How To Use Tableau For Data Science?

Tableau was founded on the principles of simplicity, visual representation, and commercial growth. These features are fantastic and assist businesses in gaining a better understanding of consumer demands, client requests, conversions, and other factors. Having said that, learning a new data science tool is always intimidating.

Tableau's objective is to make spreadsheets, databases, and other data sources easier to use for the average individual. Christian Chabot (CEO), Pat Hanrahan (Chief Scientist), and Chris Stolte (Chief Development Officer) started by merging a structured query language for databases with a descriptive language for graphics rendering. Visual Query Language, or VizQL, is a database of visualization language. 

Tableau's namesake software program is built on VizQL, which queries relational databases, cubes, cloud databases, and spreadsheets to generate a number of graph kinds. These graphs can be assembled into dashboards and distributed via a computer network or the internet.

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Steps To Use Tableau For Data Science

Even for complete beginners, getting started with Tableau is not as difficult as it may appear. With free training videos, live training sessions, and certification programs, the platform provides a vibrant learning community. To access Tableau's learning resources, go to their website. Even if you are a newbie, you can get started with Tableau.  Here are a few steps on how to use Tableau for you to get started;

  • Connect the data
  • Play around with the interface
  • Create visualizations
  • Connect the Data

You can connect your data from several sources on the left side of Tableau Desktop. Tableau Desktop can be linked to both the local file and the server. Tableau supports a variety of data sources, including Excel spreadsheets, local databases, statistics, text, and CSV files. You can also connect to data servers at faster speeds, such as Tableau Server, Google Analytics, Google BigQuery, Hadoop Hive, Oracle database, MySQL, IBM DB2, and SAP. After linking the datasets, you can experiment with your data, clean it, and combine it with other datasets to gain new insights.

  • Play around with the Interface

Following the loading of your datasets, an interface with numerous features and datasets will show on the screen. The image below shows the user interface, where you can experiment with your data and navigate to the workbooks part from the bottom left corner. 

  • Create Visualizations

The workbook interface will display all the tools needed to build outstanding visualizations. Under the Show Me section, the variables of your datasets will appear on the left side, and the visuals will appear on the right side. Select the data variable now, and Tableau will highlight the visualizations that are compatible with the variables. If you choose a nation variable, Tableau will highlight the maps and geographical graphics. 

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Tableau: How it works

Tableau, as previously said, can readily access any type of data. So, in the tableau technique, it is connected and extracted to data for visualization. Tableau can extract data from databases such as pdf, excel, text documents, R, Hadoop, Python, and SAS and store it in cloud databases such as Flipkart, Google Sheets, Netflix, and Amazon.

The data is moved to Tableau's data engine, often known as the Tableau desktop. Here, the business analyst works with data, creates a dashboard, and shares it with the user, who reads it on the Tableau Reader screen. Data is published with many supported features, like collaboration, security models, automation, dissemination, and so on. Finally, the user will be able to obtain a data visualization file via email, desktop, or mobile. (learn the fundamentals and several methods of data visualization in business analytics).

Features of Tableau

It is critical to grasp the functionalities of Tableau in order to use it properly. Here are some Tableau features: 

  • Tableau Dashboard
  • Collaboration and Sharing
  • Live and In-memory Data
  • Data Sources in Tableau
  • Maps
  • Mobile view

Tableau Dashboard

Tableau Dashboards present a comprehensive perspective of your data using visualizations, visual objects, text, and so on. Dashboards are particularly instructive because they may show data in the form of stories, allow for the addition of various views and objects, offer a range of layouts and formats, and allow users to install appropriate filters. You may even effortlessly duplicate a dashboard or its specific features from one workbook to another. 

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Collaboration and Sharing

Tableau offers simple ways for users to collaborate with one another and rapidly share data in the form of visualizations, sheets, dashboards, and so on. It enables you to securely communicate data from a variety of data sources, including on-premise, on-cloud, hybrid, and so on. Instant and simple cooperation and data sharing aid in obtaining quick assessments or feedback on the data, resulting in a more comprehensive overall examination of it. 

Live and In-memory Data

Tableau supports live data sources as well as data extraction from external data sources as in-memory data. This allows the user the freedom to use data from multiple types of data sources without restriction. Data can be used directly from the data source by establishing live data connections, or it can be kept in memory by extracting data from a data source as needed. Tableau offers additional data connection features like automatic extract refreshes, notification of a failed live connection, and so on.

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Data Sources in Tableau

Tableau provides a plethora of data source options from which to connect and retrieve data. Tableau supports data sources ranging from on-premise files, spreadsheets, relational databases, non-relational databases, data warehouses, big data, and on-cloud data. A secure connection to any of Tableau's data sources can be readily established, and that data, along with data from other sources, can be used to generate a combinatorial view of data in the form of visuals. Tableau also supports numerous data connectors, including Presto, MemSQL, Google Analytics, Google Sheets, Cloudera, Hadoop, Amazon Athena, Salesforce, SQL Server, Dropbox, and many others.


The map is yet another significant aspect of Tableau. Tableau comes with a lot of pre-installed map data, such as cities, postal codes, administrative boundaries, and so on. This makes Tableau maps extremely comprehensive and insightful. You can add different layers of geology to the map based on your needs and use your data to generate informative maps in Tableau. Tableau offers a variety of maps, including heat maps, flow maps, choropleth maps, and point distribution maps. 

Mobile View

Tableau offers a mobile version of the Tableau app in recognition of the significance of mobile phones in the modern world. One can design reports and dashboards such that they work on mobile devices as well. Tableau gives you the flexibility to design mobile layouts for your dashboard that are tailored to your particular mobile device. It is possible to add new phone layouts, interactive offline previews, etc. via the customization option. As a result, processing data while on the road is very flexible and convenient for Tableau users thanks to the mobile view.

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 Final Thoughts

Data scientists may visualize data using Tableau, which is simple to learn for both novices and specialists. Despite the sometimes frustrating learning curve, I believe you'll find that it's well worth it in the end. The multi-persona UI and the no-code, low-code, and code (SQL) tools enable collaboration across data engineers, analytics engineers, analysts, and data scientists on a single platform. Trust in data and crowd-sourced data governance are promoted by shared knowledge and data that is cataloged and well-documented. 

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