Preparing Your Data

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From the course by University of California, Davis

Fundamentals of Visualization with Tableau

1205 ratings

University of California, Davis

Fundamentals of Visualization with Tableau

1205 ratings

Course 1 of 5 in the Specialization Data Visualization with Tableau

In this first course of the specialization, you will discover just what data visualization is, and how we can use it to better see and understand data. Using Tableau, we’ll examine the fundamental concepts of data visualization and explore the Tableau interface, identifying and applying the various tools Tableau has to offer. By the end of the course you will be able to prepare and import data into Tableau and explain the relationship between data analytics and data visualization. This course is designed for the learner who has never used Tableau before, or who may need a refresher or want to explore Tableau in more depth. No prior technical or analytical background is required. The course will guide you through the steps necessary to create your first visualization story from the beginning based on data context, setting the stage for you to advance to the next course in the Specialization.

From the lesson

Making Data Connections

Creating visualizations require data and in this module, you will discuss the various data sources for visualization and specifically what can be used in Tableau. You will prepare your data and identify the types of data connections possible with Tableau. You will be able to connect and merge to multiple data sources which can help make your visualizations more powerful.

Making Data Connections Overview1:41

Preparing Your Data For Import7:14

Primary Types of Connections2:53

Preparing Your Data6:15

Connecting and Merging Multiple Data Sources4:48

Meet the Instructors

Suk S. Brar, M.B.A.
Lead Business Consultant
Blue Shield of California
Govind Acharya
Principal Analyst
Budget and Institutional Analysis

[MUSIC]

In previous lessons we focus on preparing your data for import.

Connecting to different types of data using Tableau Public and

distinguishing between a live data connection and a data extract.

In this lesson we will cover preparing your data for Tableau Public.

We will identify and demonstrate the different types of data that

Tableau Public can and cannot connect to.

And we will also demonstrate ways to get around some of the limitations

of Tableau Public.

When you first open Tableau Public you will be directed to

the Tableau Public homepage.

On the left side of the screen, you will notice that Tableau Public

gives you the option to connect to an Excel file, a text file,

an Access file, or a statistical file located on your computer.

Or the option to connect to OData or web data connector server.

The Excel, text, Access, and statistical files will be local databases,

while the OData connection will allow you to connect to an online database

To connect to your Excel, text, Access or statistical data, click on the file type.

So for example, when you click on Excel, you will notice that you have the option

to connect to a .xls, .xlxsx or xlsm file.

When you click on text, you will have the option to connect to a character delimate

file.csv tab delimate files .tab or .tsv, or text files.txt.

When you click on Access you will have the option to connect to

a Microsoft Access database .mdb or .accdb.

And when you click on Cisco file,

you will have the option to connect to a SAS file

.sas7b.spsfile.save or our files .rdata or .rda

Let's take some time and use Tableau to connect to a data file.

For this example, we will use data that is stored in a Microsoft Excel file.

From the Open file window, navigate to where the file is stored and click Open.

Tableau Public will import every sheet that resides within the Excel Workbook and

each sheet will appear under Sheets here at the bottom of the worksheet.

Similar to tab worksheet file management, people come to expect from Excel.

Click on the sheet that contains the data you would like to analyze and

drag it to the Drag Sheets Here area.

You now have a visual representation of your data and

it should look very similar to the original Excel data.

As you can see, each column has a header name and

the data type is automatically identified by Tableau through the use of icons.

An ABC icon represents string data.

For example data that includes names.

A globe icon represents geographical data.

For example data that includes states,cities, ZIP codes et cetera.

A calendar icon represents dates and the pound icon represents numeric data.

If Tableau incorrectly assigned a data type,

you can click on the associated icon and choose a correct data type.

If everything looks correct you can click on Sheet One and

begin analyzing your data.

[BLANK AUDIO].

If your data resides online you

can make a connection through

an OData or web data connector.

A Tableau web data connector gives you a way to connect to data that doesn't

already have a connector.

Using a web data connector, you can create and

use a connection to almost any data that is accessible over HTTP.

This can include internal web services, JSON data, XML data,

Rest APIs and many other sources.

Because you can control how the data is retrieved,

you can even combine data from multiple sources.

You create a web data connector by writing a webpage that contains JavaScript and

optional HTML.

Please visit your resources section for

more information on web data connectors and JavaScript.

After you've written a web data connector you can share

it with other Tableau users by publishing it to the Tableau server.

To help you create web data connectors,

Tableau has created a software development kit that concludes templates,

example code and a simulator that lets you test web data connector.

This documentation also includes a tutorial that walks you through how to

create a web data connector from scratch.

At this time Tableau Public can only connect to Microsoft Excel,

Microsoft Access, multiple text file formats,

statistical files and Web Data Connectors.

All other data sources such as Tableau servers, SAS servers, MySQL servers,

Amazon Redshift servers, etc at this time are not supported by Tableau Public.

If you currently have data in a data source that is not

supported by Tableau Public, I would recommend transferring your data

into one of the data sources that is supported by Tableau Public for analysis.

Another limitation of Tableau Public is that currently

it is limited to working with 10 million rows of data per workbook.

If your data exceeds this limit, I would suggest trying to break it into smaller

data sets so Tableau Public is able to analyze your data.

Before we conclude this session, I would like you to practice connecting to

different data sources and importing your data into Tableau Public for analysis.

In part four of this module, we will use Tableau to connect to different data

sources and connecting different data sources together.

Good luck.

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