BUSN 655 Advanced Business Analytics Management

This graduate-level course offers an in-depth exploration of analytics and big data management, focusing on the principles, techniques, and tools used to extract valuable insights from large and complex datasets. Students will learn how to leverage advanced analytics methodologies and technologies to inform decision-making, drive innovation, and create strategic value in organizations. Through a combination of theoretical concepts, hands-on exercises, case studies, and practical applications, learners will develop the skills and knowledge necessary to navigate the rapidly evolving landscape of big data analytics.

Credits

3

Offered

Summer

Outcomes

1. Understand the fundamentals of analytics and big data: Define analytics and big data concepts and their importance in organizations. Understand the characteristics of big data, including volume, velocity, variety, and veracity.
2. Explore data collection and preprocessing: Gain knowledge of data collection methods and techniques, including structured and unstructured data sources. Understand the importance of data preprocessing, including data cleaning, integration, and transformation.
3. Learn data exploration and visualization: Develop skills in exploratory data analysis and visualization techniques. Understand how to summarize and present data visually to gain insights and communicate findings effectively.
4. Analyze and model big data: Gain proficiency in applying statistical and machine learning techniques to analyze and model big data. Understand techniques such as regression analysis, clustering, classification, and predictive modeling.
5. Understand data mining and pattern recognition: Explore data mining techniques for discovering patterns, trends, and associations in large datasets. Learn about algorithms such as association rule mining, decision trees, and neural networks.
6. Explore text and sentiment analysis: Gain knowledge of text mining and sentiment analysis techniques for analyzing unstructured text data. Understand how to extract meaningful information from text, perform sentiment analysis, and detect patterns and trends.
7. Understand data visualization and storytelling: Develop skills in creating compelling data visualizations and using storytelling techniques to communicate insights effectively. Understand the principles of effective data visualization and storytelling.
8. Learn big data management and storage: Understand the challenges and techniques of managing and storing big data. Explore technologies such as Hadoop, NoSQL databases, and distributed file systems for handling large volumes of data.
9. Explore data privacy and ethics: Understand the ethical considerations and privacy issues associated with big data analytics. Explore topics such as data anonymization, consent, and regulatory compliance.
10. Apply analytics and big data concepts in real-world scenarios: Engage in hands-on exercises, projects, and case studies to apply analytics and big data management concepts to real-world business scenarios. Develop problem-solving and critical-thinking skills in the context of analytics and big data.