Book Image

Tableau Cookbook - Recipes for Data Visualization

By : Shweta Sankhe-Savale
Book Image

Tableau Cookbook - Recipes for Data Visualization

By: Shweta Sankhe-Savale

Overview of this book

Data is everywhere and everything is data! Visualization of data allows us to bring out the underlying trends and patterns inherent in the data and gain insights that enable faster and smarter decision making. Tableau is one of the fastest growing and industry leading Business Intelligence platforms that empowers business users to easily visualize their data and discover insights at the speed of thought. Tableau is a self-service BI platform designed to make data visualization and analysis as intuitive as possible. Creating visualizations with simple drag-and-drop, you can be up and running on Tableau in no time. Starting from the fundamentals such as getting familiarized with Tableau Desktop, connecting to common data sources and building standard charts; you will walk through the nitty gritty of Tableau such as creating dynamic analytics with parameters, blended data sources, and advanced calculations. You will also learn to group members into higher levels, sort the data in a specific order & filter out the unnecessary information. You will then create calculations in Tableau & understand the flexibility & power they have and go on to building story-boards and share your insights with others. Whether you are just getting started or whether you need a quick reference on a “how-to” question, This book is the perfect companion for you
Table of Contents (18 chapters)
Tableau Cookbook – Recipes for Data Visualization
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Understanding Multiple Table Join across databases


In the previous recipe, we saw how to connect to a single database which was an Access file named Sample - Coffee Chain.mdb or Sample - CoffeeChain (Use instead of MS Access).xlsx and join multiple tables within it. There could also be instances where the data resides in multiple data sources. For example, the transactional sales data could be getting captured in, let's say, a SQL database and the yearly/monthly budgets are defined in Excel. In this situation, Excel is one data source and SQL is another data source. In order to see whether the targets were met or not, we would be required to get data from both Excel as well as SQL.

Cross-database Joins help us make Joins across multiple databases across a single data source, or multiple databases across multiple data sources.

Let us take a look at how we can do a cross-database join in the following recipe.

Getting ready

For this recipe, we use two of the six datasets which have been uploaded...