Analyzing Data in Tableau
Take your Tableau skills up a notch with advanced analytics and visualizations.
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Course Description
Take your Tableau skills up a notch with advanced analytics and visualizations. In this course, you’ll learn how to create detail-rich map visualizations, configure date and time fields to show trends over time, and extend your data using Calculated Fields. You’ll also apply your new skills to complete a customer analytics case study. Through hands-on activities, you’ll learn how to create bins, customize filters and interactions, and apply quick table calculations. Finally, you’ll learn power user techniques, including how to slice and dice data and apply dynamic sets and groups—bringing you one step closer to being Tableau Desktop Specialist certification-ready.
- 1
Preparing for Analysis
FreeLearn best practices for organizing fields into dimensions and measures and how to configure date and time fields for trend analysis. All the while, you’ll use Calculated Fields, quick table calculations, and highlight actions to elevate your visualizations and reveal the hidden insights.
Data preparation50 xpNon-aggregating numerical dimensions50 xpPreparing the data50 xpMeasures and calculated fields100 xpHighlighter100 xpCalculated Fields to extend data50 xpDATEDIFF function100 xpWeekday or weekend?100 xpHighlighter for multiple rows100 xpVisualizations for exploratory analysis of trends50 xpDiscrete or continuous time analysis?100 xpDiscrete time analysis and Quick Table Calculations50 xpLow usage trends100 xpWeekly pattern by user type100 xpSlicing and dicing50 xpWeekday trends by gender and time of day100 xpBubble chart100 xpScheduling a promotional discount100 xp - 2
Exploring Visualizations
In this chapter, you’ll get to know more about Divvy users. Learning about them provides valuable information toward successful and continued engagement. To do this, you’ll build bar charts, KPI charts, and histograms with variable bin width. You’ll create additional insights by adding filters to your visualizations.
Who are your customers?50 xpMissing information100 xpExploring user data50 xpGetting to know the Divvy users100 xpAdding filters100 xpBuilding a KPI dashboard50 xpFormatting user KPIs100 xpCreating a user dashboard100 xpEnhancing the dashboard100 xpThe distribution of users50 xpChoosing the right chart type50 xpVisualizing distributions50 xpUsing a histogram100 xpUsing a line chart100 xpWorking with bins50 xpCustomizing the bin size100 xpExploring day pass user age100 xp - 3
Mapping Analysis
Dive deeper into maps and elevate geographic data with layers and density. You'll customize Tooltips and learn how to embed them with more information. You'll also learn more about Quick Table Calculations and apply them to your visualizations.
Interactive mapping of customer activity over time50 xpCustomer activity in motion50 xpVisualizing concentration of activity100 xpTableau's new density mark type100 xpLayering and total dock utilization50 xpSplitting the map100 xpEnhancing the map100 xpOverlaying the maps100 xpQuick table calculations for ranking50 xpWhat goes where?100 xpCombining characteristic and quick table calculations50 xpAdding details without noise100 xpBreaking out by customer type100 xpKPIs and time segments50 xpCharting station KPIs100 xpFrom bubbles to donuts100 xpAnalyzing our results100 xp - 4
Groups, Sets, and Parameters
Expand your Tableau toolbox with groups, sets, and parameters. You'll create groups using Lasso selection and Calculated Fields. You'll also use Parameters to enable users to dynamically input changes to your visualizations. Finally, you'll create Sets and compare your findings to an external weather data source.
Groups50 xpGroups for regions50 xpLasso selection100 xpEditing groups100 xpCreating seasonal groups50 xpSeasons100 xpRanking dashboard100 xpEmbedding in the tooltip100 xpParameters and sets50 xpParameter characteristics50 xpParameters50 xpReplacing rank with a parameter100 xpColor by parameter100 xpSets50 xpSet for windiness100 xpDivvy trips and windiness100 xpDivvy trips and temperature100 xp
In the following tracks
Tableau FundamentalsDatasets
Workbooks and datasourcesCollaborators
Celia FryarPrerequisites
Introduction to Tableau
Hadrien Lacroix
Curriculum Manager at DataCamp
Hadrien has collaborated on 30+ courses ranging from machine learning to database administration through data engineering. He's currently enrolled in a Masters of Analytics at Georgia Tech.
Hadrien started using DataCamp when the platform only had 27 courses. He then joined the Support team and helped students before becoming a Content Developer himself.
Follow Hadrien on LinkedIn
Hadrien started using DataCamp when the platform only had 27 courses. He then joined the Support team and helped students before becoming a Content Developer himself.
Follow Hadrien on LinkedIn
Sara Billen
Curriculum Manager at DataCamp
Sara is a graduate of a master's degree in Business Engineering and Marketing Analysis. Prior to working at DataCamp she worked as a Data Science consultant for a Belgian IT company. Sara is passionate about education, data science, and business and loves that she is able to combine all of these disciplines in her job as curriculum manager at DataCamp.
Lis Sulmont
Workspace Architect at DataCamp
Lis holds a Master's degree in Computer Science from McGill University with a focus on computer science education research and applied machine learning. She's passionate about teaching all things related to data and improving the accessibility of these topics.
What do other learners have to say?
I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds Banking Group
DataCamp is the top resource I recommend for learning data science.
Louis Maiden
Harvard Business School
DataCamp is by far my favorite website to learn from.
Ronald Bowers
Decision Science Analytics, USAA
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