Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.
Process Mining
Process mining is a technique designed to discover, monitor and improve real processes (i.e., not assumed processes) by extracting readily available knowledge from the event logs of information systems.
Data Strategy
Data Strategy describes a set of choices and decisions that together, chart a high-level course of action to achieve high-level goals.
Cloud Data Engineering
Cloud data engineering is the process of retrieving, cleaning, transforming, and storing data in the cloud to support the ongoing data and reporting needs of your decision makers.
Artificial Intelligence (AI)
Artificial Intelligence (AI) is the key success factor for competitiveness and helps executives and managers not just to make best business decisions, but also to execute the business with full-automation.
Trainings & Seminars
I train employees to apply the basics of Data Science, whether in purchasing, controlling, sales, production, quality or risk management! And also Executives who need to understand and apply the basics of Big Data securely.
Author Profiles
Hard Skills
Programming Languages: C#, Python
Databases: SQL Server (T-SQL) Oracle DB (PL/SQL), MySQL, PostgreSQL, snowflake, Neo4J (Cypher).
Big Data Tools: Azure Synapse, Databricks, (Apache Spark).
Data & AI: Enterprise AI, LLM, NLP, Deep Learning, BI, Cloud, Process Mining.
Business Intelligence: MS Power BI, Tableau, MicroStrategy, QlikSense & many more.
Process Mining: Event Logs, Celonis, UiPath, Signavio & many more.