Data & Process Analysis · Power BI · Microsoft Fabric · SQL · Python · Hamburg
I am training as a Fachinformatiker für Daten- und Prozessanalyse (IHK, expected completion 06/2027) and building a practical portfolio around Data/BI, process analytics, Power BI, Microsoft Fabric, SQL and Python.
My focus is on turning business processes into clear data models, dashboards, KPIs and actionable insights.
My background combines communications, PR and media work, academic experience in German and American Studies as well as Journalism, Media and Communication Studies, and experience in international business contexts.
This helps me approach data work not only technically, but also from a business, documentation and stakeholder perspective.
Today, I am building a practical Data/BI profile with a strong focus on the Microsoft Data Stack, SQL, Python and process-oriented analytics.
| Area | Current Focus |
|---|---|
| Data & BI | Power BI, reporting, KPIs, dashboards |
| Data Modelling | SQL, relational databases, clean data structures |
| Analytics | Python, data cleaning, automation, analysis |
| Microsoft Stack | Power BI, Microsoft Fabric, Azure fundamentals |
| Infrastructure | Linux basics, Cisco networking fundamentals, switching, VLANs, secure remote access documentation |
| Business Context | Process analysis, documentation, stakeholder communication |
I focus on reproducible, documented Data/BI workflows:
- Clear business questions
- Documented data sources
- Simple and explainable data models
- Validation checks before interpretation
- Readable SQL and Python
- Stakeholder-oriented summaries
- Responsible use of AI-assisted tools
Power BI · Microsoft Fabric · SQL · Excel · Data Modelling · KPIs · Reporting
Python · pandas · NumPy · matplotlib · Java basics · C/C++ basics
Microsoft SQL Server · SQL Server in Docker · MySQL · MariaDB · Relational data modelling
Git · GitHub · VS Code · PyCharm · IntelliJ IDEA · DataGrip · DataSpell · CLion
Microsoft Azure fundamentals · Docker Desktop · Linux basics · Cisco switching fundamentals · Tailscale remote access lab
- A practical Data/BI portfolio focused on Power BI, Microsoft Fabric, SQL and Python
- Small, reproducible learning repositories for core development workflows
- A Hamburg-based exploratory data analysis project: hamburg-district-data-basics
- A documented remote-access lab using Tailscale across Windows, macOS and iOS devices: remote-access-network-lab
- A documented Cisco switching lab for CCNA-level fundamentals: cisco-switching-lab
- A static portfolio website for datatidehh.de
| Repository | Focus |
|---|---|
| hamburg-district-data-basics | Initial Hamburg district profile data analysis using Python, pandas and public city data |
| python-data-basics | Python 3.12 data environment with pandas, NumPy, matplotlib and scikit-learn |
| sql-server-docker-basics | Microsoft SQL Server 2022 Docker learning project using DataGrip, SQL scripts and DPA-style training data |
| remote-access-network-lab | Documented Tailscale-based remote access lab connecting Windows, macOS and iOS devices, including SSH over a private Tailnet |
| cisco-switching-lab | Documented Cisco switching lab using Catalyst switches for VLANs, trunks, STP and basic Layer 3 concepts |
| java-basics | Java 21 learning project with IntelliJ IDEA, Eclipse Temurin and a small IPv4 subnet calculator |
| cpp-basics | C++20 learning project with CLion, CMake, Ninja and a small IPv4 subnet calculator |
These repositories document small, practical setup and learning projects. They are intentionally simple and focus on clean tooling, reproducible environments and basic development workflows.
I am building projects that demonstrate practical Data/BI skills:
- Power BI dashboards with clean data models and business KPIs
- Documented learning paths in Data/BI and IT fundamentals
- Hands-on portfolio development with GitHub, SQL, Python and Power BI
- Clear focus on Microsoft Data Stack and Hamburg-based opportunities
- Additional practical exposure to networking, Linux basics, Cisco switching and secure remote-access documentation
- Website: datatidehh.de
- LinkedIn: linkedin.com/in/datatidehh
- Kaggle: kaggle.com/DataTideHH
- GitHub: github.com/DataTideHH
