Data Extraction | Transforming Data| Visualising Data & Creating Reports In-depth understanding of Spatial Econometrics techniques and application to real-world problems Collaborative report writing in R Professional visualisation Link to the Github Repository Green Space Semivariogram Percentage Green Space per Ward in Greater London (North, East, South and West)

The Multinational Retail Data Centralisation project consolidates data from multiple sources, such as AWS RDS, PDFs, APIs, and AWS S3 buckets, into a centralised PostgreSQL database. It involves cleaning the data using Python tools, such as Pandas, and creating a star-schema database to optimise querying and analysis, facilitating insights such as sales metrics and regional performance.

This collaborative report models the relationship between green space accessibility and demographic as well as health variables across London, offering insights into urban planning and public health.

Data Extraction| Transforming Data | Visualising Data| Creating Reports Data mining and statistical analysis Strong understanding of machine learning techniques and algorithms Collaborative report writing Proficient coding in R and Python Link to the Github Repository Kernel density estimation plot

3D Reconstruction Link to the Github Repository