Data Visualization with Tableau Literacy

  • 30m
  • 20 questions
The Data Visualization with Tableau Literacy benchmark will measure your ability to recall and relate to the underlying data visualization concepts in Tableau. You will be evaluated on your ability to recognize the foundational concepts of data visualization in Tableau such as handling data sources, working with data and fields, creating basic visualizations, and best practices. A learner who scores high on this benchmark demonstrates that they have the basic skills for data visualization using Tableau.

Topics covered

  • adjust data sources and connections in a Tableau workbook
  • connect to a desktop source and use single tables and multiple tables to extract data into Tableau Data Engine
  • connect to a Microsoft SQL Server database, select tables, and directly connect to the data to enable working with live data
  • connect to multiple data sources and use the relationship tool to demonstrate automatic data blending in Tableau
  • create a basic view to explore data in Tableau Desktop
  • create a histogram to show data distribution
  • create and customize worksheets in a Tableau workbook
  • create scatter plots and trend lines to visualize and compare relationships between numerical variables
  • create vertical and horizontal bar charts to compare data across identified categories
  • demonstrate how to use a custom SQL query with a database to extract data into the Tableau Data Engine
  • demonstrate managing data types for columns in Data Source page
  • describe the purpose of shelves, cards, and marks when building visualizations in Tableau Desktop
  • filter data from the connected data source via the Tableau Data Source Page
  • find and manage fields in Data pane
  • import worksheets, dashboards, and workbook contents into a file in Tableau Desktop
  • replace data sources from the Data Source Page and worksheet view in Tableau Desktop
  • save Tableau workbooks and data sources using TWB and TDS formats
  • sort and group fields in the Data pane
  • use the pivot tool to prepare data for extraction into the Tableau Data Engine
  • work with Data Interpreter to identify data anomalies and clean up data

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