The project involved consolidating and standardizing messy expense data from a real estate company. Each month’s expenses were stored in separate sheets with multiple blocks in varying structures and inconsistent headers, making analysis challenging.
The data contains Monthly Expenses data from January to December 2025.
The main objective was to clean, standardize and merge all monthly expenses into a single, unified database for easier reporting and analysis.
Data cleaning, data transformation, Excel tables, Power Query and database consolidation.
Automate monthly data preprocessing to further reduce manual work and ensure consistent updates to the master database.
All monthly expense data was successfully cleaned, standardized and consolidated into a single, unified database. This streamlined workflow not only made the data easier to analyze but also ensured consistency and accuracy across all records. The project reinforced the importance of data cleaning, standardization, and the use of Power Query in handling complex, multi-source datasets.
N.B: Due to confidentiality agreements, I cannot share the company’s actual expense data. The portfolio only includes a single workflow diagram created in PowerPoint to illustrate the process I followed to clean, standardize, and consolidate the data.