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Data Cleaning & Outlier Removal (SPSS / Statistical Analysis)
Overview:
Performed thorough data cleaning and preprocessing on a 300-observation dataset to handle extreme outliers and normalize the distribution. By identifying and removing skewed data points, I restored statistical validity to ensure accurate population-level modeling and reliable linear regression metrics.
Key Process & Deliverables:
Outlier Detection & Removal: Screened baseline metrics to detect extreme variance and eliminate influential outliers that skewed overall population estimates.
Residual & Distribution Analysis: Evaluated standardized regression residuals using histograms and normal probability curves to confirm a bell-shaped, normal distribution ($N = 300$, $\mu \approx 0$, $\sigma \approx 1$).
Data Integrity & Reporting: Produced clean, unskewed variables ready for downstream predictive modeling, regression analysis, and executive reporting.
Outcome:
Transformed raw, heavily skewed survey/financial data into a balanced, statistically sound dataset, improving model accuracy and preventing misleading conclusions.
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🚀 My First AI Automation Project with n8n
I recently built my first automation project — an AI-Powered Invoice Extraction & Tracking System.
The problem I wanted to solve was simple:
Imagine a business receiving dozens of invoices or cash memos every week. Someone has to open each file, read the information, and manually enter the vendor name, date, items, total amount, and category into a spreadsheet.
That’s repetitive, time-consuming, and easy to get wrong.
So I built a workflow where:
📂 An invoice is uploaded to Google Drive
→ 🤖 Gemini AI reads and extracts the invoice data
→ ⚙️ n8n processes and validates the information
→ 📊 The data is automatically added to Google Sheets
The best part?
No manual data entry. Just upload the invoice and the rest happens automatically.
While building it, I also worked with things like workflow triggers, loop control, API errors/retries, and handling multiple files.
For me, this project was less about simply “building an n8n workflow” and more about learning how AI + automation + data workflows can solve real business problems.
This is just my first step into AI automation, and I’m excited to build more practical systems like this.
If your business has a repetitive process that could be automated with AI, n8n, or data workflows, feel free to DM me. I’d be happy to discuss it.
#AIAutomation #n8n #Automation #ArtificialIntelligence #DataAnalytics #DataAnalyst #WorkflowAutomation #GenerativeAI #BusinessAutomation #AI
Smart pipeline! Have you added strict JSON schema validation after Gemini extracts the invoice fields? Found that it stops edge case hallucinations before the data ever hits Sheets.
Title:
Youth Skills Training Programme — Excel M&E Dashboard
Excel-based M&E analysis project covering data cleaning, formulas, PivotTables, charts and dashboard development.
Full Description:
Analysed a simulated youth training dataset using Excel to clean, structure and interpret programme data. Built PivotTables, charts, KPI summaries and an interactive monitoring dashboard to present attendance and assessment performance.
One thing I’ve learned from working with data is that the numbers are only the beginning. The real value comes from understanding the story behind them and turning that into action.