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Data Analysis and Visualization
  • Level Foundation
  • Duration 11 hours
  • Course by University at Buffalo
  • Offered by

About

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.

Modules

Introduction and Acknowledgements

    • 1 Videos
    • 2 Readings
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1 Videos

  • Introduction to Data Analysis and Visualization

2 Readings

  • Welcome Message and Course Overview
  • Acknowledgements

Context, Objectives, and Analysis Plans

    • 1 Videos
    • 1 Readings
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1 Videos

  • Context, Objectives, and Analysis Plans

1 Readings

  • Context, Objectives, and Analysis Plans Resources (Optional)

Excel, R, MINITAB, MATLAB, and Python

    • 1 Videos
    • 1 Readings
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1 Videos

  • Excel, R, MINITAB, MATLAB, and Python

1 Readings

  • Data Analysis Tools Resources (Optional)

Techniques and Best Practices

    • 2 Videos
    • 1 Readings
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2 Videos

  • Techniques and Best Practices
  • Dan Gerena Discusses Maximizing the Value of Data

1 Readings

  • Techniques and Best Practices Resources (Optional)

Introduction to Visualization

    • 1 Videos
    • 1 Readings
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1 Videos

  • Introduction to Visualization

1 Readings

  • Introduction to Visualization Resources (Optional)

Data Analysis Software Tools Assessment

    • 1 Assignment
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1 Assignment

  • Data Analysis Software Tools

Objectives

    • 1 Videos
    • 1 Readings
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1 Videos

  • Objectives

1 Readings

  • Objectives (Optional)

Variation Sources

    • 1 Videos
    • 1 Readings
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1 Videos

  • Variation Sources

1 Readings

  • Variation Sources (Optional)

Control and Specification Limits

    • 1 Videos
    • 1 Readings
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1 Videos

  • Control and Specification Limits

1 Readings

  • Control and Specification Limits (Optional)

Variation Analysis

    • 1 Videos
    • 1 Readings
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1 Videos

  • Variation Analysis

1 Readings

  • Variation Analysis (Optional)

Process Performance

    • 1 Videos
    • 1 Readings
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1 Videos

  • Process Performance

1 Readings

  • Process Performance (Optional)

Statistical Process Control (SPC) Assessment

    • 1 Assignment
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1 Assignment

  • Statistical Process Control (SPC)

Guiding Principles

    • 1 Videos
    • 1 Readings
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1 Videos

  • Guiding Principles

1 Readings

  • Guiding Principles Resources (Optional)

Data Story

    • 1 Videos
    • 1 Readings
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1 Videos

  • Data Story

1 Readings

  • Data Story Resources (Optional)

Tableau, Excel, and Power BI

    • 2 Videos
    • 1 Readings
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2 Videos

  • Tableau, Excel, and Power BI
  • Dan Gerena Discusses Data Visualization

1 Readings

  • Visualization Tools Resources (Optional)

Insight Evaluation

    • 1 Videos
    • 1 Readings
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1 Videos

  • Insight Evaluation

1 Readings

  • Insight Evaluation Resources (Optional)

Testing and Re-Evaluation

    • 2 Videos
    • 1 Readings
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2 Videos

  • Testing and Re-Evaluation
  • Dan Gerena Discusses Sustaining a Data-Driven Strategy

1 Readings

  • Testing and Re-Evaluation Resources (Optional)

Data Visualization and Translation Assessment

    • 1 Assignment
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1 Assignment

  • Data Visualization and Translation

Project: Data Analysis and Visualization

    • 1 Videos
    • 1 Readings
    • 1 Discussion
    • 1 PeerReview
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1 Peer Review

  • Data Analysis and Visualization

1 Discussions

  • Opportunity for Reflection

1 Videos

  • Project: Data Analysis and Visualization

1 Readings

  • Project: Data Analysis and Visualization (REQUIRED)

Auto Summary

"Data Analysis and Visualization" is a foundational course in Business & Management, taught by Coursera. It provides an overview of data analysis and visualization tools like R, Minitab, MATLAB, and Python, with a focus on statistical process control (SPC). Learners will explore best practices for visual data presentation using software such as Tableau, Excel, and Power BI. This 660-minute course includes online lectures, demos, and project work, catering to individuals aiming to foster a data-driven mindset. Subscription options include Starter and Professional, ideal for those with basic data familiarity.

Peter Baumgartner
Instructors

Peter Baumgartner

Brittany O'Dea
Instructors

Brittany O'Dea