Tools for Exploratory Data Analysis in Business
University of Illinois at Urbana-Champaign via Coursera
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Overview
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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 PowerBI, Alteryx, and RStudio 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 PowerBI
- PowerBI is great for both data assembly and visualization. In this module we will use PowerBI to prepare the Teca data for analysis, and then visually explore that data with various charts.
- Module 3: ETL and EDA Using RStudio
- Using R in RStudio to load, transform, clean, and explore data
- Module 4: ETL and EDA Using Alteryx
- Alteryx is great for visually documenting the data analytic workflow. In this module we will use Alteryx to assemble the Teca data and explore it with plots and tables.
Taught by
Jessen Hobson and Ronald Guymon