Busi­ness Data Pro­cessing and Busi­ness In­tel­li­gence

Course content

Data-driven decision making is a core component of modern business practice. As a result, it is increasingly important for business students to understand the end-to-end process of business data analytics.
This course provides foundational knowledge of the major stages of business data analytics, including data collection, storage, transformation, processing, modeling, and reporting. Students gain hands-on experience with real datasets and learn the complete analysis lifecycle through practical examples. Topics include:
 

APIs in Business and AI Ecosystems: How APIs enable data access, integration, and sharing across business systems, open web services, and AI-enabled applications, including emerging integration patterns such as MCP.
Data Formats: Overview of common data formats used for digital data exchange.
Data Storage Models: High-level understanding of storage approaches for operational and analytical relational databases.
Structured Query Language (SQL): Using SQL for querying, aggregating, and filtering data, and as a quick reporting tool.
Data Warehouse Concepts: Introduction to data warehouse architectures and schema designs.

Tools: Tableau or Power BI for reporting; PostgreSQL for relational databases and SQL; and a scripting language or visual tool for interacting with Web APIs.