Tools for Exploratory Data Analysis in Business

Overview

This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using Python to conduct the ETL and EDA processes. The learning outcomes for this course include: 1. Development of an analytic mindset for approaching business problems. 2. The ability to appraise the value of datasets for addressing business problems using summary statistics and data visualizations. 3. The ability to competently operate business analytic software applications for exploratory data analysis.

Syllabus

Course Orientation and Module 1: Analytics Mindset

Your mind is the most important tool. Prepare your mind by learning about various mindsets and terms for approaching business analytic problems.

Module 2: ETL and EDA Using Python

Python is a powerful tool for working with data. In this module, we will use Python to extract, transform, and load data, generate summary statistics and visualizations for exploration, and understand the value of performing data analysis directly within Python.

Module 3: ETL and EDA Using SQL

In this module, we will explore how data quality impacts business analytics, examine the relationship between data transformation and managerial decision-making, and develop foundational skills in data manipulation using dplyr, tidyr, and stringr to prepare data for visualization.

Module 4: ETL and EDA Using APIs

In this module, we will learn to execute effective data visualizations using Dona Wong’s framework, craft emotionally resonant and visually clear charts, and apply advanced techniques to enhance the clarity, sophistication, and storytelling power of our data visuals.