Business Intelligence — Economic Analysis of Brăila County (2020–2023)
University project, Business Information Systems, Babeș-Bolyai University
What is this?
This project analyzes the financial performance of companies in Brăila County, Romania, over a four-year period that spans both the pandemic downturn (2020–2021) and the post-COVID recovery (2022–2023). The goal was to answer a few concrete business questions: which sectors were most profitable after the pandemic, which companies kept their profitability stable across all four years, and how economic activity is distributed geographically within the county.
Data
All data is public, pulled from data.gov.ro: annual financial statements from the Ministry of Public Finance (revenue, net profit/loss, assets, liabilities, employee counts) and company registry data from the National Trade Register Office (CUI, name, location). Four years of separate files per category, unioned and joined into one dataset.
Data preparation (Tableau Prep)
Cleaning and combining three years' worth of separate government files took the bulk of the actual work:
Unioned three parallel file types (balance sheets, extended balance sheets, and profitability indicators) across 2020–2023 using wildcard union Renamed and typed fields consistently (CUI and CAEN codes kept as strings, since they're identifiers, not numbers to calculate on) Handled missing values differently depending on the field: employee counts with heavy missingness were set to 0 (treated as no reported staff), while other financial fields were filled in with the column median Removed invalid negative values from fields where negatives don't make sense (revenue, fixed/current assets, liabilities), while deliberately keeping negative equity as valid (a company can legitimately have negative capital from accumulated losses) Detected and removed outliers using the IQR method, applied twice: once after unioning the financial data, and again after joining it with the company registry (the join reduced the dataset to 592 matching companies and surfaced a new set of extreme values)
Analysis (Tableau Desktop)
Built calculated fields for profit margin and profitability classification, then explored the data through several chart types: a bar chart ranking localities by net profit, a treemap showing revenue share by industry code, a packed bubble chart for profit margin per company, a side-by-side comparison of fixed vs. current assets by sector, and a highlighted table tracking debt by locality over time. Added a two-layer map (county polygon plus per-locality profit markers, some geocoded manually since Tableau couldn't resolve all the smaller localities automatically) and a trend line following net profit for five representative localities across the four years.
Everything comes together in an interactive dashboard with cross-filtering between the map, treemap, and bubble chart, and a guided Story that walks through the findings step by step.
What came out of it
Brăila municipality dominates the county's economic activity, both in profit and in debt Freight transport (CAEN 4941) and general food retail (CAEN 4711) are the two sectors with the biggest local impact Profitability clearly recovered after 2021, tracking the broader post-pandemic rebound Debt has been rising steadily, which could point to increased reliance on credit worth keeping an eye on