Data Analysis and Visualization
Data Analysis and Visualization
This course is part of Data-Driven Decision Making (DDDM) Specialization
Instructors: Peter Baumgartner
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What you'll 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
Skills you'll gain
- Statistical Process Controls
- Data Analysis Software
- Business Analytics
- Data Quality
- Process Analysis
- Business Planning
- Data Visualization Software
- Variance Analysis
- Statistical Analysis
- Data Cleansing
- Action Oriented
- Process Capability
- Data-Driven Decision-Making
- Data Storytelling
- Data Presentation
- Tableau Software
- Data Analysis
Tools you'll learn
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There are 4 modules in this course
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.
Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners 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. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=Oi4mmeSWcVc&list=PLQvThJe-IglyYljMrdqwfsDzk56ncfoLx&index=11.
This module provides an overview of the tools needed for data analysis.
What's included
6 videos6 readings1 assignment
6 videos•Total 24 minutes
- Introduction to Data Analysis and Visualization•1 minute
- Context, Objectives, and Analysis Plans•4 minutes
- Excel, R, MINITAB, MATLAB, and Python•7 minutes
- Techniques and Best Practices•6 minutes
- Dan Gerena Discusses Maximizing the Value of Data•3 minutes
- Introduction to Visualization•3 minutes
6 readings•Total 127 minutes
- Welcome Message and Course Overview•5 minutes
- Acknowledgements•2 minutes
- Context, Objectives, and Analysis Plans Resources (Optional)•40 minutes
- Data Analysis Tools Resources (Optional)•30 minutes
- Techniques and Best Practices Resources (Optional)•30 minutes
- Introduction to Visualization Resources (Optional)•20 minutes
1 assignment•Total 30 minutes
- Data Analysis Software Tools•30 minutes
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'.
What's included
5 videos5 readings1 assignment
5 videos•Total 17 minutes
- Objectives•3 minutes
- Variation Sources•2 minutes
- Control and Specification Limits•5 minutes
- Variation Analysis•4 minutes
- Process Performance•3 minutes
5 readings•Total 110 minutes
- Objectives (Optional)•10 minutes
- Variation Sources (Optional)•20 minutes
- Control and Specification Limits (Optional)•40 minutes
- Variation Analysis (Optional)•20 minutes
- Process Performance (Optional)•20 minutes
1 assignment•Total 30 minutes
- Statistical Process Control (SPC)•30 minutes
This module provides tools for leveraging data through visualization and translation.
What's included
7 videos5 readings1 assignment
7 videos•Total 36 minutes
- Guiding Principles•8 minutes
- Data Story•7 minutes
- Tableau, Excel, and Power BI•7 minutes
- Dan Gerena Discusses Data Visualization•3 minutes
- Insight Evaluation•4 minutes
- Testing and Re-Evaluation•3 minutes
- Dan Gerena Discusses Sustaining a Data-Driven Strategy•4 minutes
5 readings•Total 150 minutes
- Guiding Principles Resources (Optional)•30 minutes
- Data Story Resources (Optional)•30 minutes
- Visualization Tools Resources (Optional)•40 minutes
- Insight Evaluation Resources (Optional)•30 minutes
- Testing and Re-Evaluation Resources (Optional)•20 minutes
1 assignment•Total 30 minutes
- Data Visualization and Translation •30 minutes
This module provides an opportunity to bridge theory and practice. Learners apply knowledge from this course to solve a business problem.
What's included
1 video1 reading1 peer review1 discussion prompt
1 video•Total 1 minute
- Project: Data Analysis and Visualization•1 minute
1 reading•Total 60 minutes
- Project: Data Analysis and Visualization (REQUIRED)•60 minutes
1 peer review•Total 60 minutes
- Data Analysis and Visualization•60 minutes
1 discussion prompt•Total 10 minutes
- Opportunity for Reflection •10 minutes
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Reviewed on Sep 11, 2022
VCe cours a ete tres important pour moi, car j'ai pu aprendre d'excellentes tectniques liees a l'analyse et visualisation de donnees, aisnique a la conception de plan d'action de projet.
Reviewed on Apr 24, 2025
The graded assignments should be more related to the content. This course was on visualization, but the assignment was not fully related to the modules.
Reviewed on Jun 12, 2022
Awesome feeling! I am grateful Coursera. Thank you enoumously.
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