What is Tableau? Features, Functions & Data Visualizations [With Examples]

In today’s data-driven world, many organizations are turning their heads into Business Intelligence to analyse their data and to expand its presence with the help of data. Business Intelligence refers to the mixture of tools and technologies that convert raw data into significant insights which in turn increases the revenue of the organisation.

These tasks can be done by performing data visualisation and by deriving insights from the data. Data Visualisation refers to graphical representation of the data using different shapes and colours for better interpretability. One such tool to help the organisations in performing data visualisation is Tableau.

Tableau is one of the fastest data visualisation and data analytics platform that allows people to transform the data to solve their business problems. It helps the users to simplify the raw data and present it into clean and understandable format using graphical representations. It provides licensed as well as free products for the users with different functionalities. Learn more about tableau data visualization.

Features of Tableau

  • Transforming the business problem queries to visualisation.
  • Extracting and blending the data from multiple sources.
  • Creating dashboard to derive insights from the real-time data.
  • Drag and drop functionality to ease the usability.
  • Coding and customization of reports.
  • Ability to import various types and sizes of data.
  • Modifying data using various operations like slicing, joining, etc.

How does Tableau work?

Tableau connects with numerous data sources like different types of databases, excel, text files, AWS, Json files, PDFs, Snowflake etc to extract the data. Once the data is extracted, we can use multiple graphical representations like Bar charts, Pie charts, Histograms, Tree-map, Scatter Plots etc to analyse and visualise the data.

Line Chart (Source: Tableau)

Histogram (Source: Tableau)

Tableau Products

The products of Tableau can be classified into two sections:

Developer Tools: The developer tools are used for generation of the reports, dashboards, and visualisations. The products that fall into this category are Tableau Public and Tableau Desktop. Tableau Public is a free tool whereas Tableau Desktop is a licensed version.

Sharing Tools: The purpose of these tools is to share the reports, dashboards and visualisations that are created using Developer tools. These tools allow us to collaborate with people that are within the same organization or within the global community. The products that fall into this category are Tableau Server, Tableau Online and Tableau Reader.

1. Tableau Desktop

It is a desktop application which allows us to perform all the functionalities that Tableau provides. Tableau Desktop is further classified based on publishing and data sourcing capabilities:

  • Tableau Desktop Personal: – The workbooks used in Personal edition are private. These cannot be uploaded to Tableau Server or Tableau Online and used for personal use only. Although you can save the workbook locally or on Tableau Public. Moreover, it supports few data connectors for extraction of the data. It connects only to CSVs or Excel docs.
  • Tableau Desktop Professional: – Tableau Desktop Professional allows us to use over 65 data connectors for extracting the data. It also allows us to upload the workbooks on Tableau Server and Tableau Online, along with the option to save locally and to Tableau Public.

2. Tableau Prep Builder

It is designed to allow us to prepare the data easily and intuitively. It provides us functionality to combine, shape and clean the data for analysis in Tableau. As we keep on adding tables in the connection pane, we can drag and drop these tables to bring into the flow pane and add steps like joining, slicing, pivot etc to clean and shape the data. After finishing the flow, we can apply these operations to the entire data set.

Tableau Prep (Source: Tableau)

3. Tableau Server

The main usability of the Tableau server is to share visualisations and workbook which are generated in the Tableau Desktop throughout the organization. The access to the uploaded workbooks will be restricted to the licensed users only. It is highly secure as the workbooks are shared within the organization which also allows high speed sharing.

4. Tableau Online

In Tableau Online, the data is stored on the servers which are hosted in the cloud maintained by the Tableau group. Tableau Server and Tableau Online server the same purpose with the main difference that you need to maintain Tableau Server while Tableau Online is completely hosted on the cloud.

5. Tableau Public

Tableau Public is a free software which can allow anyone to share and explore the data visualisations online. It allows us to connect with the global Tableau community to view their visualisation or “vizzes” as Tableau community would call them. The workbooks created in Tableau Public cannot be stored locally, they are stored to the Tableau’s public servers. It is a great platform to learn Tableau and to share their vizzes to the global community.

6. Tableau Reader

Tableau Reader is a free view-only tool that allows us to view their workbooks and visualisations created using Tableau Desktop or Tableau Public. We can filter the data in Tableau Reader but editing and modifications are restricted in this product. Tableau Reader does not provide any security as it is used only for viewing purpose.

How to use Tableau?

Data Extraction

The very first thing that we need when we want to use Tableau is data. We need to locate the resources for extracting the data from various sources. It may happen that the data that we need is in different sources like databases, pdf, AWS, etc. We need to use licensed version of Tableau to access different data connectors.

The extensive list of data connectors is listed here. Every data connector has its own procedure to connect to Tableau and extract the data. It is quite easy to connect to text files and excel wherein we need to browse and select the file. Although we need to download drivers to talk with database, credentials of the database and other server details for connecting to data connectors such as Amazon Redshift.

Quick Tip: – For better interpretation of data from Excel, CSVs, Google sheets and PDFs, we can make use of Data Interpreter. It helps in detecting the titles, footers, empty rows, and other things from the file to identify the actual attributes and values. For more intensive data cleaning, make use of Tableau Prep. You can read more about Data Interpreter over here Tableau Architecture: Components & Clients

Creating Visualisations

Tableau provides a variety of graphs to provide better visualisation of the data. The visualisations that we create depend upon the properties of the data (categorical, continuous etc.) and the business problems which we are trying to solve. There is no thumb rule as to which chart should be used for what type of data, as it depends upon how the creator wants to present these visualisations. Although there are some common practices that can be followed for certain type of data.

The following are a few examples for what type of visualisations can be created in certain scenarios:

1. Time Series Data: – When we are dealing with time series data, we try to present how an attribute changes over time. For presenting changes over time, we can create visualisations using line charts, slope charts and highlights table etc.

Time Series Visualisations (Source: Tableau)

2. Distribution of data: – Distribution of an attribute allows us to analyse its range of values and the occurrence of certain values in the attribute. We can plot histogram, boxplots, violin plots etc. to visualise distribution.

Distribution Visualisations (Source: Tableau)

3. Correlation amongst attributes: – It helps in determining the relation between two attributes. Plots like scatter plot, line-column plot and bubble plot can help in visualisation of correlation between two attributes.

Correlation Visualisations (Source: Tableau)

4. Part to whole analysis: – Part to whole helps us in visualising the significance of each element from a component containing multiple elements. These visualisations are useful for summarising the overalls along with the key elements. Pie charts, Treemap, Stacked column, etc. can be used for this purpose.

Part to Whole Visualisations (Source: Tableau)

5. Spatial data: – Spatial visualisations are used when we need to analyse the locations from the data. These visualisations help in extracting the geographical patterns from the data. Flow Map, Heat Map, Contour Map etc. help in visualisation of spatial data.

Spatial Visualisations (Source: Tableau)

6. Magnitude: – The magnitude of different levels in the attribute can be compared to derive insights from the data. We can normally visualise the attributes in form of columns, bars, paired columns, paired bars etc.

Magnitude Visualisations (Source: Tableau)

Must Read: Tableau Developer Salary in India


The features of Tableau and its different products like user-friendly interface, ability to create beautiful visualisations, analysing the data in quick span of time, high level of security etc have made it one of the most essential tools for solving business problems.

For amateurs, Tableau Public is a great way to start off with and to learn from the Tableau community. Professionals prefer Tableau Desktop as it provides more data connectors and functionalities.

If you are curious to learn about tableau, data science, and want to learn more, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

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