Business intelligence and statistical modeling

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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

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