Case Study
AI Architecture & Systems Case Study
Weather Analysis Dashboard
Multi-City Meteorological Trends & Correlation Dashboard
Role & Architecture
Systems Architect
Release Timeline
April 2024
Core Stack
Power BI • SQL
Verification
Production Tested
1 / 1
01Executive Overview
An end-to-end meteorological analytics project analyzing long-term climate patterns, temperature extremes, humidity variations, and wind dynamics across global cities using SQL data modeling and interactive Power BI dashboards.
02The Engineering Challenge
Operational Problem & Constraints
Critical friction and failure modes observed in existing workflows
Raw meteorological datasets are often high-volume, multi-dimensional, and contain missing or noisy readings across disparate city sensors, making holistic trend analysis and correlation discovery difficult for researchers.
03Architecture & Technical Solution
System Architecture & Algorithmic Design
Engineering methodology, model selection, and pipeline design
Designed a comprehensive SQL schema to clean, normalize, and aggregate hourly weather records across cities (humidity, air pressure, temperature, wind vectors). Built star-schema data models in Power BI with custom DAX measures for seasonal decomposition, rolling averages, and cross-variable correlations.
04Quantified Impact & Benchmarks
Empirical Outcomes & Performance Metrics
Validated benchmarks, latency figures, and operational efficiency
Synthesized over 500,000 hourly weather records into an intuitive dashboard, enabling instant identification of micro-climate variations and meteorological anomalies.
05Core Capabilities & System Features
01
Multi-city climate comparison with geographical mapping and coordinates
02
Hourly and seasonal trend analysis with dynamic date slicing
03
Cross-variable correlation matrix (Temperature vs Pressure vs Humidity)
04
Wind rose and velocity distribution modeling across seasons
05
Custom DAX measures for anomalies and historical percentile ranks
06
Interactive filtering by climate zones, seasons, and city clusters
06Data Specifications & Telemetry
Dataset Description
City Attributes (City, Country, Latitude, Longitude)
Hourly Humidity
Atmospheric Pressure
Temperature
Weather Condition Descriptions
Wind Direction & Speed
Operational Interface & Observability
The Power BI dashboard provides comprehensive insights into weather patterns, seasonal variations, and correlations between different weather attributes. Users can interactively explore data trends, visualize historical weather data, and derive actionable insights.
07Technologies & Frameworks
Production libraries, architectural components, and runtimes used in this system:
Power BI
SQL
DAX
Excel
Data Modeling
ETL
Statistical Analysis
08Artifacts & Verifiable Deliverables
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