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Learning Tableau
Learning Tableau

Learning Tableau: Leverage the power of Tableau 9.0 to design rich data visualizations and build fully interactive dashboards

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Learning Tableau

Chapter 2. Working with Data in Tableau

Tableau offers the ability to connect to virtually any data. It does so using a unique paradigm that allows it to leverage the power and efficiency of the existing database engines with an option to extract data locally. This chapter focuses on the foundational concepts of how Tableau works with data, including the following:

  • The Tableau paradigm
  • Connecting to data
  • Working with extracts
  • Metadata and sharing connections
  • Joins and blends
  • Filtering data

The Tableau paradigm

Tableau connects directly to native data engines and also includes the option to extract data locally. The unique experience of working with data in Tableau is a result of VizQL: visual query language.

VizQL was developed as a Stanford research project, focusing on the natural ways humans visually perceive the world and how that could be applied to data visualization. We naturally see 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 visual query language behind the scenes. This allows you to focus on visualizing data.

One of the benefits of VizQL is that it provides a common way of describing how the...

Connecting to data

There is virtually no limit to the data Tableau can visualize. Each successive version of Tableau adds new native connections. Additionally, for any database without a native connection, Tableau gives you the ability to use a generic ODBC connection. With the release of the Extract API, first available in Tableau 8.0, any data source or sources can be programmatically combined and stored in a data extract for use in Tableau.

This section will focus on some practical examples of connecting to various data sources. We won't cover every connection, but will cover several that are representative of others. You may or may not have access to some of the data sources in the following examples. Feel free to follow them if you are able to or merely observe the differences.

You may have multiple data source connections to different sources in the same workbook. Each connection will show up under the Data tab on the left-hand side bar.

To add a connection, perform one of the following...

Working with extracts instead of live connections

Most data sources allow the option of either connecting live or extracting the data. However, some cloud-based data sources require an extract. Conversely, OLAP data sources cannot be extracted and require live connections.

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

Working with extracts instead of live connections

The fundamental paradigm of how Tableau works with data does not change, but you'll notice that Tableau is now querying and getting results from the extract. Data can be retrieved from the source again to refresh the extract. Thus, each extract is a snapshot of the data source at the time of the latest refresh. Extracts offer the benefit of being portable and extremely efficient.

Creating extracts...

Metadata and sharing data source connections

Metadata refers to information about the data itself. Nearly every database contains some metadata. This includes lists of the tables and fields for a data source and what type of data (for example, numeric, string, or date) a field contains. Tableau provides an additional layer of metadata that makes it very easy to customize a data connection to add or change attributes of the data.

Customizing a data source

Right-clicking on a field in the Data window reveals a menu of metadata options. Some of these options will be demonstrated in the following exercise, and others will be explained in later chapters. These are some of the options available via right-click:

  • Rename the field
  • Redefine the field as a dimension or a measure
  • Change the default use of a field to either discrete or continuous (this can only be done for date and numeric fields)
  • Add or remove the field from a hierarchy
  • Change the data type of the field
  • Change the geographic role of a field...

Joins and blends

Joining tables and blending data sources are two different ways to link related data together in Tableau. Joins are performed to link tables of data together within a single data source. Blends are performed to link together multiple data sources.

Joining tables

Most databases have multiple tables of data that are related in some way. Imagine you have been asked to analyze data in a simple database at a hospital with four main tables, related like this:

Joining tables

The primary table is the Visit table that has a record for every visit of a patient to the hospital and includes details such as the start and end dates and the type of visit (for example, inpatient, outpatient, ER). It also contains key fields that link a visit to a patient, a treatment, and a physician. You have confirmed that every visit has a patient and a physician, but some visits do not necessarily result in a treatment.

When you connect to the database in Tableau, you'll see the four tables listed on the left....

The Tableau paradigm


Tableau connects directly to native data engines and also includes the option to extract data locally. The unique experience of working with data in Tableau is a result of VizQL: visual query language.

VizQL was developed as a Stanford research project, focusing on the natural ways humans visually perceive the world and how that could be applied to data visualization. We naturally see 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 visual query language behind the scenes. This allows you to focus on visualizing data.

One of the benefits of VizQL is that it provides a common way of describing how the arrangement...

Connecting to data


There is virtually no limit to the data Tableau can visualize. Each successive version of Tableau adds new native connections. Additionally, for any database without a native connection, Tableau gives you the ability to use a generic ODBC connection. With the release of the Extract API, first available in Tableau 8.0, any data source or sources can be programmatically combined and stored in a data extract for use in Tableau.

This section will focus on some practical examples of connecting to various data sources. We won't cover every connection, but will cover several that are representative of others. You may or may not have access to some of the data sources in the following examples. Feel free to follow them if you are able to or merely observe the differences.

You may have multiple data source connections to different sources in the same workbook. Each connection will show up under the Data tab on the left-hand side bar.

To add a connection, perform one of the following...

Left arrow icon Right arrow icon
Download code icon Download Code

Description

If you want to understand your data using data visualization and don't know where to start, then this is the book for you. Whether you are a beginner or have years of experience, this book will help you to quickly acquire the skills and techniques used to discover, analyze, and communicate data visually. Some familiarity with databases and data structures is helpful, but not required.

What you will learn

  • Explore and analyze your data by creating basic and advanced data visualizations
  • Fix data problems, enhance your analysis, and create rich interactivity using custom calculations
  • Perform effective analysis by joining and blending data from different sources
  • Enhance your visualizations with custom formatting, labels, and annotations
  • Explore advanced topics such as sheet swapping, custom maps, and LOD calculations
  • Create meaningful dashboards in Tableau
  • Extend the value and functionality of your data
  • Share your data story using story points and fully interactive dashboards

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 27, 2015
Length: 340 pages
Edition : 1st
Language : English
ISBN-13 : 9781784394349
Vendor :
Tableau
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Product Details

Publication date : Apr 27, 2015
Length: 340 pages
Edition : 1st
Language : English
ISBN-13 : 9781784394349
Vendor :
Tableau
Category :
Tools :

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Table of Contents

12 Chapters
1. Creating Your First Visualizations and Dashboard Chevron down icon Chevron up icon
2. Working with Data in Tableau Chevron down icon Chevron up icon
3. Moving from Foundational to Advanced Visualizations Chevron down icon Chevron up icon
4. Using Row-level and Aggregate Calculations Chevron down icon Chevron up icon
5. Table Calculations Chevron down icon Chevron up icon
6. Formatting a Visualization to Look Great and Work Well Chevron down icon Chevron up icon
7. Telling a Data Story with Dashboards Chevron down icon Chevron up icon
8. Adding Value to Analysis – Trends, Distributions, and Forecasting Chevron down icon Chevron up icon
9. Making Data Work for You Chevron down icon Chevron up icon
10. Advanced Techniques, Tips, and Tricks Chevron down icon Chevron up icon
11. Sharing Your Data Story Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8
(22 Ratings)
5 star 45.5%
4 star 18.2%
3 star 18.2%
2 star 9.1%
1 star 9.1%
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Luis Diego Bolaños Alvarado Jun 22, 2015
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Great book for beginners.
Amazon Verified review Amazon
James Nguyen Jul 09, 2015
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Great book! It's not just about Tableau in particular but it provides good knowledge of ways to visualize data effectively.
Amazon Verified review Amazon
The Master Aug 18, 2016
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love it
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Some dude in Texas Oct 14, 2015
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Super-helpful for the DIY learner.
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PPMC Jun 01, 2016
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Excellent book
Amazon Verified review Amazon
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