Tableau

Common problems encountered in Tableau

This section of common problems will be detailed soon.

For now, check out the references below.

References

General concepts

• Tableau Concepts

• Begin by structuring and readying your data for analysis - Data preparation is the process of getting well formatted data into a single table or multiple related tables so it can be analyzed in Tableau. This includes both the structure, i.e. rows and columns, as well as aspects of data cleanliness, such correct data types and correct data values.

Tableau fundamentals

• Parts of the view - This section describes the basic elements of views that you can create in Tableau.

A. Field Labels - The label of a discrete field added to the row or column shelf that describes the members of that field. For example, Category is a discrete field that contains three members; Furniture, Office Supplies and Technology.

B. Titles - The name that you give your worksheet, dashboard, or story. Titles display automatically for worksheets and stories and you can turn them on to display them in your dashboards.

C. Marks - The data that represents the intersection of the fields (dimensions and measures) included in your view. Marks can be represented using lines, bars, shapes, maps and so on.

D. Legends - A key that describes how the data is encoded in your view. For example if you use shapes or colors in your view, the legend describes what each shape or color represents.

E. Axes - Created when you add a measure (fields that contain quantitative, numerical information) to the view. By default, Tableau generates a continuous axis for this data.

F. Headers - The member name of a field.

G. Captions - Text that describes the data in the view. Captions can be automatically generated and can be toggled on and off.

Quick overview of the View area in Tableau. More details on the actual resource reference.

• Dimensions and Measures (Blue and green)

  • Dimensions contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view.

  • Measures contain numeric, quantitative values that you can measure. Measures are aggregated by default. When you drag a measure into the view, Tableau applies an aggregation on the pill.

• Data types

Data types in Tableau

• Tableau's order of operations

• Data aggregation in Tableau - In Tableau, you can aggregate measures or dimensions, though it’s more common to aggregate measures. Whenever you add a measure to your view, an aggregation is applied to that measure by default.

Data Processing

• Functions in Tableau or by category- Tableau supports many functions for use in Tableau calculations.

• Creating calculated fields - Sometimes your data source does not contain a field (or column) that you need for your analysis. If this is the case, you can create a calculated field using data from the existing fields.

• Handling averages and weighted averages - How to calculate weighted averages in order to compare the results from using a weighted average versus an unweighted average to summarize the data?

• Blending your data - Data blending is a method for combining data from multiple sources. Data blending brings in additional information from a secondary data source and displays it with data from the primary data source directly in the view.

Data interactivity

• Creating parameters - A parameter is a workbook variable such as a number, date, or string that can replace a constant value in a calculation, filter, or reference line.

Data Presentation and Analysis

• Building Charts and Analyzing Data - Discover the various features at your disposal as you build views, and learn the basic skills you need to create elegant, insightful views, dashboards, and stories.

• Mapping Concepts in Tableau - Like any other type of visualization, geographical data presented in maps serve a particular purpose: they answer spatial questions.

• Crafting Dashboards - In Tableau, a dashboard is a collection of several views, letting you compare a variety of data simultaneously.

• Crafting Stories - In Tableau, a story is a sequence of visualizations that work together to convey information. You can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case.

• Best practices in visualization - The fonts, colors, shading, alignment, borders, and grid lines in your visualization are important parts of both your analysis and the story you're telling.