Portfolio 1
Data Science and Analytics
Assessment 1: Database Design and Implementation
Data and Information Management • ITEC200
Project Brief
Design and implement a database system for a small business scenario. Your submission must include entity-relationship diagrams showing conceptual design, normalized relational schema (at least 3NF), SQL scripts for table creation and sample data insertion, and complex SQL queries demonstrating joins, aggregations, and subqueries. Provide documentation explaining your design decisions and normalization process.
Project Work
ER Diagram and Conceptual Design
Normalized Schema Documentation
SQL Implementation Scripts
Query Portfolio and Testing
Reflection
This database design project developed my understanding of data modeling and relational database principles. The scenario involved designing a database for an online course management system with students, instructors, courses, and enrollments. The most significant challenge was achieving proper normalization while maintaining query performance. I learned that theoretical normalization principles must be balanced with practical considerations. Understanding functional dependencies was crucial for eliminating redundancy and anomalies. The ER modeling phase required careful analysis of business requirements. I learned to distinguish between entities, attributes, and relationships through iterative refinement. Converting the conceptual model to a normalized relational schema revealed the importance of choosing appropriate primary and foreign keys. Writing complex SQL queries taught me to think declaratively rather than procedurally. Mastering joins and subqueries enabled me to extract meaningful information from normalized data. I learned that well-designed databases make queries more intuitive and maintainable. This project reinforced that database design is both an art and a science, requiring technical knowledge and practical judgment.
Assessment 2: Data Visualization Dashboard
Data Analytics and Visualisation • ITEC622
Project Brief
Create an interactive data visualization dashboard analyzing a real-world dataset. Your dashboard must include data preprocessing and cleaning workflow, at least 5 different visualization types (charts, graphs, maps), interactive filtering and drill-down capabilities, statistical summaries and key performance indicators, and a written report explaining design decisions and insights discovered. Use industry-standard tools such as Tableau, Power BI, or Python libraries (matplotlib, seaborn, plotly).
Project Work
Data Preparation Documentation
Dashboard Screenshots
Interactive Dashboard File
Insights and Analysis Report
Design Rationale Document
Reflection
This data visualization project was comprehensive work analyzing global climate change indicators. I examined temperature anomalies, CO2 emissions, and sea level data to create an interactive dashboard revealing environmental trends and patterns. The project deepened my understanding of visual analytics beyond creating charts. Selecting appropriate visualization types required careful consideration of data characteristics and communication goals. I learned that effective visualizations tell stories and reduce cognitive load for decision-makers. Implementing interactivity proved challenging but rewarding. Adding filters, drill-down capabilities, and tooltips transformed static charts into exploratory tools. I learned that interactivity empowers users to discover insights aligned with their questions and interests. The data preparation phase consumed more time than anticipated. Cleaning inconsistent data, handling missing values, and aggregating time series required attention to detail. I learned that visualization quality depends on data quality, making preprocessing critical to success. Design decisions required balancing aesthetics and functionality. Choosing color schemes, layouts, and chart types involved understanding visual perception principles and accessibility guidelines. This project demonstrated that data visualization is both technical skill and communication art, bridging data science and storytelling.