Data Visualization Vs Information Visualization Explained

No matter which era you are living in, visualization always leaves a lasting imprint on the minds of individuals. Research showed that our brain measures all the information at an extremely quick rate if it is fed through the visuals. Hence visualization has been a successful method to impart both theoretical and solid thoughts and a key device to sort out the trillions of columns of data created each day

How data and information are contrastingly related with visualization?

Data visualization is for identifying the notable highlights of a data set.  Data visualization permits to explore, investigate or modify. The making of data visualization is antecedent to the making of information visualization. Information visualization is the aftereffect of such examinations. 

Keep on reading to understand the terminologies “Data visualization and information visualization” in detail.

The 4 Types of Analytics Explained x
The 4 Types of Analytics Explained
What is data visualization? 

A representation of data through graphs, charts and infographics is called data visualization. 

‘Data visualization is the craft of portraying data in a fun and innovative manner. As it resembles combining figures with a good soundtrack.’

With the rise in science and technology, the amount of data collection is increasing day by day and data visualization helps in sorting a large amount of data in a concise and precise manner. Data visualization communicates through the representation of images. 

According to Vitaly Friedman (2008):

6 Types of Data in Statistics & Research: Key in Data Science

       ‘The main goal of data visualization is to communicate data clearly and effectively through graphical means.’

Using different methods of data visualization, it gets easier for everyone to understand when the data is represented through visual images. That is why data visualization is one of the most used techniques in the fields of science and technology these days and it has become a functioning zone of search, education and development. 

Statistics of Data Visualization 

The statistic of the global data visualization market revenue in 2017, was estimated to be 4.51 billion US dollars. The market is expected to increase to 7.76 billion U.S. dollars by 2023, with a CAGR of 9.47 per cent over the forecast period.

Examples 

Data visualization offers a viewpoint on content that may at first appear to be vast or uninteresting. But here are examples of data visualization used in daily life that show the sole genuine cut-off is your creative mind! 

  • Infographics
  • Line Chart
  • Pie Chart
  • Vertical and horizontal bars
  • Area Chart

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5 Best Programming Languages for Data Visualizations

Why Data Visualization is Important in Data Science?

What is information visualization? 

Information visualization is the way of interpreting gathered data into visual terms. It permits us to draw insights from data in a productive and captivating manner. Information visualization helps us figure out data accordingly making it valuable in our lives. From business dynamic to basic course route – there’s a colossal and developing need for data to be introduced with the goal that it conveys esteem.  

Our comprehension of the world is driven by our admittance to data. The incentive of information visualization is to change over an enormous volume of crude information into something that can be rapidly and effectively comprehended. 

‘It is finding the artificial memory that best supports our natural means of perception.’ (Bertin, 1983)

A huge range of Information Visualization devices are accessible today and help to incorporate an expansive scope of computerized services and visual assets that make it simpler to see, control and examine. It helps in about approaching information and existing information streams. 

Stats on Information Visualization

IDC predicts that the Global Datasphere will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025. To keep up with the storage demands stemming from all this data creation, IDC forecasts that over 22 ZB of storage capacity must ship across all media types from 2018 to 2025, with nearly 59% of that capacity supplied from the HDD industry.

Examples

Here is the list of enthralling instances of data representation help in moving in a more creative way to deal with this energizing field.

  • Annual Report
  • Creative Campaign
  • Interactive Infographic
  • Augmented Reality Animation
  • Scientific Simulation

Data Visualization vs Information Visualization 

Comparison

            Data Visualization       Information Visualization

It is about breaking down measurements around the objectives and after-effects of those pathways.

It normally alludes to the spreading out of information ways to accumulate or developing ideas for tackling issues
In data visualization, rising subjects and new improvements cover the utilization of visual strategies to genomics.Information visualization research examines psychological and hypothetical angles.
Its tools help to see and get examples, patterns, and anomalies for the company’s dataIts tools give an open method to see and comprehend organization knowledge following your business cycles and projects

How many tools data visualization covers? 

Burning-through vast arrangements of data aren’t generally clear. Most of the time data collections are enormous to the point that it’s absolutely difficult to recognize anything helpful from them. It’s not as simple that the creators can essentially take a data index with a great many sections and make visualization without any preparation. Indeed, it’s conceivable, yet who needs to burn through handfuls or many hours plotting spots on a dispersed outline? That is the place where data visualization devices and tools are needed. 

Working of tools 

Data visualization instruments and tools give data planners a simpler method to make visual portrayals of enormous informational collections. When managing many thousands or millions of data indexes, they help in computerizing the way of making amazing visualization. Hence, help in making a creator’s work altogether simpler. 

These data visualization would then be able to be utilized for an assortment of purposes, dashboards, yearly reports, deals and showcasing materials and basically, elsewhere data should be decoded right away.

Essential Tools 

Here are the tools listed which are easy to use and give exceptional and fast outputs. 

  • Chart blocks
  • Data wrapper
  • D3.js
  • Google charts
  • Fusion charts
  • Charts.js
  • Grafana                

 How many tools information visualization covers?  

The successful utilization of any innovation in educating requires smart thought and arranging. A tool’s learning benefits rely upon when, how, and why you use it? There are a lot of tools or devices available for information visualization that line up with your objectives, and give you uphold as you choose and coordinate arrangements successfully into your process of interpreting data. Hence, you get huge help in arranging a vast assortment of data with help of these tools. 

Working of tools 

The information visualization tools allude to a wide scope of computerized apparatuses and assets that permit clients to see, dissect, control, or potentially impart complex data, like recorded, spatial, and measurable information. 

Essential Tools 

Information Visualization tools and devices range from unreservedly accessible instruments that produce basic visual portrayals of little informational collections to exclusive apparatuses that can control complex information. Here are few tools’ names given:

  • Geographic Information Systems (GIS)
  • Gapminder.com
  • JMOL
  • Google Earth
  • Microsoft Excel
  • Wolfram Alpha

What makes data visualization more effective than Information Visualization? 

While great data representation will impart data plainly and successfully and unpleasant data visualization will do the inverse. Here are some down to earth tips for how organizations and associations can utilize data visualization to convey data successfully. 

  • Try not to contort the data

This might be the main point in this entire blog entry. While data visualizations are a chance to flaunt your inventive plan and the capacity ought to never be deprived of for style. 

The graph styles, tones, shapes, and estimating you utilize all assume a part in how the information is interpreted. If you need to introduce your information precisely and morally, you need to take care to guarantee that your information perception doesn’t present the information incorrectly. 

  • Recount a story with your data 

Data visualizations like infographics give you the space to consolidate information and story structure in one page. Visuals like symbols and intense text styles let you feature significant measurements and realities. 

  • Consolidate various kinds of data visualizations 

While you may decide to keep your information perception basic, joining different sorts of outlines and charts can help recount a more adjusted story. 

Try not to be reluctant to consolidate graphs, pictograms and charts into one infographic. The outcome will be a data representation infographic that is connecting with and wealthy in visual information. 

  • Use symbols to highlight significant focuses 

Symbols are ideal for drawing in the eye when filtering a page. If there are explicit data focuses that you need to examine to focus on, setting a symbol alongside it will make it more observable.

  • Use tones deliberately in your plan 

In plan, colours are however practical as they may be popular. You can utilize tones to accentuate focuses, classify data, show development and the sky’s the limit from there. 

  • Use recent statistics

If you are setting up an introduction, it’s best not to attempt to pack such a large number of visuals into one slide. Utilize one centre visual and an amazing start to give the extent much more effect. 

 What makes Information visualization effective

Information Visualization assumes a significant part in making information edible and transforming crude data into noteworthy bits of knowledge. It draws from the fields of human-PC communication, visual plan, software engineering, and intellectual science, among others.

 ‘It is the depiction of information using spatial or graphical representations, to facilitate comparison, pattern recognition, change detection, and other cognitive skills by making use of the visual system’ (Hearst 03).

Here are a few points to make it effective and get its amazing outputs

  • Diagram First

The primary standard is maybe the most un-specialized however vital: before you make a visual, focus on the data you need to share, imagine it, and plan it. In corresponding to this methodology, it tends to be a smart thought to save figures you, run over in logical writing that you distinguish as especially compelling. 

  • Use the Right Software 

Powerful visuals regularly require great order of at least one programming. As such, it very well may be unreasonable to anticipate perplexing, specialized, and powerful figures. If you are utilizing a basic accounting page program or some other programming that isn’t intended to make perplexing, then it will give the best outputs. 

  • Utilize an Effective Geometry and Show Data 

Calculations are the shapes and highlights that are regularly inseparable from a kind of figure; for instance, bar math makes a bar plot. While calculations may be the characterizing visual component of a figure, it tends to be enticing to hop straightforwardly from a dataset to blending it with one of few notable calculations. 

  • Shadings and colours Always Mean Something 

The utilization of shading in visualization can be unimaginably incredible. In an enormous study of what makes representations vital and beautiful were accounted for as having a higher memorability score, and that seven or more tones are ideal. 

  • Basic Visuals, Detailed Captions 

However significant as it seems to be to utilize high information ink proportions, it is similarly imperative to have itemized subtitles that completely clarify everything in the figure. 

  • Think about an Infographic 

It is indistinct where a figure closes and an infographic starts; nonetheless, most would agree that figures will in general be centred around addressing information and models, while infographics normally consolidate text, pictures, and other diagrammatic components. It is not prescribed to change all figures over to infographics, infographics were found to have the most elevated memorability score also, that charts beat focuses, bars, lines, and tables.

According to Antonie de- saint Exupery,

  “Perfection is not achieved when there is nothing more to add but when there is nothing to take away”

Reasons why we should choose Data visualization? 

The familiar maxim “A picture is worth a thousand words” is one of the primary reasons we’ve seen a major development towards data visualization over the most recent couple of years.

The human brain measures data, utilizing outlines or diagrams to imagine a lot of complex information is simpler than poring over bookkeeping pages or reports. Data visualization is a fast, simple approach to pass on ideas in a general way – and you can explore different avenues regarding various situations by making slight changes.

It can help to 

  • Recognize zones that need consideration or improvement. 
  • Explain which elements impact client conduct. 
  • Assist you with understanding which items to use.
  • Anticipate deals volumes.

Data visualization assists with recounting stories by curating information into a structure clearer, featuring the patterns and anomalies. It is important in every industry or field. Each STEM field profits by getting information—thus do fields in government, account, showcasing, history, administration businesses, training, sports, etc. 

What’s more, since data visualization is so productive, the better you can pass on your focuses outwardly, the better you can use that data. 

Reasons why we should choose Information visualization? 

The way toward making Information Visualization ordinarily begins with understanding the data needs of the objective client gathering. Information Visualization is getting progressively engaging, particularly when utilized in a site or application. Being interactive considers control of the representation by clients, making it exceptionally powerful in obliging their necessities. With intuitive information representation, clients can see subjects from alternate points of view, and control their perceptions of these until they arrive at the ideal bits of knowledge. This is particularly valuable if clients require an explorative encounter.

Reasons 

Information Visualization assumes a significant part in making information edible and transforming crude data into noteworthy experiences. 

  • It draws from the fields of human-PC connection, visual plan, software engineering, and psychological science, among others. Models incorporate world guide style portrayals, line charts, and 3-D virtual structure or town plan plans. 
  • Information Visualization abilities are popular, part of the way because of the ascent in enormous information. Tech research goliath Gartner Inc. has seen that advanced change has put information at the focal point of each association. With the always expanding measure of data being accumulated and broke down, there’s an expanding need to introduce information in important and reasonable manners.

Reasons to not choose Data Visualization

Data visualization is providing amazing services to clients and gives organizations the most extreme estimation of their information but at the same time, there are some drawbacks tending it to not to use excessively or avoid it.  

  • It gives assessment not exactness 

While the information is precise in foreseeing the circumstances, the representation of similar simply gives the assessment. It most likely is not difficult to change over the heavy and protracted information into a simple pictorial arrangement yet such a portrayal of data may prompt speculative ends once in a while. 

  • Biased 

The fundamental arrangement of Data visualization occurs with the human interface, which means the information that turns out to be the base of perception can be one-sided. 

The individual getting the information for the equivalent may just think about the significant segment of data or the data that necessities centre and may reject the remainder of the information which may prompt one-sided results. 

  • Absence of help 

One of the disadvantages of data visualization is that it can’t help, which means an alternate gathering of the crowd may decode it unexpectedly. Because every person has a different perspective of collecting and assorting data.  

  • Advised plan and design issue 

If the data visualization is viewed as such a correspondence, at that point it must be real in clarifying the reason. Assuming the plan isn’t appropriate, this can prompt disarray in correspondence. It should explain the goal and purpose of the design. In other words, it requires correct verbal information.

Reasons to not choose Information Visualization? 

Although information visualization is a fast and advance method at the same time its following unsolved issues cause a problem due to which it is necessary not to choose information visualization all time without having solutions

  • Usability 

The usability issue is basic to everybody. The intricacy of the basic logical cycle associated with most data representation frameworks is a significant snag; end clients can’t perceive how their crude information is mysteriously transformed into brilliant pictures

  • Understanding Perceptual–intellectual tasks

There is a lack of auxiliary perceptual–intellectual undertakings which is a basic advance toward designing data representation frameworks. The general comprehension of these undertakings should be significantly changed and refreshed in the setting of data representation. Data recovery significantly affects the advancement of data perception as a field. 

Subsequently, plan choices should be made in advance in terms of the degree of earlier information important to comprehend the envisioned data.

  • Intrinsic quality measures 

It’s fundamental for the data representation field to set up inherent quality measurements. Up to this point, the absence of quantifiable quality measures has a direct result of the customer need for unique and imaginative work locally. 

The absence of quantifiable proportions of value and benchmarks will subvert information visualization propels, particularly their assessment and selection. 

  • Scalability 

The versatility issue is a durable test for information visualization. In contrast to the field of logical representation, supercomputers have not been the essential wellspring of information providers for information visualization. Equal figuring and other elite processing procedures have not been utilized in the field of data as much as in logical perception.

To Close

       “The new journey is not made by seeking new lands, but by opening new eyes”

 (Marcel Proust)

Quick Related Questions You Might Have

1- What is the difference between ‘data’ and ‘information’? 

The processed data is called information. Information is prepared, coordinated and introduced data that has meaning and is valuable. Data contains facts and logics. While information is obtained by arranging those facts.

2- What are the benefits of data visualization? 

     Data visualization helps in:

  • Understanding the data clearly
  • Building a relationship among data
  • Comparative analysis
  • Finding the solution to problems
  • Decision making

3- What are the advantages of information Visualization?

    Information Visualization helps in: 

  • Lessening the quest for information 
  • Encoding information in a manipulable medium
  • Utilizing visual portrayals to upgrade the recognition of examples 
  • Empowering perceptual derivation activities 
  • Expanding the memory

Emidio Amadebai

As an IT Engineer, who is passionate about learning and sharing. I have worked and learned quite a bit from Data Engineers, Data Analysts, Business Analysts, and Key Decision Makers almost for the past 5 years. Interested in learning more about Data Science and How to leverage it for better decision-making in my business and hopefully help you do the same in yours.

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