By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story.
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Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for c-suite professionals, directors and senior-level managers who want to develop a data-driven mindset. Learners should have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the second course in the Data-Driven Decision Making (DDDM) specialization.
Continuing education units (CEUs) and professional development hours (PDHs) are available through the UB Center for Industrial Effectiveness (UB TCIE) for learners who earn a course certificate.
What You Will Learn
- Identify stakeholders and key components imperative to an analytics project plan
- Name strengths and weaknesses of different analysis and visualization tools
- Visually identify, monitor, and remove process variation
- Explain how to create a compelling data story
Course 2 of 3 in the Data-Driven Decision Making (DDDM) Specialization
Syllabus
WEEK 1
Data Analysis Software Tools
This module provides an overview of the tools needed for data analysis.
WEEK 2
Statistical Process Control (SPC)
This module covers SPC, a way to analyze variation over time in your process using data. It is helpful in identifying current problems and can also be used to monitor the process for any deviations once the process is ‘in control'.
WEEK 3
Data Visualization and Translation
This module provides tools for leveraging data through visualization and translation.
WEEK 4
Project: Data Analysis and Visualization
This module provides an opportunity to bridge theory and practice. Learners apply knowledge from this course to solve a business problem.
