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Developing Data Products

Roger D. Peng, PhD, Brian Caffo, PhD, and Jeff Leek, PhD

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.

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What's inside

Syllabus

Course Overview

In this overview module, we'll go over some information and resources to help you get started and succeed in the course.

Shiny, GoogleVis, and Plotly

Now we can turn to the first substantive lessons. In this module, you'll learn how to develop basic applications and interactive graphics in shiny, compose interactive HTML graphics with GoogleVis, and prepare data visualizations with Plotly.

R Markdown and Leaflet

During this module, we'll learn how to create R Markdown files and embed R code in an Rmd. We'll also explore Leaflet and use it to create interactive annotated maps.

R Packages

In this module, we'll dive into the world of creating R packages and practice developing an R Markdown presentation that includes a data visualization built using Plotly.

Swirl and Course Project

Week 4 is all about the Course Project, producing a Shiny Application and reproducible pitch.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches how to create interactive visualizations and web-based data products, which is a common skill to have in the data science industry

Instructors are highly recognized for their work in the topic the course teaches

Builds upon learners' existing statistical knowledge and strengthens their statistical foundation in the context of data products

Uses a mix of media and materials, including videos, readings, discussions, hands-on labs, and interactive materials

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Reviews summary

Data product development course

According to students, "Developing Data Products" is well-received and engaging. Learners found it especially useful for gaining practical experience in developing data products using R and Shiny. The course project is a highlight for many, allowing them to apply learned skills to create their own data products.

The course provides a good overview of Shiny.

"Good overview of tools to use in rstudio to produce data products."

"Especially liked shiny: efficient tool to produce useful data products on the web."

Students enjoyed the final project.

"This is the 9th course in the series I completed and I found it the most fun."

"I also learned a tremendous amount that I have directly applied at work."

"The course project is much more flexible than the prior course projects and allows a student to develop a data product of their own choosing."

One student had a negative experience.

"The title should be more like "Developing Money From Gullible Students Who Don't Know Any Better"."

"Don't take this course, you will not bring anything out of it."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Developing Data Products with these activities:

Follow online tutorials on statistical analysis

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Supplement course content by exploring additional resources and tutorials.

Browse courses on Statistical Analysis

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Identify reputable online platforms or instructors
Select tutorials relevant to course topics
Follow the tutorials and complete any exercises or assignments

Revisit Statistical Analysis Tools

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Ensure a foundational understanding of basic statistical analysis concepts and tools.

Browse courses on Statistical Analysis

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Review hypothesis testing, confidence intervals, and regression.
Practice using statistical software (e.g., R) to perform the aforementioned techniques.

Refine skills in R programming

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Review fundamentals of R programming to strengthen base understanding before starting the course.

Browse courses on R Programming

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Revisit code from previous courses or projects
Review introductory R programming tutorials
Practice writing simple R scripts for data analysis

Nine other activities

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Explore Interactive Data Visualization Techniques

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Develop familiarity and proficiency with creating interactive data visualizations for effective data storytelling.

Browse courses on Data Visualization

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Complete online tutorials on creating interactive graphics using Shiny and Plotly.
Experiment with different visualization types and their use cases.

Solve practice problems on data analysis concepts

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Enhance problem-solving skills by practicing data analysis problems.

Browse courses on Data Analysis

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Find practice problems from textbooks or online resources
Attempt to solve the problems independently
Review solutions and identify areas for improvement

Practice Data Manipulation and Transformation

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Solidify your ability to manipulate and transform data for analysis and visualization.

Browse courses on Data Manipulation

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Work through exercises and practice problems that involve data cleaning, merging, and subsetting.
Explore different R packages for data manipulation and learn how to apply them in your projects.

Summarize statistical concepts in a blog post or forum

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Reinforce understanding of statistical concepts by writing a blog post or participating in forum discussions.

Browse courses on Statistical Concepts

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Identify a statistical concept to explore
Research and gather information on the concept
Organize and write a clear and concise explanation
Share your writing on a relevant platform

Collaborate on a Data Analysis Project

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Engage in collaborative work with peers to enhance your understanding and application of data analysis and visualization techniques.

Browse courses on Collaboration

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Form a group with other students and choose a data analysis project.
Assign roles and responsibilities within the group.
Work together to explore the data, create visualizations, and draw conclusions.

Attend workshops on data science and statistical methods

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Expand knowledge and network with professionals by attending workshops in the field.

Browse courses on Data Science

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Research and identify relevant workshops
Register and attend the workshops
Actively participate in discussions and networking opportunities

Develop an Interactive Shiny Application

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Create a functional Shiny application that demonstrates your mastery of data manipulation, visualization, and storytelling.

Browse courses on Shiny

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Identify a data set and develop a plan for how to present it effectively using Shiny.
Build the Shiny application using appropriate widgets and visualizations.
Test and finalize the application for presentation.

Develop a Shiny application for data visualization

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Apply course concepts by creating a Shiny application that effectively communicates data insights.

Browse courses on Data Visualization

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Identify a dataset and a visualization goal
Design and develop the Shiny application using R
Test and refine the application for usability
Deploy the application and share it with others

Participate in a data analysis competition

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Challenge yourself and showcase your skills by competing in a data analysis competition.

Browse courses on Data Analysis

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Identify a relevant competition platform
Study the competition rules and data provided
Develop a data analysis pipeline and build models
Submit your results and receive feedback

Career center

Learners who complete Developing Data Products will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data. They use their findings to help businesses make better decisions. This course can help you develop the skills you need to be a successful Data Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists are responsible for developing and implementing data-driven solutions to business problems. They use their skills in statistics, machine learning, and data mining to help businesses make better decisions. This course can help you develop the skills you need to be a successful Data Scientist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. They use their findings to help businesses make better decisions. This course can help you develop the skills you need to be a successful Statistician. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts are responsible for analyzing business problems and recommending solutions. They use their skills in data analysis, process improvement, and problem-solving to help businesses improve their performance. This course can help you develop the skills you need to be a successful Business Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers are responsible for conducting research to understand consumer behavior. They use their findings to help businesses develop new products and services. This course can help you develop the skills you need to be a successful Market Researcher. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Market Researcher

Financial Analyst

Financial Analysts are responsible for analyzing financial data to make investment recommendations. They use their skills in statistics, finance, and economics to help investors make better decisions. This course can help you develop the skills you need to be a successful Financial Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts are responsible for developing and implementing mathematical models to optimize business operations. They use their skills in statistics, optimization, and simulation to help businesses improve their efficiency and effectiveness. This course can help you develop the skills you need to be a successful Operations Research Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Operations Research Analyst

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software applications. They use their skills in computer science, software engineering, and mathematics to create software that meets the needs of users. This course can help you develop the skills you need to be a successful Software Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines. They use their skills in data engineering, software engineering, and computer science to create data pipelines that can process and analyze large amounts of data. This course can help you develop the skills you need to be a successful Data Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use their skills in machine learning, computer science, and mathematics to create machine learning models that can solve complex problems. This course can help you develop the skills you need to be a successful Machine Learning Engineer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Machine Learning Engineer

Data Visualization Specialist

Data Visualization Specialists are responsible for creating visual representations of data. They use their skills in data visualization, graphic design, and storytelling to create data visualizations that can communicate complex information in a clear and concise way. This course can help you develop the skills you need to be a successful Data Visualization Specialist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Data Visualization Specialist

UX Designer

UX Designers are responsible for designing the user experience of digital products. They use their skills in user experience design, human-computer interaction, and psychology to create digital products that are easy to use and enjoyable to interact with. This course can help you develop the skills you need to be a successful UX Designer. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for UX Designer

Product Manager

Product Managers are responsible for managing the development and launch of new products. They use their skills in product management, marketing, and business strategy to create products that meet the needs of users. This course can help you develop the skills you need to be a successful Product Manager. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Product Manager

Data Journalist

Data Journalists are responsible for using data to tell stories. They use their skills in journalism, data analysis, and data visualization to create data-driven stories that can inform and educate the public. This course can help you develop the skills you need to be a successful Data Journalist. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Data Journalist

Quantitative Analyst

Quantitative Analysts are responsible for using mathematical and statistical models to analyze financial data. They use their skills in mathematics, statistics, and finance to create models that can predict the performance of financial instruments. This course can help you develop the skills you need to be a successful Quantitative Analyst. You will learn how to use Shiny, R packages, and interactive graphics to create data products that can be used to tell a story about data to a mass audience.

See salaries and explore the career path for Quantitative Analyst

Reading list

We've selected 25 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Developing Data Products.

The Elements of Statistical Learning

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Classic textbook on statistical learning methods. It may be useful for students who want to learn more about the theory and practice of statistical learning.

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Kindle Edition

$$$

Interactive Web-Based Data Visualization with R,...

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Provides a comprehensive overview of the R programming language and its capabilities for creating interactive data visualizations. It covers the basics of ggplot2 and plotly, and how to use them to create a variety of visualizations, including charts, maps, and dashboards.

Developing Data Products

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Data product development course

Activities

Career center

Reading list

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