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Learning Tableau 2022
Learning Tableau 2022

Learning Tableau 2022: Create effective data visualizations, build interactive visual analytics, and improve your data storytelling capabilities , Fifth Edition

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Learning Tableau 2022

Connecting to Data in Tableau

Tableau offers the ability to connect to nearly any data source. It does this with a unique paradigm that leverages the power and efficiency of existing database engines (for example, Snowflake or SQL Server) or alternatively extracts the data locally.

We’ll look at relating tables of data together using joins, blends, unions, and the object model in Chapter 14, Understanding the Tableau Data Model, Joins, and Blends. In this chapter, we’ll focus on essential concepts of how Tableau connects to and works with data more broadly. We’ll cover the following topics:

  • The Tableau paradigm
  • Connecting to data
  • Managing data source metadata
  • Working with extracts instead of live connections
  • Using sets and groups
  • Filtering data

We’ll start by gaining an understanding of the underlying paradigm of how Tableau works with data.

The Tableau paradigm

The unique and exciting experience of working with data in Tableau is a result of VizQL (Visual Query Language).

VizQL was developed as a Stanford University research project, focusing on the natural ways that humans visually perceive the world and how that could be applied to data visualization. We naturally perceive differences in size, shape, spatial location, and color. VizQL allows Tableau to translate your actions, as you drag and drop fields of data in a visual environment, into a query language that defines how the data encodes those visual elements. You will never need to read, write, or debug VizQL. As you drag and drop fields onto various shelves defining size, color, shape, and spatial location, Tableau will generate the VizQL behind the scenes. This allows you to focus on visualizing data, not writing code!

One of the benefits of VizQL is that it provides a common way of describing how the arrangement of various fields in a view defines a...

Connecting to data

There is virtually no limit to the data that Tableau can visualize! Almost every new version of Tableau adds new native connectors. Tableau continues to add native connectors for cloud-based data. The web data connector allows you to write a connector for any online data you wish to retrieve. The Tableau Hyper API allows you to programmatically read and write extracts of data, enabling you to access data from any source and write it to a native Tableau format. Additionally, for any database without a built-in connection, Tableau gives you the ability to use a generic ODBC connection.

You may have multiple data sources in the same workbook. Each source will show up under the Data tab on the left sidebar.

Although the terms “data connection” and “data source” are often used interchangeably, it is helpful to make a distinction. A connection technically refers to the connection made to data in a single location, such as tables...

Managing data source metadata

Data sources in Tableau store information about the connection(s). In addition to the connection itself (for example, database server name, database, and/or filenames), the data source also contains information about all the fields available (such as field name, data type, default format, comments, and aliases). Often, this data about the data is referred to as metadata.

Right-clicking a field in the data pane reveals a menu of metadata options. Some of these options will be demonstrated in a later exercise; others will be explained throughout the book. These are some of the options available via right-clicking:

  • Renaming the field
  • Hiding the field
  • Changing aliases for values of a non-date dimension
  • Creating calculated fields, groups, sets, bins, or parameters
  • Splitting the field
  • Changing the default use of a date or numeric field to either discrete or continuous
  • Redefining the field as a dimension or...

Working with extracts instead of live connections

Nearly all data sources allow the option of either connecting live or extracting the data. A few cloud-based data sources require an extract. Conversely, OLAP data sources cannot be extracted and require live connections.

Extracts extend the way in which Tableau works with data. Consider the following diagram:

Figure 2.19: Data from the original data source is extracted into a self-contained snapshot of the data

When using a live connection, Tableau issues queries directly to the data source (or uses data in the cache, if possible). When you extract the data, Tableau pulls some or all of the data from the original source and stores it in an extract file. Prior to version 10.5, Tableau used a Tableau Data Extract (.tde) file. Starting with version 10.5, Tableau uses Hyper extracts (.hyper) and will convert .tde files to .hyper as you update older workbooks.

The fundamental paradigm of how Tableau works with data...

Using sets and groups

Sets and groups are related concepts in Tableau and both allow you to group related data together. In both cases, the grouping is defined in Tableau rather than at the source.

A group is a combination of values from one or more dimensions. For example, with the four regions Central, East, South, and West, you might choose to create two groups: East-Central and South-West. This would allow you to make new comparisons and find new insights at higher levels of geography than you might have previously. You can create a group using the context menu for a field by selecting Create | Group.

That will open a dialog box that allows you to define the groups, like this:

Graphical user interface, text, application, email  Description automatically generated

Figure 2.25: The Create Group dialog box allows you to group together values for a given dimension

The result is a field, Region (group), that you can use as you would any other dimension in your data.

You can also create ad-hoc groups by selecting marks in your visulalizations...

Filtering data

Often, you will want to filter data in Tableau in order to perform an analysis on a subset of data, narrow your focus, or drill into details. Tableau offers multiple ways to filter data.

While you may apply any number of filters to any given view, if you want to limit the scope of all your analysis to a subset of data, you can filter the data at the source using one of the following techniques:

  • Data source filters are applied before all other filters and are useful when you want to limit your analysis to a subset of data.
  • Extract filters limit the data that is stored in an extract (.tde or .hyper). Data source filters are often converted into extract filters if they are present when you extract the data.
  • Custom SQL filters can be accomplished using a live connection with custom SQL, which has a Tableau parameter in the WHERE clause. We’ll examine parameters in Chapter 4, Starting an Adventure with Calculations and Parameters.
...

Summary

This chapter covered key concepts of how Tableau works with data. Although you will not usually be concerned with what queries Tableau generates to query underlying data engines, having a solid understanding of Tableau’s paradigm will greatly aid you as you analyze data.

We looked at multiple examples of different connections to different data sources, considered the benefits and potential drawbacks of using data extracts, considered how to manage metadata, and considered options for filtering data.

Working with data is fundamental to everything you do in Tableau. Understanding how to connect to various data sources, when to work with extracts, and how to customize metadata will be key as you begin deeper analysis and more complex visualizations, such as those covered in Chapter 3, Moving Beyond Basic Visualizations.

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Key benefits

  • Learn the basics of data analysis, from snappy visualizations to comprehensive dashboards
  • Gain meaningful insights with geospatial analysis, scripting extensions, and other advanced methods
  • Explore the latest Tableau 2022 features, including Einstein Discovery and Explain Data

Description

Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau’s latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You’ll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources with Tableau’s Data Model capabilities, along with maps and geospatial visualization. You will further use Tableau Prep Builder’s ability to efficiently clean and structure data. By the end of this book, you will be proficient in implementing the powerful features of Tableau 2022 to improve the business intelligence insights you can extract from your data.

Who is this book for?

This Tableau book is for aspiring BI developers and data analysts, data scientists, researchers, and anyone else who wants to gain a deeper understanding of data through Tableau. This book starts from the ground up, so you won’t need any prior experience with Tableau before you dive in, but a full Tableau license (or 14-day demo license) is essential to be able to make use of all the exercises.

What you will learn

  • Develop stunning visualizations to explain complex data with clarity
  • Build interactive dashboards to drive actionable user insights
  • Explore Data Model capabilities and interlink data from various sources
  • Create and use calculations to solve problems and enrich your analytics
  • Enable smart decision-making with data clustering, distribution, and forecasting
  • Extend Tableau's native functionality with extensions, scripts, and AI through CRM Analytics (formerly Einstein Analytics)
  • Leverage Tableau Prep Builder's amazing capabilities for data cleaning and structuring
  • Share your data stories to build a culture of trust and action
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Publication date : Aug 26, 2022
Length: 568 pages
Edition : 5th
Language : English
ISBN-13 : 9781801072328
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Publication date : Aug 26, 2022
Length: 568 pages
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Table of Contents

19 Chapters
Taking Off with Tableau Chevron down icon Chevron up icon
Connecting to Data in Tableau Chevron down icon Chevron up icon
Moving Beyond Basic Visualizations Chevron down icon Chevron up icon
Starting an Adventure with Calculations and Parameters Chevron down icon Chevron up icon
Leveraging Level of Detail Calculations Chevron down icon Chevron up icon
Diving Deep with Table Calculations Chevron down icon Chevron up icon
Making Visualizations that Look Great and Work Well Chevron down icon Chevron up icon
Telling a Data Story with Dashboards Chevron down icon Chevron up icon
Visual Analytics: Trends, Clustering, Distributions, and Forecasting Chevron down icon Chevron up icon
Advanced Visualizations Chevron down icon Chevron up icon
Dynamic Dashboards Chevron down icon Chevron up icon
Exploring Mapping and Advanced Geospatial Features Chevron down icon Chevron up icon
Integrating Advanced Features: Extensions, Scripts, and AI Chevron down icon Chevron up icon
Understanding the Tableau Data Model, Joins, and Blends Chevron down icon Chevron up icon
Structuring Messy Data to Work Well in Tableau Chevron down icon Chevron up icon
Taming Data with Tableau Prep Chevron down icon Chevron up icon
Sharing Your Data Story Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(29 Ratings)
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4 star 6.9%
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1 star 3.4%
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Ervin Vinzon Sep 04, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
What I love about this book is the way the author explains how the level of detail and table calculations work by giving examples that are easy to absorb and understand. I also like the chapters about dynamic dashboards and advanced tableau features which you cannot find in other books. The discussion about data prep, data blends, and data relationships is very helpful to tableau developers. Overall this book is complete from the basics to advanced topics to learn and understand tableau.
Amazon Verified review Amazon
Iko Tumangan Oct 10, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Josh Milligan is an absolute pro, and explains everything tableau in a clear and concise way! It's a pleasant read and covers essential topics along with 'how to' examples. I recommend this learning resources for anyone who is beginning to use tableau as their analytics and reporting tool of choice.
Amazon Verified review Amazon
WJCarpenter Nov 28, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(Background: I read an early review copy of this. It's an update to previous editions. I haven't read those earlier editions and evaluated this as a standalone work. This is an end-user book, not aimed at developers or administrators of Tableau systems.)This book starts with the basics and slowly builds up to fairly sophisticated techniques for doing visualizations using Tableau. If you are a Tableau beginner, this is a great way to learn to use it at your own pace. If you already have some Tableau experience, I'll bet there will be things in here that are either new to you or that you have kind of forgotten about. I know that was true for me.If you are a beginner, I recommend that you stay in Chapter 1 until you feel completely comfortable with all the things he describes in that introduction. Like pretty much any sophisticated tool, there is some terminology that you will find it best to have burned into your brain cells to make the rest of the material easier to take in. Not that it's hard; it's just that it may be new ground for you, and you don't want to be bothered with trying to remember that sort of stuff when you are really trying to digest some larger concept. He does a good job of explaining what you need to know for the rest of the book, so don't skip it thinking it's a lightweight introduction.One of the things I like best about this book, besides its thorough coverage of the topic, is that the author goes beyond merely explaining how to do various things. He explains why you would or would not make various choices. This is the creative part of storytelling with data, and he's interested in having you accomplish your storytelling goals rather than just presenting visual facts from the data.
Amazon Verified review Amazon
Zach B Sep 16, 2022
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Milligan is well known in our field (data visualization) and is the perfect author for this topic. Whether it be Tableau-specific tips, tricks, and fundamentals or greater data viz theory that you can carry on to your practice with other tools, this is an incredibly effective book for new and intermediate Tableau analysts.Packt gave me an advanced review copy of this to read, and before I knew who the author was I was skeptical. Packt is known for their "spray and pray" approach to authors, where they solicit widly and heavily often asking if people are interested in authoring on topics they're unfamiliar with (I was asked if I would write a book on AI of which I know nothing.)In this case, that fear is unfounded. Josh is widely known and respected in the Tableau community, being part of the Zen Master (Tableau's most elite users) 5x.If you're interested in a starting place with Tableau or elevating your skills from beginner, this is a wonderful place to start.
Amazon Verified review Amazon
Md Faisal Akbar Aug 26, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The "Learning Tableau 2022 by author and zen master Joshua N. Milligan" covers all the fundamentals and advanced concepts of Tableau with lots of practical examples. In the first chapter author walkthrough you through connecting data to create a complete dashboard with basic tableau foundational concepts. Then he deep-dived into each concept in detail in a conversational fashion and he followed the 5W1H (who, what, where, when, why, how) method to describe most of the tableau concepts, especially in visualization, lod, and table calculations.He guides you and diving deep into connecting to different databases, live vs extract connection, performance, filtering, order of operations, basic and advanced visualization, four main types of calculations (row-level, aggregate, lod, table calculations), parameters, various formatting, tooltip, interactive and dynamic dashboards, visual analytics (distributions, trend, clustering, forecasting), mapping and advanced geospatial, extensions, scripts, AI, tableau data models, join and blend, how to work with and clean messy data using tableau desktop and tableau prep and showed different ways of sharing data stories with lots of tips and tricks and tableau shortcuts.After reading this book, you will have a solid understanding of tableau and it will improve your data and visualizations skill.
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