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Questo esercizio fa parte del corso

Analizzare i dati in Tableau

InicianteNível de habilidade

4.9+

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Learn 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.

Exercise 1: Data preparation Exercise 2: Non-aggregating numerical dimensions Exercise 3: Preparing the data Exercise 4: Measures and calculated fields Exercise 5: Highlighter Exercise 6: Calculated Fields to extend data Exercise 7: DATEDIFF function Exercise 8: Weekday or weekend?Exercise 9: Highlighter for multiple rows Exercise 10: Visualizations for exploratory analysis of trends Exercise 11: Discrete or continuous time analysis?Exercise 12: Discrete time analysis and Quick Table Calculations Exercise 13: Low usage trends Exercise 14: Weekly pattern by user type Exercise 15: Slicing and dicing Exercise 16: Weekday trends by gender and time of day Exercise 17: Bubble chart Exercise 18: Scheduling a promotional discount

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.

Exercise 1: Who are your customers?Exercise 2: Missing information Exercise 3: Exploring user data Exercise 4: Getting to know the Divvy users Exercise 5: Adding filters Exercise 6: Building a KPI dashboard Exercise 7: Formatting user KPIs Exercise 8: Creating a user dashboard Exercise 9: Enhancing the dashboard Exercise 10: The distribution of users Exercise 11: Choosing the right chart type Exercise 12: Visualizing distributions Exercise 13: Using a histogram Exercise 14: Using a line chart Exercise 15: Working with bins Exercise 16: Customizing the bin size Exercise 17: Exploring day pass user age

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.

Exercise 1: Mappatura interattiva dell’attività dei clienti nel tempo Exercise 2: Attività dei clienti in movimento Exercise 3: Visualizzare la concentrazione dell’attività Exercise 4: Il nuovo tipo di mark di densità di Tableau Exercise 5: Stratificazione e utilizzo totale dei moli Exercise 6: Suddividere la mappa Exercise 7: Migliorare la mappa Exercise 8: Sovrapporre le mappe Exercise 9: Calcoli rapidi di tabella per il ranking Exercise 10: Cosa va dove?Exercise 11: Combinare calcoli caratteristici e calcoli rapidi di tabella

Esercizio in corso

Exercise 12: Aggiungere dettagli senza creare rumore Exercise 13: Suddividere per tipo di utente Exercise 14: KPI e segmenti temporali Exercise 15: Visualizzare gli indicatori KPI della stazione Exercise 16: Dalle bolle alle ciambelle Exercise 17: Analizzare i nostri risultati

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.

Exercise 1: Groups Exercise 2: Groups for regions Exercise 3: Lasso selection Exercise 4: Editing groups Exercise 5: Creating seasonal groups Exercise 6: Seasons Exercise 7: Ranking dashboard Exercise 8: Embedding in the tooltip Exercise 9: Parameters and sets Exercise 10: Parameter characteristics Exercise 11: Parameters Exercise 12: Replacing rank with a parameter Exercise 13: Color by parameter Exercise 14: Sets Exercise 15: Set for windiness Exercise 16: Divvy trips and windiness Exercise 17: Divvy trips and temperature