Exploratory analytics is where data meets discovery, revealing hidden patterns and turning raw information into breakthrough insights. In this course we will first provide an overview of exploratory analytics methods such as clustering, association rule mining, anomaly detection, and study their business use cases. We will then consider a case study to learn how to use a design sprint framework to ideate about exploratory analytics project plan. Learning objectives: - Analyze how exploratory analytics concepts can be used to solve business problems - Construct an issue tree for an exploratory analytics project - Select a solution approach and define an exploratory analytics project
Creating Mock-ups for Dashboards - Internal
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Skills You'll Learn
Analytics, Process Mapping, Data Analysis, Exploratory Data Analysis, Tree Maps, Data Mining, Project Design, Business Analysis, Business Analytics, Ideation, Anomaly Detection, Unsupervised Learning
From the lesson
Module 4: Exploratory Analytics Sprint Phase 2: Solutions Mapping
Taught By
Soumya Sen
Associate Professor