DEI Survey Data Analysis

I was hired by Health Justice, a consulting firm, to help analyze data from equity surveys within a large organization.   

Although the stats and graphs for this project were simple, the complexity of datasets and the volume of deliverables offered some challenges:

The dataset contained hundreds of columns with different data types and formats. I leveraged R programming and the 'dplyr' package to programmatically clean, format, segment, and summarize the data.

Due to the sheer volume of deliverables, it was impractical to adjust figures and tables individually. I addressed this by setting up an automated pipeline, which included the creation of graphs and tables (using the 'ggplot2' and 'flextable' packages) and report compilation (using the 'officer' package).

Hundreds of graphs and tables, with different levels of stratification, delivered in different formats (.png, .html or within a report).

Data validation, including the detection of invalid response patterns.

Exploratory analyses, including total and partial survey completion patterns and analysis of metadata.