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Data Visualization with Tableau (38 Blogs) Become a Certified Professional

When you talk about Data Visualization, the first word that comes to your mind is – Tableau. I am guessing that’s why you might be here reading this Tableau tutorial because you have heard about the advantages of Tableau. The demand for Tableau certification training is at peak because of its increasing adoption in the market.

This is my first blog in this Tableau Tutorial blog series which will explain how to get started with Tableau. Hope you will enjoy learning about Tableau with this Tableau Tutorial blog.

Well you came to the right place. In this Tableau Tutorial, you will be learning the following topics:

Importance Of Data Visualization
Data Visualization Tools
Why Tableau?
What Is Tableau?
Tableau Product Family
Understanding More About Tableau
Visualizations
Use Case – Datamatics

Let us first start this Tableau tutorial by understanding the concepts behind Data Visualization.

Importance Of Data Visualization

Data Visualization is one of the most important part of data analysis. It has always been important to present the data in an understandable and visually appealing format. Data visualization is one of the skills that Data Scientists have to master in order to communicate better with the end users.

Data is the word here.

Let me first give you an idea of the kind and amount of data that we are dealing with. According to SiliconAngle, there was 2.5 zetabytes of stored data world over in the year 2012 and it is set to hit more than 50 zetabytes mark by the end of 2017. To put things in perspective, this data has largely been produced by websites and cross platform transactions. Add to it the fact that there would be a total of 20 billion “smart” devices connected to the internet by the end of 2020 and the numbers can be baffling!

Data visualization allows data scientists to converse with their end users. The outcome of data analysis is not immediately comprehensible to the people who do not directly deal with data. Data visualization bridges that gap and makes people appreciate the possibility of data analysis.

Let us consider the following example to understand this:

The following image shows the x and y co-ordinates of different points to be plotted on a graph. The numbers look almost the same, don’t they? Maybe the lines will look similar after we plot each set on the graph.

Quartet Dataset - Tableau Tutorial - Edureka

So, now take a look at the image below when we plot these points in our graph:

You see how different they look like when you actually visualize it. It wasn’t possible for us to figure out the nature of each line until we visualized it.

Tableau Tutorial: Introduction To Data Visualization Tools

Here are the top 5 data visualization tools that are being used extensively in BI:

Tableau
Qlikview
Domo
Microsoft power BI
Excel

Let us know a little bit about all of them.

Tableau:

Basic version of Tableau data visualization tool is free which can perform regular tasks such as:

Sales data analysis
User density monitoring
Consumer segmenting
Tracking budgeting expense
Categorizing and sub-categorizing data

Excel:

You can actually do some pretty complex things with Excel, from ‘heat maps’ of cells to scatter plots. As an entry-level tool, it can be a good way of quickly exploring data, or creating visualizations for internal use, but the limited default set of colors, lines and styles make it difficult to create graphics that would be usable in a professional publication or website.

Microsoft Power BI:

Microsoft Power BI is a cloud-based business intelligence and analytics service that provides a full overview of your most critical data.

Connecting to all of your data sources, Power BI simplifies data evaluation and sharing with scalable dashboards, interactive reports, embedded visuals and more.

Domo:

Domo is designed to be available for all business users, regardless of technical expertise, to help them make better business decisions.

Domo recently launched Business Cloud, the world’s first open, self-service platform to run an entire organization. Business Cloud brings together the data, the people and the insights users need to find answers to critical business questions and make faster, better-informed decisions to improve performance.

Qlikview:

The QlikView business discovery platform is one of a few visual analytics tools offered by Qlik. QlikView can’t create the same elegant visualizations that the other tools offer, but the software’s dynamic model means that you can quickly analyze your data in multiple dimensions. In addition, QlikView is able to work off of data in memory instead of off your disk, allowing for real-time operational BI environments (like monitoring financial transactions).

QlikView is able to work with a wide variety of data sources, including SAP, Oracle, Salesforce.com and other legacy data files like Excel spreadsheets. What’s more, QlikView can combine these disparate data sources into a single visualization or dashboard.

But now the big question is which tool should you go for? Well, I say go with Tableau. Take a look below to know why.

Why Tableau?

Below are some of the pros or features of Tableau which will spellbind you to start using it right away!

Tableau Features:

1. Apt visualizations:

Tableau connects to many different data sources and can visualize larger data sets than Power BI can. Once in Tableau, a dashboard shows the basics of the users’ data. The user can then drill down into data sets by downloading a worksheet. From there, they can apply various visualizations to the data.

In Tableau, you select the data and switch between visualizations on the fly. It’s easier to jump between visualizations in Tableau.

Tableau visualizes data from the start, allowing you to see the significance right away. Tableau differentiates correlations using color, size, labels and shapes, giving you context as you drill down and explore on a granular level.

2. Depth of discovery:

The features of Tableau gives users ways to answer questions as they investigate data visualizations. The solution can show basic trends as predictions, use “what if” queries to adjust data hypothetically, and visualize components of data dynamically for comparisons.

3. Implementation:

Tableau provides a variety of implementation and consulting services. For enterprise-level deployment, there’s a four-step process spanning weeks, and for smaller-scale deployments, there are quick-start options that can complete setup in a matter of hours.

Tableau provides a variety of implementation and consulting services. For enterprise-level deployment, there’s a four-step process:

Phase 1 – This phase involves IT planning, architecture consulting, pre-install checkup, server installation and verification, and validation of security configuration.
Phase 2 – Phase 2 involves working with data and data migration, including data modeling, data mining, data extraction, data sources and business workflow.
Phase 3 – In Phase 3, there’s a two-day classroom training covering Tableau Fundamentals, hands-on advanced coaching, and building and formatting visualizations.
Phase 4 – This final phase helps companies expand Tableau usage across their business. It includes implementation workshops where topics such as evaluating action plans and defining measurable outcomes are discussed.

4. Automation functionality:

Tableau is a little more intuitive with creating processes and calculations. For example, when creating calculations in a tabular format, the formula can be typed once, stored as a field and applied to all rows referencing that source. This makes it easier to create and apply recurring processes. Tableau’s flexibility also allows users to create custom formulas that aren’t available in most of the tools.

5. Data source connectors:

Tableau offers hundreds of native connectors to easily pull, cleanse and correlate data from practically any source without having to create custom code.

Tableau extracts large data sets from sources for quick, ad-hoc analysis using two different methods: Live Connection and In-memory. Both adapt to your local database and, based on the size and capacity, sync data quickly by extracting the relevant data to a query. It also has a general Open Database Connectivity (ODBC) connection for any connections that don’t have a native connector provided. This is the reason, you can see an increasing demand graph for Tableau certification training.

Tableau Product Family

1. Tableau Desktop:

It is a self service business analytics and data visualization that anyone can use. It translates pictures of data into optimized queries. With tableau desktop, you can directly connect to data from your data warehouse for live upto date data analysis. You can also perform queries without writing a single line of code. Import all your data into Tableau’s data engine from multiple sources & integrate altogether by combining multiple views in a interactive dashboard.

2. Tableau Server:

It is more of a enterprise level Tableau software. You can publish dashboards with Tableau Desktop and share them throughout the organization with web-based Tableau server. It leverages fast databases through live connections.

3. Tableau Online:

This is a hosted version of Tableau server which helps makes business intelligence faster and easier than before. You can publish Tableau dashboards with Tableau Desktop and share them with colleagues.

4. Tableau Reader:

It’s a free desktop application that enables you to open and view visualizations that are built in Tableau Desktop. You can filter, drill down data but you cannot edit or perform any kind of interactions.

5. Tableau Public:

This is a free Tableau software which you can use to make visualizations with but you need to save your workbook or worksheets in the Tableau Server which can be viewed by anyone.

Understanding Tableau

Let us start by taking a look at the datatypes that Tableau supports. Refer to the diagram below which shows all the compatible data types of Tableau.

The above diagram shows you the data types that Tableau supports with respective examples.

Now, the data types that we are dealing with can also be categorized broadly into two categories and they are:

Measures
Dimensions

Refer to the diagram below to understand the differences between Dimensions and Measures.

In order to make it more understandable to you, A dimension is used to add more detail to describe your data.

How To Use Tableau?

You just need to follow the below 3-step mantra to use Tableau:

Connect to data
Play around with the UI
Create visualizations

1. Connect to data

The first thing to do in Tableau is to connect to your data. There are mainly two types of connections-

Connecting to your local file or connecting to a server.

Tableau can connect to any local file or database such as-

Excel
Text File
Access
Statistical File, or
Other Database file.

Local connection gives the maximum speed of data processing.

Tableau can connect to your data server too. It can connect to almost any type of data server. Below are some of the most popular databases that Tableau can connect:

Tableau Server
Google Analytics
Google BigQuery
Hortonworks Hadoop Hive
MapR Hadoop Hive
IBM DB2
IBM BigInsights
IBM Netezza
Microsoft SQL Server
Microsoft Analysis Services
Oracle
Oracle Essbase
MySQL
PostgreSQL
SAP

While working on Tableau, data can have Live Connection where any change in the source data will be automatically updated in Tableau. On the other hand, data can be Extracted to Tableau repository so that any change made here will not affect the original source data.

Data Joins

You can also integrate different data-sets together to link up and produce better insights. There are different ways to join data-sets. Refer to the diagram below to understand them all.

In the above diagram shows the four data-set join options available in Tableau.

2. Play around with the UI

This is how the user interface looks like:

UI- Show me the data

This is the pane with which you can create visualizations. You can create different visualization in order to represent your dataset. The diagram below shows the ‘show me’ data pane:

Some visualizations might not be available at times because of incompatible dataset.

Below are the most popular visualizations used widely in Tableau:

Tree Map

Heat Map

Now let’s explore few more options available in our UI.

Menu

The menu bar in Tableau consists of various options to edit your visualization. Let me take you through them one by one.

File menu

This Menu is used to create new Tableau workbook and open existing workbooks from both local system and Tableau server. The important features in this menu are:

Workbook Locale to set the language to be used in the report.
Paste Sheets to paste a sheet into the current workbook which is copied from another workbook.
Export Packaged Workbook option is used to create a packaged workbook which will be shared with other users.

Data Menu

This Menu is used to create new data source to fetch the data for analysis and visualization. It also allows you to replace or upgrade existing data source.