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datatransformation

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The data set contains data about city fuel cycle consumption of vehicles. This report demonstartes data cleaning and preparation techniques using SAS to prepare it for statistical analysis. It uses arrays, concatenation, data type converison, outlier removal and standardization. The dataset is downloaded from https://archive.ics.uci.edu/ml/datas…

  • Updated Mar 31, 2022
  • SAS

Full production-grade, Python-based ETL workflow built for Sutter Health’s ABSMC campuses. Automates bidirectional data migration across MS Access, SQL Server, Excel, and Revit BIM using mainly pyodbc, SQLAlchemy, Pandas, Prefect, BIMLink, and pyRevit. Enables seamless facility operations, real-time BIM sync, and audit-ready reporting.

  • Updated May 20, 2026
  • Python

A modern, data warehouse–native ELT pipeline using a Medallion architecture (Bronze/Silver/Gold) in SQL Server: ingested raw data into Bronze tables, transformed and cleansed it into Silver tables using T-SQL stored procedures, and published Gold-layer reporting views (star schema and flat/wide tables).

  • Updated Feb 5, 2026
  • TSQL

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