Business Intelligence

Lectures:
1. Introduction to BI, fundamental of BI, basic architectures and components.
2. Data warehouses. according to Inmona and Kimballa, design patterns.
3. ETL Framework, functional requirements for ETL, architectures.
4. Data govermance, master data management.
5. Data Vault, design, usage.
6. Architecture of modern data warehouse.
7. Components of Microsoft Azure and Amazon WS for data warehouses.
8. Distribution and vizualization of data in data warehouses.
9. Analytic oved data warehouses, design patterns.
10. BI modeling.
11. OLAP and MDX.
12. Introduction to DAX.
13. BI use cases, practical projects, pros and cons.
14. Management of BI projects.

Practices:
1. SSIS, introduction.
2. SSIS, data loading, basic operations in data flow.
3. SSIS, Delta management.
4. SSIS, Surrogate keys, key mapping, incremental load.
5. SSIS, ETL Framework.
6. SSIS, optimization, performance management.
7. Microsoft Azure - an infrastructure for a data-warehouse.
8. Microsoft Azure - tools for ETL.
9. Microsoft Azure - streaming data.
10. Reporting Services - introduction, implementation.
11. Power BI - model.
12. Power BI - data visualization.
13. Power BI - project management.
14. Microsoft Azure - AI, machine learning.