I’ve been working on getting certified for Tableau, one of the most well recognized Data Visualization Tools in Marketing and Data Analytics. A lot of the charts and graphs you see on the news and other media are developed with Tableau, along with internal reports and dashboards for major corporations, sales teams and finance.

I’m creating this as a study guide and to reinforce the knowledge before I take my Exam – super excited. It’s actually anticipated to be difficult because it involves a lot of memorization since I’ve taken the practice tests. But these are just more universal terms in Tableau and Data Science/Analytics in general, as that is what I felt I had the most difficulty with.

As I’ve described previously in my post, Finance and Data Analytics, I’ve always had a knack with the variables in a given problem. It has allowed me to devise the Emissions Tax Plan – Tableau will help me devise a more compelling story. Nothing can beat a good visual. Imagine being able to create and embed this.

Additionally, I’m looking at good Data Sources like Statista and USASpending.gov. Be sure to let me know if you got any more sources.

Tableau Definitions, Terms, Notes

If you’re gonna talk data science, visualization, marketing jargon and sound smart, you can throw out some cool terms with this. If you want to pass the Tableau Certification Test and make the big bucks, you have to actually understand the software and all of the terms and definitions.

Tableau Data Map - NH Obesity
Tableau Dashboard displaying a map and scatter plots for 3 different variables.

Tableau Basics Guide – Data Analytics/Marketing Notes

Tables: Yes, I know – this is basic stuff, but it actually tripped me up a lot. A data table is a number of columns and rows with individual fields of data. Think your typical spreadsheet. Tables show individual fields, or values, in a cross tab – X and Y axis.

Tableau Data Field – Each column of data from a table is a field

You cannot modify the source data with Tableau – including the name. However, you can change the metadata – name displayed, hide data from the view, organize in folders, .

Tableau Workbooks and Sheets are:

Worksheets – Build views of data by dragging and dropping on shelves.

Dashboard – Several views (worksheets) combined to present or monitor.

Story – A sequence of work sheets or dashboards used to tell a story and convey pertinent information.

Types of Layers in Tableau – New Data Modeling

Data is organized differently in Tableau now, starting with Tableau 2020.2 – data sources come in two different layers.

Physical Tables remain distinct.

Logical Tables are merged into a single, flat table. You must use relationships between two logical tables. You can only use joins with physical tables physical tables if contained in a logical table.

Types of Data Files in Tableau

Dimension – Independent variable field, produces headers when put into rows or column shelves. Qualitative, categorical data by default – dimension.

Measure – Dependent Variable, numerical, quantitative value dependent on one or more values.

Green Pill in Tableau – continuous field, Created the Axes

Blue Pill – Discrete, Dimensions

Meta Data – you can make edits from the Data Grid

Types of Tableau Files:

.tbwx file – Tableau Packaged  Workbook: complete Tableau file containing workbook and all external data

.tde file – Tableau Extract File – faster, can be used independent

.tds file – Tableau Data Source: data modeling including data types, fonts, colors, settings, or metadata

.twb file – Tableau workbook

Viz – a Tableau Visualization

Data Attributes

  • Folder structure
  • Measure and dimension conversions
  • Field data types (e.g., strings, integers, dates)
  • Field properties (e.g., how a field is displayed or aggregated)
  • Attributes (e.g., field names)

Dimensions – Field that is an independent variable, contains qualitative, categorically fixed data (breed, race, brand)

Measures – Field that is a dependent variable, typically produces Axis, quantitative (numeric) data (totals, sums, averages)

Tableau Bins – Create equal sized containers of data, used to display a specific range off data in a chart or graph. Cannot be calculated fields

Top N Field – “N” is user defined, will deliver the Top “N” Results , ex. Top 10,15, 25 records

Groups, Hierarchies, Relational Data

Calculated Fields, Calculations –

Box and Whisker Plots

Tables – Common Field Name

Append Data with Unions

3 ways to group data –

  1. Tableau Marks – Displays data using marks; every mark corresponds to a row or row group


2) Labels

3) Dimensions shelf.

Tableau Data Interpreter

Uses AI to clean up dirty data; only with Excel or .csv files. Cleans up extra columns, merged columns and headers.

Working With Large Data Sets in Tableau

Extracts work fast, and with up to billions of instances. When working with large sets of data, it’s best to use an extract over a live data set.

Types of Calculations

Table Calculations

Table calculations address direction.

Aggregated Fields

Aggregated and non-aggregated fields cannot be combined. They are calculated fields.

Tableau Extracts

Tableau Extracts are are subsets of data saved into a .tde file. They are great for working with large sets of data, and improve performance by working with only the important data you want to work with. They provide offline access to data and allow functions that aren’t available on full data sets.

Combining Data in Tableau

There are different ways to combine data in Tableau – the main four are Joins, Relationships, Blends and Unions.

Types of Joins in Tableau

There are 5 main types of Joins in Tableau –

Left Join – New table has all values from left table, and only matched from right table.

Inner Join – Combines tables into one that has matched values; un-matched dropped completely.

Full Outer Join – Contains all values from both tables, un-matched values have a null value.

Right Join  – New table has all values from right table, and only matched from left table.

Join Clauses – Determines which fields are used and how to complete a table join in Tableau. There are pre-determined clauses, or custom.

See more here.

What is a Tableau Union

Joins multiple tables from the same data source by using the wildcard search option. To do this – click New Union on the Data Source Tab in the bottom left of Tableau.

Union Data – appends rows from one table to another.

Blending Data – Displays two sources of data in one view

Differences Between Joins and Relationships

Relationships –  are a dynamic, flexible way to combine data from multiple tables for analysis. We recommend using relationships as your first approach to combining your data because it makes data preparation and analysis easier and more intuitive. Do not merge tables together. Handles nulls.

Relationships must be used between logical tables.

Joins – are a more static way to combine data. Joins must be defined between physical tables up front, before analysis, and can’t be changed without impacting all sheets using that data source. Joined tables are always merged into a single table.

Learn more here.

Types of Tableau Filters

Data Source Filter – restricts users from seeing certain types of data

Extract Filter – Pre-Condition filters before the extract

Context Filter – Discrete, create a filter to be applied first, create a dependent numerical or Top N filter

Measure Filter – Aggregate data such as sum, average

How to create Tableau Filters

Quick Filters –

Logical Tables –

Physical Tables –

Quick Table Calculation

Types of Charts

Area charts

Pareto chart –

Bar chart – Requires two data sources

Box plot

Line chart

Scatter plot

Histogram – Requires only one data source

Bullet Graph – Bar market with additional information that shows progress towards a goal, uses two measures

Aggregation – SUM, MIN, MAX, AVG, COUNT

Measure, measure field


Discrete Dimension

Aggregated Measure

Sets – Custom Fields that define a subset of data – compare and ask questions about a subset of data.

Dynamic Sets only on one dimension

Calculated Fields –

Difference between measures and fields –

dual axis chart – Combining multiple axis charts

Parameter – Float, Integer, String – Single select only.

concatenate – connect or link together

Great Data Sources for Tableau

Tableau Map display on EmissionsTax.org?

I’ve actually been compiling my own data for www.ScrubMoney.com, and am going to be releasing a really cool stock data visualization. I started by doing the donkey work and manually entering the data for individual stocks into an Excel spreadsheet.

Then, I added some basic formulas and I have a pretty nifty spreadsheet. Finally, I put the data in Tableau and made some basic visualizations. Whats cool is I have a live snapshot of the data from December of 2021, and then just updated the data – that will create something really cool.

If I had a live connection to this data would be best, like a broker account or trading desk. Please let me know if you have the info on that. If not – just sign up for the newsletter at the top right of every page here.

In a completed project, I got data from Trading Economics, put it in a spreadsheet, did a simple calculation for GDP Per Capita, then loaded it up to Tableau. This is called Pollution and GDP Per Capita on EmissionsTax (my environmental website).

I don’t have the pollution data yet, however, you can see the correlation by using knowledge most people have.

Other Data Sources and Tips

As I mentioned at the beginning of this guide, Statista and USASpending.gov are great places from my understanding. Basically any place you can find data in a .csv or Excel file, and therefore, you can turn it into a data visualization.

WorldoMeters.info has some pretty crazy stuff.

The art comes from telling the story through that visualization and showing the meaning.

Rather than make this Tableau Study Guide perfect, what makes it the best is it will continue to be updated. Find I’m missing info or got something wrong?

Have a question that isn’t here or clear? Hit me up or leave a comment bellow!