You will learn how to use the data viewer screen, how to pre-filter your data to help performance, when to use or not to use a Tableau extract, and how to alter data types and check your data before loading into Tableau.

You will see all of the different data sources that Tableau has the ability to connect to, and learn how to connect to data to load it into Tableau.

Tableau has excellent functionality for map building. You will learn how to use Longitude and Lattitude measures to build maps, and how to leverage Tableau’s smart capabilities to build maps instantly from geographically relevant data. You will also learn how to display information effectively on a map, and several different ways of doing so.

Bar charts are the backbone of visual analysis. You will learn how to easily create bar charts in Tableau that can be used to quickly see variation across values. You will also learn how to build comparative bar charts with equivalent axes to allow you to see data variation across values and variables, spot outliers, and understand trends.

Scatter plots are essential to understanding correlations, trends, relationships, and their significance, of quantitative variables. You will learn how to create scatter plots easily in Tableau, how to de-aggregate data points, and how to interpret these charts.

You will learn how to easily add trend lines to scatter plots in Tableau so you can see the direction and strength of a relationship between variables, and how to perform multivariate trend analysis in one chart.

Getting data types right is critical to do accurate analysis. You will learn what the different data types are that Tableau understands, what their differences are, and when to use them.

Dimensions and measures are the two fundamental categories of variables available in Tableau, and they have important differences. You will see how each is used for different kinds of analysis, and how changing a dimension to a measure and visa versa can alter the kinds of analysis you can perform.

Continuous and discrete are two ways of interpreting how variable functions, and there are important implications here about what you will get from analysis or visualization. You will learn the difference between the two, and why you would select one or the other for certain types of analyses.

The calculated field functionality in Tableau is extremely powerful. You will learn the basics of how it works, and you will create calculated fields to aid in analysis. You will learn how to use the calculated field editor, how to do complex if-then heuristics, and check your calculations to ensure their validity.

You will learn both how to quickly group qualitative variables to help see insights as well as how to perform calculated aggregations (including summations, average, etc.) on quantitative variables to be able to understand the data appropriately

You will learn how to add variables to Tableau in a hierarchal way to be able to see insights faster and easier, and how to use Tableau’s built-in hierarchy functionality to organize your dimensions for quick reference, as well as for drill-downs.

Sorting is a simple but powerful feature of Tableau. You will learn how to use sorting functionality to quickly understand how the data moves, and how sorting can be used across variables pull out insights.

Good formatting and design are often overlooked elements of visual analytics, but they are absolutely essential to the success of data visualization. Good design will allow the message and insights of your data to be communicated effectively, without which nothing ever happens. You will learn the principles of good formatting and design in Tableau.

One of the most important features of Tableau is the ability to bring together several data visualizations into a single dashboard to get an overview of everything. Dashboarding in Tableau is extremely powerful and feature-rich. We will dive into the basics of Tableau dashboarding so you will be able to create well designed, insightful dashboards by the end of the course.

Somewhat of an underused, hidden gem in Tableau, the tooltip is extremely powerful. If designed well, it can give you deep and rich insight into your visualizations with hover-over details necessary for good interpretation and exploration of the data. We will teach you how to design your tooltips for rich insights and ad-hoc analysis.

Another aspect of good design, labeling and annotations are often overlooked, but necessary features in analysis to be able to present to others and ensure they get the proper insights from the data visualization. You will learn how to effectively use these tools.

You will learn how to use data highlighting capabilities in Tableau to perform powerful ad-hoc analyses and answer questions of your data in real-time.

An absolutely essential element of analysis, Tableau gives you extremely feature-rich data filtering capabilities. You will learn how to use filtering to drill into both quantitative and qualitative variables, to remove confounding variables, and to allow for exploration of the data in real-time.

Often times, simple heuristics can be used in data visualization to get to insight very quickly, without having to do more robust and advanced analytical methods. In business, this is important, because it saves both time and money, and often produces the same or very similar results to more advanced methods. You should always start with a heuristic before moving on to more expensive methods. You will learn how to use basic heuristical thinking and how to implement them in Tableau.

You will learn how to spot and remove confounding variables in your analysis, to ensure the insight you are getting is clean and accurate.

Throughout this course you will learn good practices of analysis, how to ask the right questions, check assumptions, and build views that drive insight. Solid analysis skills are at the heart of professional data visualization.