front of the class. The implementation must effectively showcase how data is utilised to generate business insights using appropriate Big Data tools and techniques. The report should document the design, implementation process, challenges, and evaluation of the solution’s effectiveness. The presentation will communicate how the system works, key insights derived, and its impact on business decision-making. 

This assignment is assessed on BI solution implementation (40%), evaluating how well the Python-based system handles data ingestion, processing, analytics, and visualisation using appropriate Big Data tools. The written report (30%) will be assessed on clarity, documentation, challenges addressed, and effectiveness of the solution. The final presentation (20%), delivered in Week 12, will be assessed on how clearly the team communicates the system’s functionality, insights, and business impact using visuals and demonstrations. Finally, code documentation and organisation (10%) will be evaluated for clarity, structure, and adequate commenting.