Big Data Analyst with Statistics

Course overview

The course initially imparts statistical expertise, enabling you to recognize relationships, verify observations, and correctly classify measurement data. Subsequently, you will acquire relevant knowledge to evaluate and visualize corporate data as a Big Data Analyst. This includes understanding the requirements of data and databases, as well as data warehouse modeling and the ETL process, the Apache framework, data analysis, programming, visualization, and management in the Big Data context. Additionally, you will learn how artificial intelligence is applied in the profession. Statistics and Data Analysis Statistical fundamentals Artificial Intelligence (AI) in the work process Methods for comparing two groups Basics of regression analysis Methods for comparing means of multiple groups Introduction to experimental design (DoE, Design of Experiments) Project work in statistics Data Engineer Fundamentals of Business Intelligence, Data Engineering Requirements management for Data Engineers Artificial Intelligence (AI) in the work process Databases Data Warehouse ETL Project work for Data Engineers Data Analytics Introduction to data analysis Review of Python fundamentals Data analysis, Data Analytics Artificial Intelligence (AI) in the work process Data visualization Data management Data analysis in the Big Data context Dashboards Text Mining Project work in Data Analytics Big Data Specialist What is Big Data? Introduction to Big Data frameworks: Big Data solutions in the cloud (overview of AWS, Azure, GCP), introduction to Data Lakes and Data Warehouses, overview of Apache Hadoop and Spark Distributed data processing with Spark: Apache Spark Data pipelines and data integration: ETL and ELT processes, orchestration Components of Big Data: Apache Spark NoSQL and data storage: CAP theorem, ACID, BASE, HBase, databases Big Data visualization: BI tools (Power BI, Tableau) Data governance and data protection: GDPR, governance concepts Project work in Big Data Changes are possible; the course content is regularly updated.

Upcoming dates

• 2026-08-02T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Karlsruhe, Baden · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Aachen · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Albstadt, Württemberg · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Aschaffenburg · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-19T23:00:00.000Z · Augsburg, Bayern · Combined Learning