BI and reporting
KPI design, dashboards, management reports, and analysis of sales, campaigns, and acquisition channels.
Business Intelligence · Data Engineering · Data Governance
Data that supports better decisions
I design and organize data processes: from source systems and ETL/ELT pipelines to models, KPIs, reports, and practical data standards.
About
Analytics that works in practice
I work at the intersection of Business Intelligence, Data Engineering, and Data Governance. I help organizations move from scattered sources and manual reporting to a structured data layer, clear KPI definitions, and reporting that supports real decisions.
My experience includes analytics modernization, migrations, reporting automation, data standards, and cooperation with teams that rely on operational and management data every day.
- BI and analytics for sales, campaigns, and user behavior
- Data Engineering: Python, SQL, orchestration, and automation
- Data Governance: metric definitions, dictionaries, and standards
- Excel and data analysis training delivered as practical workshops
Specializations
Areas where I most often help
Every project starts with the decisions the data needs to support. Architecture, tools, and delivery model come next.
Data Engineering
ETL/ELT pipelines, automation, data models, quality checks, and source integrations using SQL and Python.
Data Governance
Metric definitions, data dictionaries, ownership standards, and a clear conceptual layer for data work.
Process
From diagnosis to team adoption
Diagnosis
I clarify goals, audiences, business decisions, and current issues with data quality and availability.
Architecture
I design sources, flows, the data model, KPI definitions, and the way results will be validated.
Delivery
I work iteratively: small releases, fast feedback, stabilization, and quality control.
Adoption
I prepare documentation, training, and handover so the solution continues to work after implementation.
Training
Excel and data analysis workshops
I run practical workshops based on realistic datasets and business scenarios. The goal is practical independence, not just knowledge of features.
- Excel: pivot tables, formulas, data cleaning, and workflow automation
- Data analysis: metric thinking, data quality, and basic modeling
- Materials: exercises, datasets, checklists, and short instructions for use after the workshop
Contact
Let’s discuss data in your organization
The fastest way to reach me is through LinkedIn. Send a short note about the data, reports, or processes your team works with.