Designing an Exploratory Data Analysis Research Plan from Pluralsight

A well-crafted exploratory data analysis research plan can make a big difference in a data scientist's work being implemented in their organization. In this course, you will learn the foundational components and how to deliver a successful analysis.

Creating a successful data science project that provides value to an organization can be a complex process. Developing an exploratory data analysis research plan elevates your data science project to an invaluable piece of information for the business. In this course, Designing an Exploratory Data Analysis Research Plan, you will learn what the components of a research plan are and strategies to implement the insights found into the organization. First, you will explore the basic components of a research plan and the difference between an academic and business-oriented exploratory data analysis research plan. Next, you will learn how to ask the right questions and begin getting a grasp on your data. Finally, you will develop a set of insights, including a series of machine learning models, and deliver the final exploratory data analysis research plan using R Markdown. When you are finished with this course, you will have the skills and knowledge needed to develop an exploratory data analysis research plan that may be implemented in your next data science project. Software required: R programming and R Studio.

What's inside

Syllabus

Course Overview

The Purpose of an Exploratory Data Analysis Research Plan

Beginning Our Data Exploration

Data Modeling

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches data exploration for business professionals

Explores exploratory data analysis research planning techniques

Applies R programming and R Studio software to practical use cases

Influenced by industry-standard techniques in exploratory data analysis

Recommended for students with some background in data science

Requires students to have access to specific software and tools

Reviews summary

Strategic data analysis planning for business

According to learners, this course provides a largely positive experience for those seeking to enhance their strategic approach to data analysis. Students emphasize its focus on developing a well-crafted exploratory data analysis research plan and understanding the distinction between academic and business-oriented applications. The course is highlighted for teaching how to ask the right questions and effectively deliver insights, often leveraging R Markdown. While many find its emphasis on communication and project management invaluable for organizational impact, some express a desire for more hands-on technical content, suggesting it's more conceptual than code-heavy.

Course assumes prior knowledge of R programming.

"My only minor critique is that it assumes a certain level of familiarity with R, so beginners might find that part a bit fast-paced."

"It assumes you already know R, which is fine, but good to know upfront."

Teaches effective communication of insights using R Markdown.

"...The section on R Markdown for delivery was particularly insightful, showing how to effectively communicate."

"The R Markdown templates provided were also a huge time-saver."

"The final module on delivering the analysis using R Markdown was very practical."

Emphasizes structuring data analysis for business value.

"This course really nails the strategic side of data analysis, which is often overlooked... Highly recommend for those who want to bridge the gap between technical work and business strategy."

"Absolutely fantastic! The focus on asking the right questions and developing a clear research plan resonated deeply. It truly elevates your data science project..."

"I found this course incredibly useful for shaping my data analysis projects. The framework for creating an exploratory data analysis research plan is well-explained and applicable."

Highly valuable for professionals improving project impact and communication.

"Essential for any data professional! This course filled a critical gap in my knowledge – how to translate raw data insights into strategic business recommendations."

"A must-take for anyone in data science looking to enhance their communication and project management skills. This course taught me how to frame my analysis..."

"Covers the non-technical but equally important aspects of data science projects very well. It's more about the mindset and process than specific coding techniques."

More conceptual and strategic than practical coding.

"I was hoping for a bit more hands-on application of the concepts within R itself... good for a high-level understanding but you'll need to practice on your own."

"Honestly, I was quite disappointed. I expected more concrete examples of how to actually *do* exploratory data analysis, not just talk about planning it."

"Not what I signed up for. I thought this would be a deep dive into EDA techniques with R, but it's mostly conceptual. Very little actual coding practice..."

"It felt a bit light on the 'data modeling' practicalities."

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 Designing an Exploratory Data Analysis Research Plan with these activities:

Follow tutorials on exploratory data analysis

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Following tutorials on exploratory data analysis can help you learn the basics of the process and how to apply it to your own data.

Browse courses on Exploratory Data Analysis

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Find online tutorials on exploratory data analysis.
Follow the tutorials step-by-step.
Complete the exercises at the end of each tutorial.

Read Exploratory Data Analysis with R

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Reading Exploratory Data Analysis with R can provide you with a comprehensive understanding of the EDA process and its application in R.

View R for Data Science: Import, Tidy, Transform,... on Amazon

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Read the book thoroughly.
Take notes on the concepts and techniques.
Complete the exercises at the end of each chapter.

Join a study group for the course

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Joining a study group can help you learn from others and get help with the course material.

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Find a study group that meets your schedule.
Attend the study group meetings regularly.
Participate in discussions and ask questions.

Four other activities

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Practice R programming exercises

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Practicing R programming exercises can help you improve your coding skills and prepare you for the course.

Browse courses on R Programming

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Find online R programming exercises.
Solve the exercises on your own.
Check your answers against the solutions.

Create a data exploration plan

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Creating a data exploration plan can help you organize your thoughts and ensure that you follow a structured approach to your data analysis.

Browse courses on Exploratory Data Analysis

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Define the goals of your data exploration.
Identify the data you will need.
Choose the data exploration techniques you will use.
Write a summary of your plan.

Attend industry events related to data science

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Attending industry events can help you network with other data scientists and learn about the latest trends in the field.

Browse courses on Data Science

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Find industry events in your area.
Attend the events and meet other data scientists.
Learn about the latest trends in data science.

Contribute to an open-source data science project

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Contributing to an open-source data science project can help you learn about the latest developments in the field and improve your coding skills.

Browse courses on Data Science

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Find an open-source data science project on GitHub.
Read the project documentation.
Contribute code to the project.
Submit your pull request.

Career center

Learners who complete Designing an Exploratory Data Analysis Research Plan will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist applies their programming expertise to build models that uncover insights in complex data. They do the work of a Data Analyst combined with the work of a Statistician. This course may be useful for those seeking to land their first Data Scientist role. It will help build the foundational components of a research plan, which is an essential skill for Data Scientists since they create many plans in their work.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst uses specialized tools and techniques to extract and analyze data to aid decision-making. This course may be useful for Data Analysts who want to advance their career. It teaches an elevated approach to developing analytics plans; this skill could help an Analyst make a case for a promotion.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A Business Intelligence Analyst specializes in collecting, analyzing, and presenting business data to aid decision-making. This course may be useful for those looking to begin work as a Business Intelligence Analyst. It will help you develop research plans to go along with your analyses.

See salaries and explore the career path for Business Intelligence Analyst

Statistician

A Statistician uses mathematics and statistics to collect, analyze, interpret, and present data. This course may be useful for those seeking to land their first Statistician role. It will help build the foundational components of a research plan, which is an essential skill for Statisticians.

See salaries and explore the career path for Statistician

Machine Learning Engineer

A Machine Learning Engineer designs, builds, deploys, and maintains machine learning systems. This course may be useful for Machine Learning Engineers who work on Exploratory Data Analysis projects. It teaches the skills for building the plan that will guide these projects, which will impress your project stakeholders.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

A Data Engineer designs, builds, and maintains data systems. This course may be useful for Data Engineers who want to advance into the Data Science field. It covers the foundational components of a research plan, which is a skill commonly utilized by Data Scientists.

See salaries and explore the career path for Data Engineer

Research Analyst

A Research Analyst gathers and analyzes data to make recommendations for business decisions. This course may be useful for Research Analysts who want to transition into a Data Analyst role. This course can help build a foundation in developing research plans, a core responsibility of a Data Analyst.

See salaries and explore the career path for Research Analyst

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical modeling to analyze financial data. This course may be useful for Quantitative Analysts who want to expand their skillset. It teaches the creation of research plans, which can lead to more accurate financial modeling.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

A Business Analyst uses data to identify and solve business problems. This course may be useful for Business Analysts who are looking to advance to a Sr. Business Analyst role. It can help build the foundation for developing research plans, which can make you a more effective partner to Stakeholders.

See salaries and explore the career path for Business Analyst

Data Architect

A Data Architect designs, builds, and maintains data systems. This course may be useful for Data Architects who want to advance to a Sr. Data Architect role. It helps you develop a foundation in creating research plans, a skill used by Sr. Data Architects when laying out the vision for data systems.

See salaries and explore the career path for Data Architect

Data Science Manager

A Data Science Manager leads a team of data scientists. This course may be useful for Data Science Managers who want to build their foundational knowledge of data science. It explores the creation of research plans, which can help you lead and advise a team of data scientists.

See salaries and explore the career path for Data Science Manager

Software Engineer

A Software Engineer designs, builds, and maintains software systems. This course may be useful for Software Engineers who want to transition into a Data Science role. It helps you develop a foundation in creating research plans, a skill used by Data Scientists to ensure their work is used by the organization.

See salaries and explore the career path for Software Engineer

Product Manager

A Product Manager analyzes market data to build and manage a product's roadmap. This course may be useful for Product Managers who are looking to gain an advantage over peers. It covers the foundational components of a research plan. This knowledge may be valuable when you are preparing to pitch your product's roadmap to Stakeholders.

See salaries and explore the career path for Product Manager

Marketing Analyst

A Marketing Analyst analyzes market data to help a company advertise, brand, and sell its products or services. This course may be useful for Marketing Analysts who want to expand their skillset. It explores the creation of research plans, which will help improve the quality of your analyses.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

A Financial Analyst analyzes financial data to make recommendations for investments. This course may be useful for Financial Analysts who want to become more effective in their roles. It teaches the foundational components of a research plan, which is helpful for informing investment decisions.

See salaries and explore the career path for Financial Analyst