Business Intelligence and Statistical Modeling Your analysis should take on a 3-paragraph format; Define, explain in detail, then present an actual example via research. Your paper must provide in-depth analysis of all the topics presented:
Understand the nature of data as it relates to business intelligence (BI) and analytics Learn the methods used to make real-world data analytics ready
Describe statistical modeling and its relationship to business analytics
Learn about descriptive and inferential statistics
Define business reporting, and understand its historical evolution
Understand the importance of data/information visualization
Learn different types of visualization techniques
Appreciate the value that visual analytics brings to business analytics
Know the capabilities and limitations of dashboards
Understand the basic definitions and concepts of data warehousing
Understand data warehousing architectures
Describe the processes used in developing and managing data warehouses
Explain data warehousing operations
Explain the role of data warehouses in decision support
Explain data integration and the extraction, transformation, and load (ETL) processes
Understand the essence of business performance management (BPM)
Learn balanced scorecard and Six Sigma as performance measurement systems
