In this project-based course, you will follow your own interests to create a portfolio worthy single-frame viz or multi-frame data story that will be shared on Tableau Public. You will use all the skills taught in this Specialization to complete this project step-by-step, with guidance from your instructors along the way. You will first create a project proposal to identify your goals for the project, including the question you wish to answer or explore with data. You will then find data that will provide the information you are seeking. You will then import that data into Tableau and prepare it for analysis. Next you will create a dashboard that will allow you to explore the data in depth and identify meaningful insights. You will then give structure to your data story by writing the story arc in narrative form. Finally, you will consult your design checklist to craft the final viz or data story in Tableau. This is your opportunity to show the world what you’re capable of - so think big, and have confidence in your skills!
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Data Visualization with Tableau Project
This course is part of Data Visualization with Tableau Specialization
Instructors: Suk S. Brar, M.B.A.
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What you'll learn
Develop a project proposal
Assess the quality of the data and perform exploratory analysis
Create KPIs and dashboards and assess your analysis
Create your data story and write a narrative to accompany your visualization
Skills you'll gain
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There are 6 modules in this course
In this first milestone, you will write a project proposal that will capture the “who, what, why and how” of your project plus any challenges that you foresee along the way. Your proposal will include: a specific business case or personal objective, any intended outcomes, a description of the needs of the intended audience, a description of the dataset to be used, and any foreseeable challenges.
What's included
2 videos7 readings1 peer review1 app item2 discussion prompts
In milestone two, you will acquire the dataset that supports your project proposal, import it into Tableau, and prepare the data for analysis.
What's included
1 video3 readings1 peer review1 discussion prompt
In this milestone, you will use the skills that you have learned in the specialization to perform exploratory analysis of your data. You will identify key metrics in the data and create KPIs, and you will use those KPIs to create dashboards that allow for comparative views and “brushing and linking.” This will allow us to begin to think about the proper context of developing an explanatory analysis that will form the basis for the remaining milestones. Be sure your visualizations demonstrate the visual and cognitive design principles learned throughout the Specialization, and make use of advanced features like hierarchies, actions, filters and parameters.
What's included
1 video6 readings1 discussion prompt
In this module, you will continue to work through Milestone 3, your exploratory analysis and dashboard creation as outlined in the third week. You will then submit your deliverables for peer review.
What's included
2 readings1 peer review1 discussion prompt
In this milestone, you will take a short but essential break from the data visualization software and begin to give structure to your data stories. You will define the basic story arc of your data story, or draft a narrative description of what your data visualization communicates. You have started that process in the previous milestones, but now we will start assembling our story using Story Points.
What's included
1 video3 readings1 peer review1 discussion prompt
In this final milestone, you will apply design elements from our design checklist. You have met the goals of the stakeholder’s and will complete your design to meet the needs of the audience. You will apply the cognitive and visual design concepts learned throughout this Specialization and create a visualization or data story that leaves a lasting impression with your audience.
What's included
2 videos1 peer review2 discussion prompts
Instructors
Offered by
Recommended if you're interested in Data Analysis
Coursera Project Network
University of California, Irvine
University of Maryland, College Park
Macquarie University
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