RSM412H1 Lecture Notes - Lecture 1: Exploratory Data Analysis, Unsupervised Learning, Data Science
Document Summary
Key principles: data is a strategic asset, systematic process for knowledge extraction, sleeping with the data. Organisations need to invest in people who are passionate about data, data literate, creative: embracing uncertainty, bab principle. Data science is a tool and not a means to an end. Business-analytics-business: need to define business problem, use analytics to solve it, then integrate output. Business analytics process back into business process: define business problem. Company needs to grow customer base by targeting new segments and reducing customer churn: map to machine learning problem. Break business problem into data science problem. Reduce customer churn by x% and identify new customer segments for targeted marketing: data preparation. Source of data, quality of data, data bias. Understand data better, investigate nuances, discover hidden patterns, formulate modeling: exploratory data analysis (eda) strategies, modeling. Experiment with multiple, choose most optimal model.
