Introduction to Data Visualisation- Why is it Important?

By Marina Chatterjee Updated on May 4, 2023 20185

Ever come across a pie chart or any other graphic image depicting information? I’m sure, you must have. They are one of the most common ways of putting forward statistics results that could be understood by many – but did you ever stop to think, wait, what are these visuals called? What is its purpose? And most importantly, are they used in business growth scenarios? Firstly, the bar graphs, pie charts, or any other method of representing information is known as Data visualization. Surprisingly, it is one of the most common mathematics topics people come across in their day-to-day life.

What is data visualization?

Yes, you know what data visualization is, but by definition, it means much more. In simple words, data visualization is a graphical representation of any data or information. Visual elements such as charts, graphs, and maps are the few data visualization tools that provide the viewers with an easy and accessible way of understanding the represented information. In this world governed by Big Data, data visualization enables you or decision-makers of any enterprise or industry to look into analytical reports and understand concepts that might otherwise be difficult to grasp.

Why is data visualization important?

By now, you would have understood how data visualization simplifies the way information is presented. However, is that the only power of data visualization? Not really. As the world is changing, the need for information is changing as well. Here are a few benefits of data visualization:
● Easily, graspable information – Data is increasing day-by-day, and it is not wise for anyone to scram through such quantity of data to understand it. Data visualization comes handy then.
● Establish relationships – Charts and graphs do not only show the data but also established co-relations between different data types and information.
● Share – Data visualization is also easy to share with others. You could share any important fact about a market trend using a chart and your team would be more receptive about it.
● Interactive visualization – today, when technological inventions are making waves in every market segment, regardless of big or small, you could also leverage interactive visualization to dig deeper and segment the different portions of charts and graphs to obtain a more detailed analysis of the information being presented.
● Intuitive, personalized, updatable – Data visualization is interactive. You could click on it and get another big picture of a particular information segment. They are also tailored according to the target audience and could be easily updated if the information modifies. Also do check our free course on data visualization using python.

What are different Data Visualization Tools?

Data visualization tool helps in, well, visualizing data. Using these tools, data and information can be generated and read easily and quickly. Many data visualization tools range from simple to complex and from intuitive to obtuse.
● Tableau Desktop – A business intelligence tool which helps you in visualizing and understanding your data.
● Zoho Reports – Zoho Reports is a self-service business intelligence (BI) and analytics tool that enables you to design intuitive data visualizations.
● Microsoft Power BI – Developed by Microsoft, this is a suite of business analytics tools that allows you to transform information into visuals.
● MATLAB – A detailed data analysis tool that has an easy-to-use tool interface and graphical design options for visuals.
● Sisense – A BI platform that allows you to visualize the information to make better and more informed business decisions.

What are Data Visualization Techniques?

Here are a few data visualizations that you must know:
● Know the target audience – this shouldn’t come as a surprise. Designing a chart of a graph should always be done based on the audience that will view it.
● Create a goal – or more like a logical narrative. Ensure to set clear goals that must be conveyed through the infographic. Also, the relevant content type is a must.
● Choose the chart type – A pie chart does not complement every information visually. Similarly, a bar graph does not show every statistic clearly. Choose the chart part accurately to put forth the information.
● Context – Use of colours is encouraged depending upon the context. A decrease in the profit growth could be marked red, whereas green could show the increasing parameter.
● Use tools – Yes, one of the easiest ways to create data visuals is using tools. Use them as they make the charts intuitive as well as easy to read.

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What are Data Visualization examples?

What better way to understand data visualization, if not with examples? Here are a few for your reference:
● Government Budget – Government budgets are always tough to understand as they number and more numbers. A recent example is a colour-coded treemap that was designed by The White House during Barack Obama’s presidency, which visually broke down the US’s 2016 the budget for better understanding and put government programs in context.
● World population – How would you present the world population along with their density? Simple, by visual representation. A world map showing the population density is another data visualization example.
● Profit and loss – Business companies often resort to pie charts or bar graphs showing their annual profit or loss margin.
● Films and dialogues – Out of many characters in the film who will have how many dialogues? Data visualization is the answer here. The makers of popular sitcom ‘FRIENDS’ used a pie chart during shooting to ensure that every six characters have an equal number of jokes and dialogues.
● Anscombe’s quartet – It is one of the most well-known and popular, which has four data sets of identical descriptive statistics, but they appear different when graphed.
All of these four data sets have different distributions and consists of 11 points
marked on x and y-axis.

Data Visualization in Statistics

The mathematical topic, statistics is very closely related to data visualization; they both represent data.
● By combining both statistics and data visualization, businesses can transform the data into a valuable asset that drives growth.
● Thereafter, data visualizations along with statistics could be used to establish correlations between different data sets. Businesses often use to co-relate their different departments' results.
● Both of them make it easier to notice any patterns that might be recurring in the data.
● Use of data visualization in statistics optimizes the way business read data and extract relevant insights from it further pursue how to improve brand name.
● It even helps in determining which statistical figures are relevant for work or task and which are not.

Data Visualization using Tableau

Tableau is the US-based data visualization firm that easily connects to almost any data source; it could either be corporate Data Warehouse, Microsoft Excel or web-based data. Also, the data does not have to be accumulated as Tableau allows analysis on real-time data feed. Tableau enables you to connect with various data sources, files, and servers. Tableau also encourages you to work on different file formats such as CSV, JSON, Txt, and even servers such as Tableau Server, MySQL, Amazon Redshift and more.

There are many other benefits of Tableau as well:

● Tableau is a smart tool and even recommends which visualization tool could be used for what purpose. You could navigate through the software, click on the ‘Show Me’ feature available within the tool, which would show different types of graphs and charts with various attributes.
● Tableau also supports map, data of which could be easily modified by you, and unlike other BI tools, you don’t have to break your head to use them. It is relatively easy to use maps in Tableau.
● Tableau has an interactive UI that plays an important role in how you could design and develop data visualization charts. The tool offers numerous fields and chart options such as heat map, Scatter Plot, Packed Bubble, and more.

What is the Scope of Data Visualization in Business?

In this era, when Big Data is making waves everywhere, the scope of data visualization is much more than could be anticipated. A vast amount of data is generated today by organizations and managing, structuring, and reading that data is a hectic task. However, with data visualization technique, it is possible to not only read that data but also leverage it in business.
● Display and reports – This is one of the common uses of data visualization in business. Organizations can create, update, translation, or delete any textual information into a visual context.
● Operational alerting – another scope of data visualization is operational alerting. It enables sales, marketing, and internal processes teams to stay informed about any new promotion, product launch, or more. Data visualization allows sending visual alerts to the teams in real-time.
● Mindmaps – A diagramming tool, mind maps are used in creating and visualizing structure and relationships, classifying ideas used for observing and managing information, arriving at a decision, and solving other business problems.
● Business growth – Probably one of the main scopes of data visualization. Business growth is measured and represented using graphics to better understand how an organization is doing in terms of sales.
● Other sectors – Other scopes of data visualization are in the medical field,
geography, biology, and meteorology that depict different types of data used in these fields.
Finally, data visualization plays an important role in displaying and depicting different and huge amount of data types in simple, understandable structure and layout. With multifold benefit in almost every industrial and commercial field, data visualization is today’s topmost growing technique, which is preferred by a large number of data scientists to visualize and analyze complex data sets.