ETLens – Bringing Your Data Into Focus

Bringing your data into focus – I transform complex information into a clear picture that supports fast and accurate decisions. I integrate data into a coherent ecosystem, reducing reporting time. Focus on what's really important.

Azure · Power BI · DAX · Python · PowerQuery · ETL · Web Apps · Data Automation · Data Flow · Analytics

About me

💡 Are you looking for a partner who not only understands data , but can translate it into concrete business decisions?

Since 2018, I've been helping organizations better leverage their data. I specialize in BI Consulting and ETL process design in Azure and Python. Combining my technical and business expertise, I help companies automate reporting, integrate various data sources, and reduce the risk of errors.

My approach is simple: before creating code or a dashboard in Power BI,I first understand the business context and real needs. This ensures that the solutions I implement not only work technically but also actually increase the organization's efficiency.

What I offer:

  • BI Consulting – consulting on data architecture, tool selection, and Business Intelligence best practices.
  • BI Implementation – ETL process implementations, data integrations, and report and dashboard design in Power BI.
  • Ad-Hoc BI – quick analyses, additional reports, and support in solving current data challenges.

🚀 Do you want to improve data flow and reporting in your company? Let's talk and see how I can help you with this.

Key competencies

  • Python & ETL: automation of data processes, construction of pipelines, and preparation of data for analysis and reporting.
  • Azure Data Platform: designing cloud data architecture, orchestrating and monitoring pipelines, ensuring security and performance.
  • System Integration: combining ERP, SharePoint, files, and APIs into one coherent data system, with quality and consistency control.
  • Reporting & Analytics: designing data models and KPIs, creating transparent dashboards in Power BI, and implementing BI best practices.

Stack & Integrations

Python and Libraries
Python pandas NumPy SQLAlchemy
Microsoft Azure
Data Factory Azure SQL Virtual Machines Automation App Service Logic Apps
Power Platform and Office 365
Power BI Power Query Excel PowerPivot Power Automate
Integrations and Data Sources
SAP GUI / VBS SharePoint OneDrive REST API CSV/Excel

Social Media

Offer

BI Consulting

Data and BI Strategy: Needs Diagnosis, Target Architecture, and Action Plan Tailored to Your Organization.

Audit & Roadmap Governance & KPI Azure Architecture
  • • ETL/BI Process Assessment and Bottleneck Identification
  • • Data Architecture (Azure, Integrations, Security, Costs)
  • • Data model and KPI standards, BI best practices
  • • Implementation Roadmap: Priorities, Estimates, Quick Wins

Case: audit of 50+ sales files → roadmap → consistent model and faster reporting.

time: 1–2 weeks mode: workshop + remote
Schedule a consultation →

BI Implementation

End-to-end implementations: from ETL pipelines in Azure to ready-made dashboardsPower BI and refresh automation.

ADF / Automation Azure SQL Power BI / DAX
  • • ETL in Azure: Data Factory / Automation, Orchestration and Logging
  • • Integrations: SAP, SharePoint/OneDrive, REST API, files
  • • Data Model + Reports: Power BI, DAX, Performance Optimization
  • • Automated Refreshing and Monitoring (App Insights)

Automated refresh and monitoring (App Insights)""Case: SAP + files → Azure SQL → Power BI; report time reduced from 6 hours to 10 minutes.

time: 2–6 weeks mode: sprints + CI/CD
Order implementation →

Ad-Hoc BI

Fast, immediate support: analyses, data corrections, one-time reportsand lightweight file/API integrations.

Rapid Report Data Cleanup Light Integration
  • • One-off reports and dashboards, proof-of-concepts
  • • Data cleaning, column mapping, quality validation
  • • Combining Multiple Sources into a Lightweight Analytical Model
  • • Fast File/API Integrations and Task Automation

Case: one-time KPI dashboard + automatic CSV/Excel export for management every Monday at 8:00.

time: 1–5 days mode: quick POC
Report an ad-hoc topic →

How I work - process for selected offer

Step 1

Discovery & Business Goals

45–60 min workshop: pain, KPIs, constraints (time/cost/compliance).

Step 2

As-Is: Sources and Processes

Overview of SAP/SharePoint/DB, roles, and workflows; identification of bottlenecks and risks.

Step 3

To-Be: architecture & governance

Target architecture in Azure, data model, KPI standards, security and costs.

Step 4

Roadmap & quick wins

Implementation plan with priorities and estimates; quick win/POC list.

time: 1–2 weeks mode: workshop + remote

Result: audit report + implementation roadmap (in stages).

Live Samples

Currency ETL – daily exchange rate updates (ECB) + dashboard

A daily pipeline retrieves data from the European Central Bank, adds a new day to the local history, and publishes a static dashboard (Plotly) on GitHub Pages. The project demonstrates the end-to-end process: download → validation → transformation → publication.

Python GitHub Actions Plotly GitHub Pages
  • • Data: eurofxref-daily.xml + backfill 90 days (ECB)
  • • Automation: GitHub Actions (cron, publish to Pages)
  • • Result: online dashboard + CSV files with course history
How does it work in a nutshell?
  1. One-time 90-day backfill feeds history (CSV).
  2. The daily run appends the current day from `eurofxref-daily.xml`.
  3. The script converts rates → PLN (EUR/PLN directly, USD/PLN = PLN/USD etc.).
  4. We generate `index.html` (Plotly) and publish it to GitHub Pages.

Live demo: refreshed every morning (cron in GitHub Actions).

Northwind ETL – OData → PostgreSQL (Neon) + BI Integration

The pipeline retrieves data from the Northwind sample database (OData V4), loads it into a PostgreSQL database in Neon, and prepares it for analysis in BI tools (Power BI, Looker Studio). The project demonstrates the end-to-end process: download → transformation → loading → visualization.

Python OData API PostgreSQL (Neon) SQLAlchemy Power BI
  • • Data: Northwind OData (Products, Orders, Customers, Employees, Supplierse.t.c.)
  • • Automation: ETL in Python + SQLAlchemy → Neon PostgreSQL
  • • Result: SQL tables ready to be connected in Power BI / Looker Studio
How does it work in a nutshell?
  1. The script retrieves data from OData (pagination + column selection).
  2. Transformation: type conversion (e.g. date, number), field clearing.
  3. Loading: Writing DataFrame → PostgreSQL (Neon) using SQLAlchemy.
  4. Analysis: Power BI / Looker Studio connects to tables and visualizes data.

Live demo: Power BI report powered by Northwind data from PostgreSQL(Neon).

Coming soon: more samples

More demo projects will be coming soon, such as ETL with API for DuckDB + dashboard, data quality alerts, and mini-projects for SMB.

Contact

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