Learning tableau 2019 tools for business intelligence, data prep, and visual analytics

Chapter 2, Working with Data in Tableau, focuses on essential concepts of how Tableau works with data.. Chapter 4, Starting an Adventure with Calculations, focuses on laying a foundation

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Contributors

Joshua N Milligan is a five-time Tableau Zen Master, the highest

recognition of excellence from Tableau Software for masters and teachers

of Tableau and collaborators within the community He was one of threeIron Viz Global finalists in 2017 He is passionate in serving others

through data visualization and analytics As a consultant with Teknion

Data Solutions since 2004, he has extensive real-world experience across

many industries In addition to authoring every edition of Learning

Tableau, he was a technical reviewer for Tableau Data Visualization Cookbook and Creating Data Stories with Tableau Public He shares

Tableau and Tableau Prep tips on VizPainter and his Twitter handle is

@VizPainter He lives with his family in Tulsa

Dmitry Anoshin is an expert in the field of analytics with 10 years of

experience He started using Tableau as a primary BI tool in 2011 in hisrole as a BI consultant for Teradata He is certified with both TableauDesktop and Server He leads probably the biggest Tableau user

community with more than 2,000 active users This community has 2-3Tableau talks every month, headed by the top Tableau experts, TableauZen Masters, and Viz Champions In addition, Dmitry has previouslywritten three books with Packt and reviewed a further seven Finally, he is

an active speaker at data conferences and helps to adopt cloud analytics

Chapter 1, Taking Off with Tableau, introduces the foundational principles

of Tableau We'll go through a series of examples that will introduce thebasics of connecting to data, exploring and analyzing the data visually, andfinally putting it all together in a fully interactive dashboard

Chapter 2, Working with Data in Tableau, focuses on essential concepts of

how Tableau works with data You will look at multiple examples of

different connections to different data sources, consider the benefits andpotential drawbacks of using data extracts, consider how to manage

metadata, dive into details on joins and blends, and finally, take a look atoptions for filtering data

Chapter 3, Venturing on to Advanced Visualizations, explores how to create

the various types of views and how to extend basic visualizations using avariety of advanced techniques such as simple calculations, jittering,

multiple mark types, and dual axis Along the way, we will also coversome details on how dates work in Tableau

Chapter 4, Starting an Adventure with Calculations, focuses on laying a

foundation and also gives a number of practical examples, by means ofwhich you will understand the key concepts behind how calculations work

Chapter 6, Making Visualizations that Look Great and Work Well, explains

how formatting works in Tableau, giving you the ability to refine the

effective communication of your data story

Chapter 7, Telling a Data Story with Dashboards, demonstrates

how Tableau allows you to bring together related data visualizations in asingle dashboard This dashboard could be a static view of various aspects

of the data, or a fully interactive environment, allowing users to

dynamically filter, drill down, and interact with the data visualizations Inthis chapter, you will take a look at most of these concepts within thecontext of several in-depth examples, where you will walk through the

dashboard design process step by step.

Chapter 8, Digging Deeper – Trends, Clustering, Distributions, and

Forecasting, explains how Tableau enables you to quickly enhance your

data visualizations with statistical analysis Built-in features, such as trendmodels, clustering, distributions, and forecasting, allow you to quickly addvalue to your visual analysis You will take a look at these concepts in thecontext of a few practical examples using some sample datasets

Chapter 9, Cleaning and Structuring Messy Data, focuses on a number of

principles for structuring data to work well with Tableau, as well as somespecific examples of how to address common data issues

Chapter 10, Introducing Tableau Prep, works through a practical example as

we explore the paradigm of Tableau Prep, enabling the reader to

understand the fundamental transformations and see many of the featuresand functions of Tableau Prep

Chapter 11, Advanced Visualizations, Techniques, Tips, and Tricks, explains

a number of advanced techniques in a practical context You'll learn thingssuch as creating advanced visualizations, dynamically swapping views on

a dashboard, using custom images, and advanced geographic

visualizations

Chapter 12, Sharing Your Data Story, explains how Tableau enables you to

share your work using a variety of methods In this chapter, we'll take alook at the various ways to share visualizations and dashboards, along

with what to consider when deciding how you will share them.

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INCLUDE

EXCLUDE

Level of detail example

Linear

Tall data

Wide and tall in Tableau

Good structure – star schemas (Data Mart/Dat

Union files together Cross database joins

Connecting to data Cleaning the data

Ad hoc custom territories

Publishing to Tableau Server and Tableau Online

Interacting with Tableau Server

Leave a review - let other readers know what you think

What is it about Tableau that inspires an ever growing community to hold

up signs that read I ♥ Tableau and excitedly share data visualizations on

social media? Why do so many organizations turn to Tableau as the goldstandard for visual analytics? How can an analytics platform be so fun,engaging, and useful all at once?

Tableau disrupted the paradigm for visually interacting with data It made

it easy and intuitive (and fun!) to be hands-on with the data, to receiveinstant visual feedback with every action, and to ask questions and

uncover insights in a natural flow of thought and interaction And

Tableau continues to expand and evolve in ways that make seeing andunderstanding data easier and more powerful New features such as SetActions, geospatial support, and new statistical models expand the

analysis that's possible Transparency, density maps, new color palettes,and formatting options greatly enhance the visual story you can tell The

introduction of Tableau Prep brings the same intuitive instant feedback to

data prep and cleansing that Tableau Desktop brought to data

visualization We'll cover these new features (and more) in the chapters ofthis book!

We'll look at Tableau through the lens of understanding the underlyingparadigm of how and why Tableau works in the context of practical

examples And then we'll build on this solid foundation of understanding

so that you will have the requisite tools and skills to tackle even the

toughest data challenges!

This book is for anyone who needs to see and understand their data! From

the casual business user to the hardcore data analyst, everyone needs tohave the ability to ask and answer questions of data Having a bit of

background with data will definitely help, but you don't need to knowscripting, SQL, or database structures Whether you're new to Tableau orhave been using it for months or even years, you'll gain a solid foundationfor understanding Tableau and possess the tools and skills to build towardadvanced mastery of the tool

book

This book does not assume any specific database knowledge, but it

definitely will help to have some basic familiarity with data itself We'llcover the foundational principles first, and while it may be tempting toskip the first chapter, please don't! We'll lay a foundation of terminologyand the paradigm that will be used throughout the remainder of the book

currently have a license

files

For most chapters, you'll find applicable data files (Excel and text files)and a set of Tableau Workbook files, (.twbx) , or Tableau Flow files, (.tfl) , which

finished example

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The code bundle for the book is also hosted on GitHub at https://github.com/ PacktPublishing/Learning-Tableau-2019 In case there's an update to the code, itwill be updated on the existing GitHub repository

We also have other code bundles from our rich catalog of books and

videos available at https://github.com/PacktPublishing/ Check them out!

We also provide a PDF file that has color images of the

screenshots/diagrams used in this book You can download it here: https:// www.packtpub.com/sites/default/files/downloads/9781788839525_ColorImages.pdf

There are a number of text conventions used throughout this book

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Data menu."

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Foundations

This section lays the foundations for data visualization in Tableau Itprovides an overview of the interface and terminology, explains dataconnections, and covers a wide variety of visualization types

This section consists of the following chapters:

Chapter 1, Taking Off with Tableau

Chapter 2, Working with Data in Tableau

Chapter 3, Venturing on to Advanced Visualizations

When you first encounter a dataset, often the first thing you see is the rawdata—numbers, dates, text, field names, and data types Almost certainly,there are insights and stories that need to be uncovered and told, decisions

to make, and actions to take But how do you find the significance? How

do you uncover the meaning and tell the stories that are hidden in the data?

Tableau is an amazing platform for seeing, understanding, and making

key decisions based on your data! With it, you will be able to achieveincredible data discovery, data analysis, and data storytelling You'll

This chapter introduces the foundational principles of Tableau We'll gothrough a series of examples that will introduce the basics of connecting todata, exploring and analyzing the data visually, and finally putting it alltogether in a fully interactive dashboard These concepts will be developedfar more extensively in subsequent chapters But don't skip this chapter, as

it introduces key terminology and key concepts, including the following:

The cycle of analytics

Connecting to data

As someone who works with and seeks to understand data, you will findyourself working within the cycle of analytics This cycle might be

illustrated as follows:

Tableau allows you to jump to any step of the cycle, move freely betweensteps, and iterate through the cycle very rapidly With Tableau, you havethe ability to do the following:

Data discovery: You can very easily explore a dataset using

Tableau and begin to understand what data you have visually

Data preparation: Tableau allows you to connect to data from

many different sources and, if necessary, create a structure thatworks best for your analysis Most of the time, this is as easy aspointing Tableau to a database or opening a file, but Tableau givesyou the tools to bring together even complex and messy data from

Data analysis: Tableau makes it easy to visualize the data, so you

can see and understand trends, outliers, and relationships In

addition to this, Tableau has an ever-growing set of analyticalfunctions that allow you dive deep into understanding complexrelationships, patterns, and correlations in the data

Data storytelling: Tableau allows you to build fully interactive

dashboards and stories with your visualizations and insights sothat you can share the data story with others

All of this is done visually Data visualization is the heart of Tableau You

can iterate through countless ways of visualizing the data to ask and

answer questions, raise new questions, and gain new insights And you'llaccomplish this as a flow of thought

Tableau connects to data stored in a wide variety of files and databases.This includes flat files, such as Excel documents, spatial files, and textfiles; relational databases, such as SQL Server and Oracle; cloud-baseddata sources, such as Google Analytics and Amazon Redshift; and OLAPdata sources, such as Microsoft Analysis Services With very few

exceptions, the process of analysis and creating visualizations will be thesame, no matter what data source you use

2 Under Connect and To a File, click Text File

3 In the Open dialogue box, navigate to the \Learning Tableau\Chapter