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Ross Maciejewsk
and
K. Selcuk Candan
This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic...
Read more
This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic...
Read more
This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic usefulness, as well as the types of statistical graphs, —tools that are essential to exploratory data analysis.
Register for this course and see more details by visiting:
OpenCourser.com/course/lexadi/introduction
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possible dealbreakers
Geared toward learners brand new to big data storage, querying, exploratory data analysis, and statistical graphing
Covers exploratory querying to prepare learners for further analyses
Taught by industry experts in data analysis
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Reviews summary
Avoid this course
One reviewer found this course to have low coherence and low practical utility. They also viewed the course as overly theoretical and too time-consuming.
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 Introduction to Data Exploration and Visualization with these
activities:
Gather industry-specific resources
Show steps
Expand your knowledge base by compiling industry-specific resources, providing valuable context and enriching your understanding of real-world applications.
Show steps
-
Identify credible websites, articles, and industry reports.
-
Organize these resources into a central repository.
-
Review the materials regularly to stay updated on industry trends.
Create a comprehensive course resource
Show steps
Enhance your understanding of the course materials by organizing notes, assignments, quizzes, and exams into a comprehensive resource, fostering better retention and recall.
Show steps
-
Gather all relevant course materials.
-
Organize them into a logical structure.
-
Annotate and summarize key concepts for easy reference.
Review statistical graphics tools
Show steps
Review essential statistical graphics tools to strengthen your foundation for creating effective visualizations.
Browse courses on
Data Visualization Tools
Show steps
-
Identify the key statistical graphics tools and their functions.
-
Practice using these tools to create basic visualizations.
-
Explore additional resources to enhance your understanding.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete visualization exercises
Show steps
Sharpen your visualization skills through repetitive exercises, reinforcing concepts and improving your proficiency.
Show steps
-
Find visualization exercises online or in textbooks.
-
Dedicate regular time to solve these exercises.
-
Analyze your results and identify areas for improvement.
Create a visualization portfolio
Show steps
Showcase your visualization skills by creating a portfolio of your best work, demonstrating your ability to communicate data effectively.
Show steps
-
Gather a collection of your best visualizations.
-
Create a platform or website to display your portfolio.
-
Provide clear explanations and context for each visualization.
Explore advanced visualization techniques
Show steps
Expand your visualization knowledge by following tutorials and workshops on advanced techniques, further enhancing your ability to create impactful visualizations.
Show steps
-
Identify tutorials or workshops that align with your learning goals.
-
Set aside dedicated time to engage with these resources.
-
Experiment with the new techniques and apply them to your own projects.
Participate in data visualization competitions
Show steps
Challenge yourself and gain recognition by participating in data visualization competitions, fostering creativity and pushing the boundaries of your skills.
Show steps
-
Identify relevant data visualization competitions.
-
Thoroughly prepare by practicing and refining your skills.
-
Submit your best work and seek feedback to improve.
Gather industry-specific resources
Show steps
Expand your knowledge base by compiling industry-specific resources, providing valuable context and enriching your understanding of real-world applications.
Show steps
Show steps
Show steps
- Identify credible websites, articles, and industry reports.
- Organize these resources into a central repository.
- Review the materials regularly to stay updated on industry trends.
Create a comprehensive course resource
Show steps
Enhance your understanding of the course materials by organizing notes, assignments, quizzes, and exams into a comprehensive resource, fostering better retention and recall.
Show steps
Show steps
Show steps
- Gather all relevant course materials.
- Organize them into a logical structure.
- Annotate and summarize key concepts for easy reference.
Review statistical graphics tools
Show steps
Review essential statistical graphics tools to strengthen your foundation for creating effective visualizations.
Browse courses on
Data Visualization Tools
Show steps
Show steps
Show steps
- Identify the key statistical graphics tools and their functions.
- Practice using these tools to create basic visualizations.
- Explore additional resources to enhance your understanding.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete visualization exercises
Show steps
Sharpen your visualization skills through repetitive exercises, reinforcing concepts and improving your proficiency.
Show steps
Show steps
Show steps
- Find visualization exercises online or in textbooks.
- Dedicate regular time to solve these exercises.
- Analyze your results and identify areas for improvement.
Create a visualization portfolio
Show steps
Showcase your visualization skills by creating a portfolio of your best work, demonstrating your ability to communicate data effectively.
Show steps
Show steps
Show steps
- Gather a collection of your best visualizations.
- Create a platform or website to display your portfolio.
- Provide clear explanations and context for each visualization.
Explore advanced visualization techniques
Show steps
Expand your visualization knowledge by following tutorials and workshops on advanced techniques, further enhancing your ability to create impactful visualizations.
Show steps
Show steps
Show steps
- Identify tutorials or workshops that align with your learning goals.
- Set aside dedicated time to engage with these resources.
- Experiment with the new techniques and apply them to your own projects.
Participate in data visualization competitions
Show steps
Challenge yourself and gain recognition by participating in data visualization competitions, fostering creativity and pushing the boundaries of your skills.
Show steps
Show steps
Show steps
- Identify relevant data visualization competitions.
- Thoroughly prepare by practicing and refining your skills.
- Submit your best work and seek feedback to improve.
Career center
Learners who complete Introduction to Data Exploration and Visualization will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst examines and interprets data, organizing it into an understandable and cohesive format. This course, Introduction to Data Exploration and Visualization, provides a strong foundation for a career as a Data Analyst. It introduces the core concepts of data exploration and visualization, such as identifying dataset elements, understanding data warehouses, and effectively using visual variables and statistical graphs. These concepts and skills are essential for success in data analysis, as they empower analysts to uncover patterns, trends, and insights within vast datasets.
Data Engineer
Data Engineer
A Data Engineer designs and builds data architectures and systems. They ensure that data is collected, stored, organized, and processed efficiently to meet the needs of the organization. This course, Introduction to Data Exploration and Visualization, is highly relevant to a Data Engineer's role as it provides a comprehensive overview of the fundamental concepts of data exploration and visualization techniques. By understanding how to explore, analyze, and present data effectively, Data Engineers can design robust and scalable data systems that support data-driven decision-making.
Data Scientist
Data Scientist
A Data Scientist combines skills in data analysis, machine learning, and statistics to extract insights from data and build predictive models. This course, Introduction to Data Exploration and Visualization, is a good starting point for aspiring Data Scientists, as it covers the basics of data exploration and visualization. By gaining a solid understanding of these concepts, Data Scientists can effectively explore and analyze large datasets, identify patterns and trends, and develop data-driven solutions to complex business problems.
Statistician
Statistician
A Statistician collects, analyzes, interprets, and presents data. They use statistical methods to uncover patterns and trends in data, and to make predictions about future events. This course, Introduction to Data Exploration and Visualization, can be beneficial for aspiring Statisticians as it provides a solid foundation in data exploration and visualization techniques. By gaining proficiency in these skills, Statisticians can effectively communicate complex statistical concepts and findings to a diverse range of audiences.
Business Analyst
Business Analyst
A Business Analyst uses data and analysis to identify and solve business problems. They work closely with stakeholders to understand their needs and develop solutions that improve business outcomes. This course, Introduction to Data Exploration and Visualization, can be helpful for aspiring Business Analysts as it provides a foundational understanding of data analysis and visualization techniques. By mastering these skills, Business Analysts can effectively analyze data, identify trends and patterns, and develop data-driven recommendations to improve business performance.
Market Researcher
Market Researcher
A Market Researcher gathers and analyzes data about markets, consumers, and competitors. They use this information to develop marketing strategies and campaigns that target specific audiences and drive business growth. This course, Introduction to Data Exploration and Visualization, can be beneficial for aspiring Market Researchers as it provides a solid foundation in data analysis and visualization techniques. By gaining proficiency in these skills, Market Researchers can effectively analyze market data, identify consumer trends, and develop targeted marketing strategies.
Financial Analyst
Financial Analyst
A Financial Analyst evaluates and interprets financial data to make investment recommendations and assess the financial health of companies. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Financial Analysts as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Financial Analysts can effectively analyze financial data, identify trends and patterns, and make informed investment decisions.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical methods to improve the efficiency and effectiveness of business operations. They work on a variety of projects, such as optimizing supply chains, scheduling production, and designing logistics networks. This course, Introduction to Data Exploration and Visualization, can be beneficial for aspiring Operations Research Analysts as it provides a solid foundation in data analysis and visualization techniques. By gaining proficiency in these skills, Operations Research Analysts can effectively analyze data, identify inefficiencies, and develop data-driven solutions to improve operational performance.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work on a variety of projects, such as developing new features, fixing bugs, and improving performance. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Software Engineers as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Software Engineers can effectively analyze data, identify patterns and trends, and develop software solutions that meet the needs of users.
Web Developer
Web Developer
A Web Developer designs and develops websites and web applications. They work on a variety of projects, such as creating new websites, updating existing websites, and fixing bugs. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Web Developers as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Web Developers can effectively analyze web data, identify user behavior patterns, and develop user-friendly and engaging websites.
Data Journalist
Data Journalist
A Data Journalist uses data to tell stories and uncover insights. They work on a variety of projects, such as writing articles, creating data visualizations, and developing interactive data-driven applications. This course, Introduction to Data Exploration and Visualization, can be beneficial for aspiring Data Journalists as it provides a solid foundation in data analysis and visualization techniques. By gaining proficiency in these skills, Data Journalists can effectively analyze data, identify trends and patterns, and communicate complex information in a clear and engaging way.
Information Architect
Information Architect
An Information Architect designs and organizes the structure and content of websites and other digital products. They work on a variety of projects, such as creating navigation systems, designing user interfaces, and developing content strategies. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Information Architects as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Information Architects can effectively analyze user data, identify patterns and trends, and develop user-centered designs that improve the user experience.
User Experience Designer
User Experience Designer
A User Experience Designer designs and evaluates the user experience of websites and other digital products. They work on a variety of projects, such as creating prototypes, conducting user research, and developing design guidelines. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring User Experience Designers as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, User Experience Designers can effectively analyze user data, identify pain points, and develop user-centered designs that improve the user experience.
Content Strategist
Content Strategist
A Content Strategist develops and executes content strategies for websites and other digital products. They work on a variety of projects, such as creating content calendars, developing editorial guidelines, and promoting content. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Content Strategists as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Content Strategists can effectively analyze content performance, identify trends and patterns, and develop data-driven content strategies that achieve business objectives.
Digital Marketing Specialist
Digital Marketing Specialist
A Digital Marketing Specialist plans and executes digital marketing campaigns. They work on a variety of projects, such as creating social media content, managing email campaigns, and analyzing website traffic. This course, Introduction to Data Exploration and Visualization, may be helpful for aspiring Digital Marketing Specialists as it provides a foundational understanding of data analysis and visualization techniques. By gaining proficiency in these skills, Digital Marketing Specialists can effectively analyze campaign performance, identify trends and patterns, and develop data-driven marketing strategies that improve campaign effectiveness.
For more career information including salaries, visit:
OpenCourser.com/course/lexadi/introduction
Reading list
We've selected 14 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
Introduction to Data Exploration and Visualization.
This classic book by Edward Tufte must-read for anyone interested in data visualization. It provides a deep dive into the principles of visual communication and how to effectively present data.
This practical guide is specifically designed for business professionals who want to use data visualization to communicate effectively with their audience. It covers topics such as choosing the right visuals, creating engaging presentations, and using data to tell compelling stories.
Provides a modern approach to data visualization, covering topics such as data wrangling, visual perception, and the use of machine learning in data visualization.
Comprehensive guide to the Python programming language for data analysis. It covers topics such as data wrangling, data visualization, and statistical modeling.
Provides a comprehensive overview of interactive data visualization techniques for the web. It covers topics such as creating interactive charts, maps, and dashboards using popular JavaScript libraries.
Provides a comprehensive guide to data visualization using Python. It covers topics such as data preparation, choosing the right visuals, and creating interactive visualizations using popular Python libraries.
Save
Comprehensive guide to the R programming language for data science. It covers topics such as data wrangling, data visualization, and statistical modeling.
Provides a step-by-step guide to using Power BI for data visualization. It valuable resource for beginners who want to learn how to use Power BI effectively.
Save
Provides a collection of creative and visually appealing data sketches. It valuable resource for inspiration and for learning how to communicate data in a simple and engaging way.
Save
Emphasizes the importance of honesty and integrity in data visualization. It provides guidance on how to avoid misleading visuals and how to use data visualization for ethical and responsible communication.
Focuses on the design of effective information dashboards. It provides guidance on how to choose the right metrics, create clear and concise visualizations, and organize dashboards for maximum impact.
Provides a comprehensive overview of the fundamentals of data visualization. It covers topics such as visual perception, cognitive psychology, and the design of effective visualizations.
Provides a theoretical foundation for data visualization. It covers topics such as visual perception, cognitive psychology, and the design of effective visualizations.
Save
Provides a cautionary tale about the potential pitfalls of data visualization. It covers topics such as statistical biases, data manipulation, and the importance of critical thinking when interpreting data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/lexadi/introduction
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Via
Coursera
Institution
Arizona State University
Instructors
Ross Maciejewsk
K. Selcuk Candan
This course belongs to a
collection
called
Data Visualization. It's comprised of four courses:
- Multivariate and Geographical Data Analysis
- Introduction to Data Exploration and Visualization (viewing)
- Additional Tools Used for Data Visualization
- Temporal and Hierarchical Data Analysis
Good to know
Geared toward learners brand new to big data storage, querying, exploratory data analysis, and statistical graphing
Covers exploratory querying to prepare learners for further analyses
Taught by industry experts in data analysis
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