Data Analytics and Storytelling

Course Description

Organizations need to gain insight into past trends, predict future behaviors, and identify opportunities that will allow them to stay ahead of their competition. Accomplishing this requires developing insights from vast stores of data. Data analytic techniques are used to collect, analyze, and interpret large datasets to find patterns, trends, and correlations in support of decision-making by management team members. This course provides a foundation in practical analytics tasks including problem definition, data collection, cleansing, manipulation, and analysis.

Once data has been analyzed and conclusions have been drawn, the results must be presented in a concise, compelling manner. Students will learn best practices for visually and verbally presenting the results of data analytics using a data storytelling framework.

Facilitator-led workshops allow students to practice the techniques as they learn. Students are encouraged to bring their own projects to class.

Learning Objectives

• Understand the strategic and operational value of data and data analytics
• Leverage data analysis to improve the decision-making process
• Define the problem to solve and form a working hypothesis
• Identify data sources and create analytical datasets
• Perform statistical analysis to test the hypothesis
• Develop a compelling visual representation to share analytical results
• Build a story around the visualization that will draw attention
• Integrate ethical considerations into the data analysis and decision-making process

Intended Audience

This course is designed for business analysts, project managers, decision-makers, systems analysts, data administrators, data scientists, database administrators, business intelligence analysts, or any other project team member practicing business analysis. This course may also be appropriate for individuals who manage or mentor business analysts or data analysts.

Prerequisites

While there are no specific course prerequisites, students should be familiar with basic concepts related to capturing, storing, and retrieving data from corporate data sources such as relational databases and spreadsheets. Students should be comfortable manipulating data and developing charts in Excel.