Decision-Support System for Social Security Data (CNSS)
A star-schema data warehouse fed by ETL flows, with analytics dashboards for decision-makers.
Overview
An academic business-intelligence project built around social-security (CNSS) style data: designing a data warehouse, automating ETL flows with KNIME and Python, loading MySQL, and publishing analytical dashboards in Tableau.
The problem
Operational data was spread across flat files with inconsistent formats, which made it slow to answer simple management questions such as trends by region, period or category.
What I built
I modelled a star schema (fact table + dimensions), built ETL flows in KNIME and Python to clean, standardise and load the data into MySQL, then designed Tableau dashboards with filters by period, region and category so that indicators can be read in a few clicks.
Results
- A clean, documented star-schema model ready for analysis
- Repeatable ETL flows instead of manual file preparation
- Interactive dashboards answering the main management questions
Highlights
- Dimensional modelling (fact and dimension tables)
- ETL with KNIME and Python: cleaning, standardisation, loading
- MySQL data warehouse
- Tableau dashboards with drill-down filters
