Database Programming & Data Analysis for Businesses

Many business processes start out as a simple spreadsheet or Access file. Once several people work at the same time, thousands of rows accumulate or links between customers, orders, items and hours are needed, spreadsheets break down: files lock up, formulas get overwritten and nobody knows which version is current.

A properly engineered SQL database (such as PostgreSQL or SQL Server) solves this permanently. Data is stored once without contradictions, validation rules prevent typos on entry, and every team member works on the same live dataset through a clean web interface or API.

During the transition nothing has to be retyped by hand: I write Python and SQL migration scripts that read your existing Excel files, CSV exports or Access tables, standardise formats, merge duplicates and load everything cleanly into the new database.

Many companies sit on valuable data from sales, purchasing, time tracking or operations, but rarely use it because manual analysis in Excel takes hours. With Python and libraries such as Pandas and Polars, hundreds of thousands of rows can be filtered, joined and evaluated in seconds.

Instead of copying numbers together every Monday morning, I set up automated analytics pipelines: a script pulls the latest data from your database or APIs, calculates margins, trends, utilisation or outliers, and delivers a clean HTML/PDF report by email or updates a protected web dashboard.

Complex business questions become easy to answer: which customer segments or products are truly profitable after all costs? Where do bottlenecks occur in order fulfilment? Every metric is transparently derived and reproducible at any time.

Sometimes a database is already in place, but queries take minutes, reports slow down operations or separate tools don't talk to each other. A targeted look under the hood – adding missing indexes, rewriting slow SQL joins and normalising tables – often speeds up queries dramatically without replacing your whole system.

If your company uses several disconnected systems – such as industry software, an online shop, time tracking and accounting – I connect them via reliable ETL pipelines (Extract, Transform, Load) that fetch, validate and sync records automatically.

Backed by five years at Siemens AG working with data monitoring (ELK stack) and Python automation, plus a Top 1% global ranking in Python on CodinGame, every database and pipeline is built for stability, clear error logging and easy maintenance.

Sensitive business, customer and financial data does not belong in opaque third-party cloud tools. I deploy all databases, analytics scripts and dashboards directly on your own server, in your existing cloud or in a certified German data centre.

A clean database also lays the foundation for custom web apps or local AI/RAG systems: once your data is structured in PostgreSQL (including pgvector), a local AI assistant can search records and documents in seconds.

Upon completion you own the entire database schema, all SQL and Python scripts and the technical documentation – with zero per-seat licence fees and no vendor lock-in.