Business Intelligence (BI) is information management and analysis for the enterprise. It includes data capture and management of the data warehouse but is most often associated with data analysis, insights gathering and reporting. BI uses data mining technologies, tools and techniques to transform raw data from multiple internal and external sources into actionable metrics that can be used in operations, planning, product development, strategic management and other divisions of a company.
1 Identify the major frameworks of computerized decision support: decision support systems (DSS), data analytics and business intelligence (BI).
2 Explain the foundations, definitions, and capabilities of DSS, data analytics and BI.
3 List the definitions, concepts, and architectures of data warehousing.
4 Demonstrate the impact of business reporting, information visualization, and dashboards.
5 Explain data mining, neural networks, support vector machines, text analytics, text mining, sentiment analysis, web mining, web analytics, social analytics, social network analysis.
6 Outline the definitions, concepts, and enabling technologies of big data analytics.
7 Apply big data technologies in business intelligence using geospatial data, location-based analytics, social networking, Web 2.0, reality mining, and cloud computing.
8 Identify the major ethical and legal issues of analytics.
9 Describe how analytics are powering consumer applications and creating a new opportunity for entrepreneurship for analytics.
10 Effectively communicate course work in writing and oral presentation.
Decision Making and Decision Support Systems
Business Intelligence Concepts and Platform Capabilities
Data Visualization and Dashboard Design
Business Performance Management Systems
BI Maturity, Strategy, and Summative Project