Data mining and business intelligence (BI)
DM and BI are critical components in contemporary organizational strategies, enabling firms to extract actionable insights from vast datasets. By leveraging advanced analytical techniques, businesses can identify trends, enhance decision-making processes, and gain a competitive edge. The integration of data mining with BI tools facilitates the transformation of raw data into meaningful information, promoting informed strategic planning and operational efficiency. This synergy not only optimizes resource allocation but also fosters innovation, ultimately driving growth and profitability in an increasingly data-driven marketplace.
This course discusses Business Intelligence and Data Mining as complex systems composed of many sub-systems that must be aligned to work together to produce the desired business value and support decision making.
Course Objectives:
- · Introduce data mining and business intelligence concepts, terminology and techniques.
- · Discuss the role of data mining and business intelligence in decision making.
- · Describe the characteristics, components and challenges of business intelligence and data mining.
- · Identify how various business intelligence systems can contribute to organizational success
- · Describe data mining and business intelligence tools, platforms and technologies.
Learning Outcomes:
By the end of the course, students should be able to:
- · Explain Data Mining and Business Intelligence concepts and terminology.
- · Describe the purpose and capabilities of successful Data Mining and BI and how value is actually generated within organizations.
- · Understand the role of Data Mining and BI in decision making.
- · Understand the importance of gathering a good set of requirements, requirement gathering techniques and the special challenges data mining and business intelligence efforts pose.
- · Conduct a data mining and business intelligence operations assessment.