WARSAW · BUSINESS ANALYST · PROCESS & DATA

Onur Usalan

Business Analysis · Process Improvement · Data Analytics · Business Strategy

I translate business needs into structured requirements, measurable insights and practical next steps. My case studies show the full path—from defining the question to validating the evidence behind a recommendation.

Warsaw, Poland

SGH

Master’s student in International Business at SGH Warsaw School of Economics

A project decisionE-commerce
01 / 05

Question

What can sales and cancellations tell us?

Professional snapshot

Business thinking, backed by evidence.

Open to
Business Analyst
Junior Business Systems Analyst
Data Analyst
Evidence
Operational reporting internship · Two end-to-end case studies · International Business at SGH
Core areas
Business analysisProcess improvementData analyticsKPI reportingUAT & traceability

How I contribute

One connected approach—from need to decision.

I connect business analysis, process improvement, data analytics and business strategy so that every recommendation has a clear purpose and a defensible evidence trail.

Business Analyst

Translate stakeholder needs into well-defined problems, actionable requirements, user stories and acceptance criteria that keep business and technical teams aligned.

Business Analysis

Structure ambiguous challenges through stakeholder analysis, current-state assessment, gap analysis and traceable documentation—from the initial question to a validated solution.

Process Improvement

Map workflows, identify bottlenecks and control gaps, and define measurable future-state improvements that reduce friction and support reliable delivery.

Data Analytics

Use SQL, Python, Excel and Tableau to clean and model data, define trustworthy KPIs and turn operational evidence into clear management reporting.

Business Strategy

Connect market context, operational performance and analytical evidence to prioritised recommendations, transparent trade-offs and decision-ready next steps.

Selected case studies

Analysis you can inspect, not just read about.

Two end-to-end cases show how I frame a business question, govern the measures, test the result and communicate a responsible recommendation.

Define a defensible comparison

EU Digital Procurement Competition Monitor

Independent end-to-end case study · Public data · Documented stakeholder scenarios

Competition and supplier-concentration decision view. Verified project output generated from official TED result notices.
Executive dashboardVerified repository output

The business question

How can public-procurement teams screen digital procurement results for competition patterns while retaining a traceable, reproducible evidence trail?

My contribution

I documented requirements, defined the evidence cohort and KPI rules, and connected the analysis to data checks, UAT and reporting outputs.

Keep the denominator visible

The single-bid rate uses the 27,100 notices with competition evidence, not all 38,971 notices. Keeping that boundary visible prevents missing evidence from being treated as a competitive outcome. The result is a screening signal for further investigation, not a finding of misconduct.

Review the KPI definition, evidence cohort and validation checks.

Dataset scale: 38,971 EU-27 digital result notices analysed

Reconcile KPIs and reporting

E-Commerce Sales, Cancellations & Customer Value Decision System

Independent end-to-end case study · Public data · Documented stakeholder scenarios

Sales, cancellations and customer value. Verified dashboard output generated from UCI Online Retail II.
Executive dashboardVerified repository output

The business question

Where should an e-commerce leadership team focus first to protect sales value, reduce cancellation exposure and retain valuable customers?

My contribution

I documented business requirements and KPI rules, built the SQL model and dashboard, and linked requirements to UAT checks and output evidence.

Keep sales separate from profit

The source contains transactions but no cost or cancellation-reason fields. I report sales and cancellations separately without presenting net sales as profit. Assessing profitability or explaining why orders were cancelled would require additional data.

Follow a requirement through the KPI definition, SQL output and UAT check.

Dataset scale: 1,067,371 transaction lines

All case studies

Experience proof

Operational DataAnalysisVisualisationManagement Reporting

July 2024 — August 2024Ankara, Turkey

Operational data analysis and management reporting

Etisan Proje A.Ş.

Software Unit Intern
  • Cleaned, preprocessed and structured operational datasets using SQL and Python/pandas.
  • Built Tableau dashboards with country-to-institution drill-down reporting.
  • Delivered stakeholder-focused analytical reports and dashboards reviewed by management.

OutputClean analytical datasets, Tableau dashboards and stakeholder-focused management reports.

Review experience in context

Working principles

Clarity before complexity.

Based in Warsaw and studying International Business at SGH, I combine a management perspective with practical experience in SQL, Python, Tableau and business analysis documentation.

I make the decision, definitions and limitations explicit. If the available evidence cannot support a conclusion, I show what is missing and define the next question—because credible analysis is as much about boundaries as it is about results.

Read my profile

Professional contact

Let’s turn the next business question into a clear decision.

I am open to Business Analyst, Junior Business Systems Analyst and data-focused opportunities in Warsaw, across Poland and within international teams.

Location
Warsaw, Poland