About:
This was my final project for my MS in Cartography and GIS at University of Wisconsin-Madison. I
perform a lot of data quality analyses at the electric utility where I work, so I wanted to create a
framework to standardize the way data quality project information was catalogued, and create a single
database table to store a common set of attribute and spatial information for every data quality error
identified in our GIS. This single table would allow analysts to perform quick, high-level queries to
provide answers about data quality in our GIS without having to join to multiple tables and perform
time-intensive spatial queries. It would also allow us to visualize data quality errors in an AGOL dashboard.
Project Summary
Process: I used a SQL Server database, and Python scripts were written in both Python 2.7 and 3.8. I used pandas and geopandas for nearly all data analysis and manipulation, and interacted with the SQL Server database from my Python scripts using pyodbc and sqlalchemy. The ArcGIS Online Dashboard was created with Dashboards Beta.
Completed April 2021