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Skill-Up EdTech Team

The Tableau Capstone Project allows you to apply what you've learned about making data-driven decisions to real business challenges companies face every day.

Effective business intelligence (BI) is crucial in decision-making and strategizing in today's data-driven business environment. This capstone project explores the utilization of Tableau, a leading data visualization tool, to enhance BI capabilities within an organization. The project will showcase how Tableau can convert raw data into actionable insights, enabling informed decision-making.

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The Tableau Capstone Project allows you to apply what you've learned about making data-driven decisions to real business challenges companies face every day.

Effective business intelligence (BI) is crucial in decision-making and strategizing in today's data-driven business environment. This capstone project explores the utilization of Tableau, a leading data visualization tool, to enhance BI capabilities within an organization. The project will showcase how Tableau can convert raw data into actionable insights, enabling informed decision-making.

This project begins by identifying key business objectives and data sources relevant to the organization's operations. You will learn about data cleaning and preparation processes to ensure data accuracy and consistency. You will use Tableau's visualization capabilities, interactive dashboards, and stories to showcase important KPIs, trends, and patterns within the data.

By the end of this capstone, you'll be able to design the interactive dashboard and create an engaging story suitable to present to stakeholders.

Upon completion of the course, you will have gained several Tableau business intelligence skills to include in your portfolio.

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What's inside

Syllabus

Preparing Data for Visualization
In this capstone project module, you will apply data cleaning and preparation techniques to improve data quality, ensuring it is accurate and reliable for analysis. You will also explore the impact of missing values on data quality and identify strategies to handle them effectively. By the end of this module, you will have cleaned and prepared data for basic data visualization and analysis.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Examines business intelligence, a crucial skill in today's data-driven business environment
Focuses on data visualization and data-driven insights with Tableau, an industry-leading tool
Teaches data cleaning and preparation techniques, emphasizing data quality and accuracy
Develops skills in storytelling with Tableau, helping learners present insights in engaging ways
Guided by Skill-Up EdTech Team, a reputable provider of EdTech training
Provides hands-on experience, preparing learners to apply Tableau in real-world business scenarios

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Reviews summary

Tableau skill application & portfolio project

According to students, this Tableau Capstone Project is an excellent course for solidifying Tableau skills, serving as a valuable final stage to professional certificates. Learners found the lectures very useful, providing step-by-step guidance for the project. The instructor was praised for being clear and concise, making complex concepts easy to grasp. The final project, though challenging, was very rewarding, enabling the creation of a complete dashboard and story for a professional portfolio. It offers an amazing opportunity to apply everything learned in previous stages of a program.
The final project was challenging but ultimately rewarding.
"The final project was challenging but very rewarding, allowing me to build a complete dashboard and story..."
"It was challenging, but the outcome of creating a full dashboard and story for my portfolio was truly rewarding."
Lectures and instructor provided clear, step-by-step guidance.
"I found the lectures to be very useful, as they guided me step by step through the project..."
"The instructor was clear and concise, making complex concepts easy to grasp."
"The guidance provided made even complex Tableau concepts simple to understand."
Excellent for applying previously learned skills in a practical project.
"It was an amazing opportunity to apply everything I had learned throughout the program."
"I really enjoyed this course... an excellent course for solidifying Tableau skills!"
"I was able to build a complete dashboard and story that I could add to my portfolio, which was great."

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 Tableau Capstone Project with these activities:
Tableau Meetup
Connect with other Tableau users, learn from industry experts, and explore new data visualization trends.
Show steps
  • Attend local or virtual Tableau meetups or conferences.
  • Join online Tableau forums or communities.
  • Participate in discussions and ask questions related to Tableau.
Review Data Visualization: A Practical Introduction by Andy Kirk
Reinforce your knowledge of data visualization techniques and concepts by reviewing core principles and examples in the book.
Show steps
  • Read the book's chapters on data visualization fundamentals, types of visualizations, and best practices.
  • Complete the exercises and examples provided in the book to practice your data visualization skills.
Tableau Tutorial for Beginners
Start your Tableau journey by following guided tutorials that introduce the basics of Tableau and its features.
Browse courses on Tableau
Show steps
  • Learn to connect to data sources.
  • Create simple visualizations and charts.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Tableau Visualization Exercises
Sharpen your Tableau skills by completing guided visualization exercises and challenges.
Browse courses on Tableau
Show steps
  • Access online Tableau exercise platforms or tutorials.
  • Select exercises that align with specific Tableau features or visualization techniques.
  • Follow step-by-step instructions or videos to create visualizations from scratch.
  • Evaluate your results and identify areas for improvement.
Tableau Discussion Forum Participation
Engage with fellow Tableau enthusiasts in online forums to share insights, ask questions, and learn from others' experiences.
Browse courses on Tableau
Show steps
  • Ask questions to clarify concepts.
  • Share your own Tableau projects and insights.
Tableau Data Visualization Practice
Engage in hands-on data visualization exercises using Tableau to solidify your understanding of Tableau's capabilities.
Browse courses on Tableau
Show steps
  • Load sample datasets into Tableau.
  • Create visualizations to explore data trends and patterns.
  • Build interactive dashboards to showcase key insights.
Tableau Dashboard Project
Apply what you've learned by creating an interactive Tableau dashboard that visually communicates key insights from a real-world dataset.
Show steps
  • Identify a business or personal dataset that you want to visualize.
  • Import the data into Tableau and clean and prepare it for analysis.
  • Design and build a dashboard that effectively communicates the key insights from the data.
  • Create a presentation or documentation that explains the dashboard's purpose, design, and findings.

Career center

Learners who complete Tableau Capstone Project will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 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 Tableau Capstone Project .
This classic book by Edward Tufte must-read for anyone interested in data visualization. It covers a wide range of topics, from the principles of visual perception to the design of effective charts and graphs.
Seminal work on the grammar of graphics, a formal language for describing data visualizations. It covers a wide range of topics, from the basics of the grammar of graphics to the use of the grammar of graphics to create a variety of charts and graphs.
Decisive provides a four-step process (WRAP) for making better decisions: Widen your options, Reality-test your assumptions, Attain distance before deciding, and Prepare to be wrong. offers practical strategies and is highly applicable for students and professionals seeking to improve their decision-making skills in various contexts. It's a practical guide that complements the theoretical understanding of decision making.
Ariely explores the many ways in which our decisions are not rational, revealing the systematic and predictable errors we make. is highly relevant to understanding the biases discussed in several of the online courses. It serves as valuable additional reading to complement theoretical knowledge with real-world examples of irrationality.
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This recent book delves into the concept of noise – the unwanted variability in judgments that should ideally be identical. It builds upon Kahneman's previous work and is highly relevant to contemporary discussions on improving decision making in professional settings, such as medicine, law, and forecasting. It provides a deeper understanding of errors in judgment beyond just biases.
Provides a comprehensive overview of the psychological processes that influence managerial judgment and decision making. It is often used as a textbook in business schools and is highly relevant for understanding how cognitive biases affect decisions in organizational settings. It's a valuable resource for both students and professionals.
Drawing on her background as a professional poker player, Duke provides a framework for making better decisions in situations involving uncertainty and incomplete information. is particularly useful for understanding probabilistic thinking and managing risk, relevant to courses on decision making under uncertainty and financial analysis. It offers practical strategies for real-world decision making.
Schwartz argues that an overload of choices can lead to increased anxiety, indecision, and dissatisfaction. is highly relevant to understanding the psychological impact of decision making in modern society, a theme that resonates with courses on consumer psychology and behavioral economics. It provides a deeper understanding of the challenges individuals face when making choices.
Provides a comprehensive overview of data visualization, covering the basics of visual perception, data types, and chart types. It great resource for beginners who want to learn the fundamentals of data visualization.
Comprehensive guide to data cleaning in R and Python. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It valuable resource for anyone who wants to learn more about data cleaning and improve the quality of their data.
Provides a comprehensive overview of data cleaning techniques, including data quality assessment, data transformation, and data validation. It valuable resource for anyone who wants to learn more about data cleaning and improve the quality of their data.
Considered a classic practical guide, this book outlines a structured approach to decision making focusing on identifying objectives, creating alternatives, and understanding consequences and tradeoffs. It's a valuable reference tool for anyone who needs a systematic method for tackling complex decisions. The methods presented are time-tested and widely applicable.
A follow-up to 'Thinking in Bets,' this book offers practical tools and frameworks for making better decisions in everyday life. It focuses on developing a robust process for decision making, even when faced with uncertainty. is well-suited for a broad audience looking for actionable strategies.
This guidebook offers a comprehensive overview of the Business Intelligence lifecycle, from data integration to analytics. It provides clear explanations of architectural design and processes, making it valuable for gaining a broad understanding of the field. It useful reference for navigating the complexities of BI projects and includes practical solutions.
Comprehensive guide to data cleaning in SAS and Python. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It valuable resource for anyone who wants to learn more about data cleaning and improve the quality of their data.
Comprehensive guide to data cleaning in Stata and Python. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It valuable resource for anyone who wants to learn more about data cleaning and improve the quality of their data.
Dalio shares the principles he developed and used to achieve success in life and at Bridgewater Associates. The book outlines a systematic approach to decision making based on clearly articulated principles and radical transparency. It provides insights into strategic decision making in a professional context.
Examines the traits and techniques of 'superforecasters' – individuals who are exceptionally good at predicting future events. It provides insights into probabilistic thinking, updating beliefs based on new information, and working in teams to improve forecasts, all of which are relevant to data-driven decision making and strategic planning.
For those working with Microsoft BI tools like Power BI, SSAS, and Excel, a strong understanding of DAX is essential. is considered a definitive guide to the DAX language, providing in-depth knowledge for creating powerful calculations and data models.
This academic text provides a thorough exploration of the theoretical and empirical research on thinking and decision making. It covers various models of decision making and biases, making it a valuable resource for graduate students and researchers seeking a deep understanding of the subject. It's more suitable as a core textbook for advanced study.
Applies game theory principles to a wide range of strategic interactions, providing a framework for thinking strategically and making decisions when the outcome depends on the choices of others. It's highly relevant for understanding strategic decision making in business and other competitive environments.
Taleb discusses the impact of rare and unpredictable events (black swans) and our tendency to rationalize them in hindsight. is relevant for understanding the limitations of traditional forecasting and decision-making models in the face of extreme uncertainty. It offers a critical perspective on how we think about and prepare for the unexpected.
Comprehensive guide to the entire Business Intelligence project lifecycle, from planning to deployment. It provides a structured approach to implementing BI solutions and emphasizes understanding business needs and ensuring data quality. It valuable resource for project managers and those involved in BI implementation.
Klein explores decision making in naturalistic settings, focusing on how experienced professionals make high-stakes decisions under pressure and with limited information. is valuable for gaining a broader understanding of decision processes beyond purely rational models and is particularly relevant for those interested in leadership and applied decision making.
While not solely focused on personal decision making, Cialdini's book explores the principles of persuasion and how they influence our decisions and compliance. Understanding these principles is valuable for recognizing external factors that can impact decision processes, relevant to courses on consumer psychology and negotiation. It provides insight into how others can influence our choices.
Provides real-world examples of how companies are using big data and analytics to achieve success. It showcases Business Intelligence in action across various industries, offering practical insights and inspiration. It's valuable for understanding the practical applications of BI.
Practical guide to data cleaning in Python. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It great resource for anyone who wants to learn how to use Python for data cleaning.
This guide focuses specifically on strategic decision making within a business context, offering practical steps and frameworks for developing effective business plans. It useful resource for professionals and students interested in the application of decision-making principles to business strategy. It serves as a practical guide for a specific domain of decision making.
While focusing on data science, this book is highly relevant to Business Intelligence as it explains how to use data mining and analytical thinking to solve business problems. It provides a solid foundation in the principles and concepts behind extracting value from data, which core component of BI.
Addresses the importance of having a sound data strategy in the age of big data and IoT. It helps readers understand how to leverage data, analytics, and Business Intelligence to drive profitability and gain a competitive edge.
A practical guide to data visualization using Tableau, emphasizing the principles and best practices of effective data storytelling.
Offers a visually engaging collection of 50 models and frameworks for better decision making and strategic thinking. It's a practical and accessible resource that can be used as a quick reference tool for approaching different types of decisions. It provides breadth in terms of the variety of decision-making approaches.
Predictive analytics is an advanced area within Business Intelligence. explores how predictive analytics works and its applications in various business scenarios. It's suitable for those looking to deepen their understanding of advanced BI techniques.
Effective data visualization crucial aspect of Business Intelligence. focuses on the principles of designing insightful and effective dashboards for communicating data clearly and accurately. It's a valuable resource for anyone involved in presenting BI findings.
Tableau widely used BI and data visualization tool. focuses on mastering Tableau for implementing advanced BI techniques, analytics, and even machine learning models. It's a practical guide for those looking to become proficient in using a popular BI platform.
Provides a practical, hands-on guide to implementing Business Intelligence solutions using the Microsoft SQL Server platform and Power BI. It covers building data models, creating reports, and utilizing various Microsoft BI tools. It's particularly useful for those working within a Microsoft ecosystem.
Makes a compelling business case for embracing big data. It helps readers understand the value and potential of big data, which significant driver for modern Business Intelligence initiatives. It's relevant for understanding the strategic importance of BI in a data-rich world.
Serves as an excellent introduction to Business Intelligence for beginners with no prior experience. It covers basic concepts, vocabulary, and walks readers through the process of identifying business needs and implementing a BI strategy. It's a great starting point for high school and undergraduate students.
Practical guide to data cleaning in JMP. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It great resource for anyone who wants to learn how to use JMP for data cleaning.
Practical guide to data cleaning in SAS. It covers a wide range of topics, including data import, data exploration, data transformation, and data validation. It great resource for anyone who wants to learn how to use SAS for data cleaning.
A practical guide to using Tableau effectively, covering best practices, performance optimization, and data storytelling.
Beginner's guide to using Tableau, one of the most popular data visualization tools. It covers the basics of Tableau, as well as how to use Tableau to create a variety of charts and graphs.
A guide to data storytelling with R. covers the basics of data visualization and dashboarding in R and provides tips on how to use R to create effective data stories.
Data warehousing foundational component of Business Intelligence. provides an accessible introduction to data warehousing concepts for beginners. It's a good prerequisite read for understanding where the data used in BI originates and how it's structured.

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