Optimize Your Data Warehouse with Advanced Denormalization

Optimize Your Data Warehouse with Advanced DenormalizationOptimize Your Data Warehouse with Advanced Denormalization

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Mahmoud Ashry

• 2d

Project Title:

Advanced Data Warehouse Optimization – SalesPilotDW (Phase 2: Denormalization)

Project Description:

Built directly upon the core infrastructure established in Phase 1, this phase focuses on advanced data warehouse refactoring and high-performance denormalization to optimize the analytical layer for enterprise business intelligence.

Core Tech Stack & Tools Used: • Analytics & BI: Power BI (Executive Dashboards with Row-Level Security applied) • Databases & Optimization: PostgreSQL, SQL Server (ARM-based OCI Ampere A1 Migration) • Infrastructure & Monitoring: Python ETL, Telegram API Alerts & Logs

Key Evolutionary Enhancements & Achievements: • Strategic Data Denormalization: Restructured over 18 complex normalized tables from Phase 1 into a high-performance Star Schema (optimized Fact and Dimension tables) to streamline analytical queries. • Query Performance Tuning: Drastically reduced Power BI dashboard refresh latency and optimized data retrieval speeds through strategic denormalization and database environment fine-tuning. • Enterprise Security Deployment: Implemented advanced Row-Level Security (RLS) within Power BI to ensure safe, role-based data access for key stakeholders.

Microsoft Power BI Data Modeling PostgreSQL Python

Johnathan Kimbrough

pro

• May 28

Check it out

AWS Claude Python

Johnathan Kimbrough

pro

• 8h

Thanks

En Zuo

pro

• May 28

😊 GIS Mapping and Environmental Site Plan Development for Approval Documentation I developed a professional GIS mapping package for an environmental approval project, including site boundary mapping, receptor buffer analysis, infrastructure marking, coordinate tables, A3 layout design, scale bars, legends, north arrows, and regional location insets. The final outputs were prepared as clear, approval-ready maps using high-resolution aerial imagery and GDA2020 / MGA Zone 50 coordinate reference standards.:

QGIS Python mapping Data Visualization

Nazar Kaneruk

• May 29

His work so cool!

En Zuo

pro

• May 28

GIS-Based Terrain Analysis and DEM Visualization in Sinai This project is a GIS-based terrain analysis created for the Sinai region using digital elevation model data. The work focuses on extracting and visualizing key topographic characteristics, including aspect direction, hillshade relief, slope variation, and contour elevation patterns.

The project includes four separate thematic maps: aspect analysis, hillshade visualization, slope classification, and contour mapping. Each map was designed with coordinate system information, scale bar, north arrow, legend, and terrain background to support professional cartographic presentation. The outputs help identify terrain direction, elevation behavior, surface steepness, landform structure, and topographic variation across the study area.

My work involved processing DEM data, generating raster-based terrain layers, creating slope and aspect classifications, producing hillshade relief, extracting contour information, styling each map layer, and preparing clean map layouts for presentation. This project demonstrates my ability to handle geospatial raster analysis, terrain modeling, and professional GIS map production.

Skills & Tools: ArcGIS Pro, QGIS, GIS Mapping, DEM Analysis, Terrain Analysis, Raster Processing, Hillshade Mapping, Slope Analysis, Aspect Analysis, Contour Mapping, Cartography, Coordinate Systems, Spatial Analysis, Map Layout Design, Geospatial Data Visualization.