Data Visualisation with Tableau
The graphical representation of data and information by using visual elements such as graphs, charts, and maps is known as data visualisation. Visualisation tools provide an accessible way to find and understand patterns and trends in data and plot the same.
When it comes to big data, visualisation tools and techniques are crucial for analysing massive amounts of data and making data-driven decisions. Visualisation is an efficient tool which can be used to make sense of trillions of rows of data generated every day. Data visualisation helps convey the data in a form that is simpler to understand highlighting trends, outliers and forecasts. Good data visualisation also removes noise from the data and highlights the useful information.
Effective data visualisation is a delicate balance between form and function. There might be an instance where the simplest graph could be a powerful source of information and even the most stunning visualisation might fail to convey the right information. Therefore, data and visuals need to work together to convey precise information in the simplest form and with clarity.
Different types of visualisations
Data visualisation is not limited to the simple bar graphs or pie charts. While these are the basics of visualisation, there are other more sophisticated forms of depicting information and communicating the message accurately. The key is to pair the right information with the right kind of visualisation.
Some of the common types of data visualisations are Tables, charts, graphs, maps, infographics, and dashboards. The other more specific examples of visualisation methods are area chart, bar chart, bubble cloud, box and whisker plots, bullet graph, circle view, dot distribution map, heat map, gannt chart, histogram, highlight table, network, matrix, polar area, scatter plot, streamgraph, radial tree, timeline, text tables, treemap, wedge stock graph, word cloud, and more.
How to choose a good data visualisation tool?
There are various tools that could be used for data visualisation and analysis. Each tool solves a different purpose and hence along with having the working knowledge of these tools, it is also important to know how and where these tools will be applicable. Also, not every tool can scale to enterprise-level, therefore visualisation tools need to be selected depending on the application.
Good data visualisation theory and skills transcend into specific tools and products. While learning these skills, one should focus on the best practices and develop a personal style when it comes to visualisations and dashboards. Regardless of the tools that you end up using, it is important to build a foundation of analysis and the skill of storytelling to become a successful data visualisation professional.
Importance of Data Visualisation
We are in a world where images speak louder than words and hence visualisation is an important skill to learn for analytics professionals. When we talk about big data, visualisation is of utmost importance for making sense of the huge amount of data and deciphering patterns.
Today, more and more companies are using machine learning to collect large amounts of data. With help of machine learning, data mining becomes faster and more effective and finds simpler ways to sort through, comprehend, and explain the data in a way that makes the most sense of the data for the business and other stakeholders.
Data scientists working on complex projects need a way to understand the data that they are collecting and will eventually work on. It will help them tweak their methods accordingly to ensure optimum results from the project.
The results from complex algorithms are much easier to understand in a visual format as compared to multiple lines of text and numbers. Data visualisation applications are not limited to the domains of data science, business intelligence, and business analytics. It extends to the roles of a teacher that make sense of students’ results, computer scientists that are trying to develop AI applications, and more such examples. It is a tough task to think of an industry that does not need to make better sense of data.
Given the way a human brain processes information, a large amount of complex data can be easily depicted using charts or graphs rather than poring over spreadsheets and lengthy reports. Data visualisation is an easy and faster way to convey concepts and adjustments can be made by experimenting with different scenarios. Data visualisation can also:
- Identify areas that need attention or improvement
- Clarify factors that affect consumer behaviour
- Help with product placements
- Predict sales volume
Data Visualisation with Tableau
Tableau is the fastest-growing data visualisation tool and a preferred choice of most of the organisations and professionals across industries. It helps in simplifying raw data into an easily understandable format.
Data visualisation using Tableau provides extremely fast data analysis and the visualisations are created in the form of dashboards and worksheets. The data that is created through tableau is easily understood by professionals at all levels in an organisation. It also allows non-technical users to create a customised dashboard.
Some of the best features of Tableau are:
- Data Blending
- Real-time analysis
- Data collaboration
Tableau software does not require any technical knowledge or programming skills to operate. When you have a look at Tableau dashboard examples, you would realise how easy it is to create one.
The Tableau product suite contains:
- Tableau Desktop - It has a rich feature set that allows users to code and customise reports
- Tableau Public - The workbooks that you create cannot be saved locally and should be saved in Tableau’s public cloud that could be accessed by anyone
- Tableau Online - It has all the functions that are similar to Tableau server but the data is stored on the servers that are hosted in the cloud maintained by Tableau group
- Tableau Server - It is used to share workbooks and the visualisations that are created in the Tableau desktop application across the organisation
- Tableau Reader - It is a free tool that will allow you to view the workbooks and the visualisations that are created using Tableau Desktop or Tableau Public.
Data analytics in Tableau could be classified into two sections:
- Developer Tools - These are the tableau tools that are used in development such as the creation of dashboards, reports, charts, and visualisation fall into the category of developer tools. Some of the tableau products that fall under this category are the Tableau Desktop and Tableau Public.
- Sharing Tools - The purpose of these tools is to share the visualisation reports and dashboards created using the developer tools. Products that fall into this category are Tableau Online, Tableau Server, and Tableau Reader.
Data Visualisation course with Tableau
The ‘Data Visualisation with Tableau’ course by Great Learning Academy will help you learn to create easy to read and understand graphs, charts and other visual representations of data. The course will cover the basics and functionality of Tableau, dashboard design with Tableau Dashboard examples, visual analytics and advanced mapping.
The course has 11.5 hours of video content and quiz to measure your learning. The course syllabus includes Visual Analytics and the 7 step process, Exploring the Tableau Desktop 10 Interface, Importing Data Set In Tableau, Deriving insights: Number Vs Visuals, Design Principles, String Calculations, Logical Operations, Groups in Tableau, Introduction to Dashboards, Special Types of Charts, Funnel and Control Charts, Parameters in Tableau, What-If Analysis with Parameters, Building Dashboards, Building Storyboards, and Advanced Mapping Techniques.
Upon completion of the course, you will get a certificate of completion from Great Learning which is easily shareable on your LinkedIn profile and you can also add it to your resume. Join this course now to learn data visualisation from scratch using Tableau.