Exploratory Analytics Project Ideation

Overview

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

Syllabus

Specialization and Course Overview
Module 1: Overview of Exploratory Analytics

This module delves into exploratory analytics methods, including clustering, anomaly detection, and association rule mining. Students will learn how to group similar data points, identify outliers, and uncover hidden relationships within datasets, leveraging these techniques to gain deeper insights and drive data-driven decisions.

Module 2: Use Cases of Exploratory Analytics

Learn about different business contexts where exploratory analytics have been applied to generate insights from data. Practical examples in this module will reinforce theoretical concepts in exploratory analytics, preparing students to effectively apply these methods in other real-world scenarios.

Module 3: Exploratory Analytics Sprint Phase 1: Problem Identification

This module illustrates how to set up a design sprint for exploratory project ideation with team members. The process begins with brainstorming to decompose a complex business process and its needs into clear, actionable data analytics questions using Situation-Complication-Question (SCQ) analysis. These questions are then prioritized and mapped out using an issue tree to ensure a structured approach to problem-solving and to identify the most critical areas for data-driven insights.

Module 4: Exploratory Analytics Sprint Phase 2: Solutions Mapping

In the next step of the design sprint for exploratory project ideation, teams identify desired project outcomes by creating mockups to visualize potential solutions. They then construct a solution approach to map these outcomes to the initial questions by selecting the appropriate exploratory analytics methods and available data, ensuring a structured and data-driven path to achieve the project goals.