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04Data Analytics · Business IntelligenceCompleted

Operational Analytics & BI

An operational analytics project that transforms service data into dashboards designed to understand demand, waiting times, SLA performance and operational bottlenecks.

Technologies used
PythonPandasNumPyMatplotlibSeabornPower BIDAX
Context

Operational data is only useful when it helps people understand what is happening and decide what to do next. This project focused on analysing service activity, demand, waiting times, attention times, SLA compliance and operational performance.

Analysis

The analysis covered demand patterns, service behaviour, waiting and attention times, abandonment and operational congestion. The objective was to move beyond descriptive numbers and identify patterns that could support operational decisions.

Visualization

The results were structured into dashboards focused on three perspectives: executive performance, operational demand and congestion, and service-level indicators such as waiting times and SLA performance.

Outcome

The project demonstrates the connection between data preparation, exploratory analysis, business intelligence and decision-making — the foundation that later supports more advanced analytical and machine learning work.