***Now Upgraded to Tableau Desktop v9***
This course helps you to master all the basics of Tableau Desktop software quickly and easily. It is aimed at anyone who wants to be able to use this award winning product to analyse and visualize data - both experts and non-experts.
The course is organised into 20 step by step lessons, with a duration of three hours in total.
It covers all the major components and functions of the software, with all the steps needed to build data visualizations and publish dashboards.
Lessons include supplementary notes and we've also added in some quizzes to check and reinforce key information.
We're sure this course will give you the know-how and confidence to be able to use Tableau Desktop in your projects and create some amazing and insightful data visualizations and dashboards.
This introductory lecture welcomes you to our course and gives a brief overview of the course content and what to expect.
This lecture goes into more detail about the course content and outlines the course prerequisites. At the end of this lecture, please follow the instructions below to install Tableau Desktop. We've supplied instructions for both PC and Mac.
Also, this is where you will find datasets (Excel files) which are used in exercises throughout the course.
In this lecture, we'll take a brief look at the Tableau Family of Products. By the end, you'll know where Tableau Desktop fits within the Tableau suite and you'll have an understanding of the purpose of the other products.
In this lecture, we'll begin by having a look at the large array of data connections that Tableau supports and then walk you through connecting to a file based data source. We'll also touch on workaround options should Tableau not support a particular data connection out-of-the-box.
In this unit, we'll show you how to connect to structured data sources such as Microsoft SQL Server or Oracle. We'll also introduce you to the Data Window which is an easy-to-use and powerful feature of Tableau Desktop allowing you to select, filter and join tables to source your data from.
At the end of this lecture, you will have a firm understanding of how to go about connecting Tableau Desktop to a Cloud or API (Application Programming Interface) based data source such as Google BigQuery.
In this lecture, we'll take a comprehensive look at the many ways we can combine data sources together. After a brief look at joining data sources outside of Tableau, we'll look at the ways we can do this within Tableau as well. At the end of this lecture, you will have a firm understanding of the different options Tableau offers to combine data and when to use them.
In this lecture we will look at the difference between Measures and Dimensions, the difference between Discrete and Continuous data as well as the types of data fields available in Tableau such as numbers, strings, and dates. We'll see that Tableau lets you define various properties of data fields which change the way Tableau represents them in our data visualizations.
Filtering is the key tool which is used to focus on a specific area or subset - particularly when we're dealing with a large and/or complex dataset. This lecture will show you how to go about filtering in Tableau Desktop. At the end of this lecture, you will learn about the different ways to filter the data both at the data source level as well as within the workbook itself.
In this unit, we'll look at some additional data operations which you can use to further manipulate and organise your data. Specifically, we'll focus on Sorting, Grouping, Hierarchies and Sets.
In this lecture, we have a look at several different file types specific to Tableau. We demonstrate how to create and use Tableau Extract within your workbook and explain what Tableau Data Source and Tableau Packaged Data Source file types are used for.
Dates are one of the most common fields used in data analysis. This lecture explains the difference between using a date as a discrete field and as a continuous field. It also looks at different properties of date fields and what you can do with them.
In this lecture we take a little break from Tableau to discuss the definition and goals of data visualization and what should we be aiming for when creating them. We also look at the types of data visualizations Tableau provides.
Tableau provides a large number of formatting options. In this lecture we set some ground rules for formatting and then have a look at examples of formatting tables and charts using options available in Tableau.
One of the great features of Tableau is its seamless integration of location based reporting. In this lecture we look at the different mapping options Tableau provides out of the box as well as creating your own custom geographic roles.
Using parameters can make your dashboards interactive and allow end users to drive the analysis in the dashboard. In this lecture we look at simple "what if" and "top n" examples and how to use parameters in order to make them dynamic.
This lectures shows how you can extend your incoming datasets using calculated fields, tableau in-built functions and table calculations.
In this lecture we take you through some rules for creating dashboards and go over all the necessary steps for building a simple dashboard in Tableau.
Actions are used to make your dashboards dynamic. They guide users to explore and interact with data. This lecture shows you how to implement different actions within your dashboard.
In this final lecture we look at the available options for publishing your dashboards. We also walk you through publishing onto the Tableau Public, the free hosting option for your dashboards.
I am a Senior Business Intelligence Consultant working in Melbourne, Australia. I have close to 20 years of experience in IT, many years consulting on projects in areas of data warehousing, business intelligence and analytics. I've run a number of internal courses within our consulting firm as well as courses for our clients. I enjoy teaching and helping others. I also have a team of other consultants who are happy to assist in preparing material for Udemy courses.