Data Visualization has become a necessity these days from being an option in the past. The world of business has attested to the use of data for informed decision making. Data Visualization empowers businesses to make complex data more accessible, understandable, and usable. The primary shift towards Data Visualization necessitation is because:
Decision-making is becoming increasingly reliant on data, which comes at such a breakneck speed and volume that we can't comprehend it without some form of abstraction, such as a visual one.
Even non-statistical data, however, necessitates visual representation. Complex systems, such as business process workflows or how customers travel through a store, are difficult to comprehend, let alone fix if one can't see them first.
How is Data Visualization so important?
To communicate information clearly and efficiently, data visualization uses statistical graphics, plots, information graphics and other tools. Numerical data may be encoded using dots, lines, or bars, to visually communicate the heavy data. Effective visualization helps users analyze and reason about data and evidence. One may have analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables.
Transforming data into visuals is now simple (and inexpensive) for everyone, independent of data or creative expertise, much for the internet and an increasing variety of affordable tools. However, one disadvantage is that it encourages you to “click and viz” without first considering your intent and objectives. It's too easy to mistake convenience for quality. Convenience may seem like a nice substitute for good, but it will result in charts that are only adequate, if not ineffectual. Converting spreadsheet cells to a chart automatically just visualizes portions of a spreadsheet; it does not capture an idea.
Building a Thoughtful and Productive Visualization Strategy
It has been observed time and again, Managers who want to improve their charting skills frequently begin by understanding rules. When is it OK to use a bar chart? Is there such a thing as too many colors? What should you do with the key? Is it necessary for me to start my y-axis at zero?
Knowing visual grammar is vital and valuable, but it doesn't guarantee that you'll be able to create good charts. To begin with, chart-making guidelines are to abandon strategy in favor of execution; it's like packing for a vacation without a map.
Your visual communication will be significantly more successful if you first recognize that it is a series of tasks, each of which necessitates different forms of planning, resources, and abilities.
Consider the nature and goal of your vision before you begin thinking visually:
Is the data or the information conceptual?
Is this a declaration or an exploration?
You can plan what resources and tools you'll need if you know the answers to these questions, and you can start figuring out what style of visualization will help you reach your goals the most efficiently if you know the answers to these questions.
The above diagram highlights how an effective data visualization strategy works and how there is an easy way to achieve the same by the power of following a step-by-step approach.
Tips and Tricks for Effective Data Visualization
Finally, we have some surprising yet effective tips and tricks for Data Visualization that has always been highlighted and accepted by the experts in the world of effective visualizations.
Less is more: The art of omission is to be cherished. You should highlight what’s important, leaving out what isn’t.
Choose your colors with care: Use of appropriate colors can highlight and clarify, while inappropriate use will obscure and conceal information.
No more gauges: Although the use of gauges and speedometers in dashboards is quite popular, there are better and more effective visualizations available that also take up less space.
Start at zero: With a bar chart, always allow the vertical to start at zero, to prevent graphs from being wrongly interpreted.
Show the difference: If you want to compare two series, you can also highlight the difference between the two.
No more pies: The pie chart is colorful and popular, but not always effective. Find relevance of its use to use it.
Highlight what’s Appropriately Important: Keep a dashboard neutral and highlight what is important, like the current position, or a different value.
Graphs from another angle: A horizontal bar graph is often the best choice when long labels are used or when you want to show the hierarchy.
In some senses, the term "data visualization" is a misnomer. It appears to reduce the process of creating good charts to a mechanical one. Rather than the creation itself, it conjures the instruments and processes needed to create. It also illustrates the dataviz world's continued concern with procedure above results.
Visualization is nothing more than a method. When we produce a fantastic chart, we get at some truth and inspire people to feel it—to see something they couldn't see before. To sway people's opinions. to elicit a response.
At Merkle Sokrati, we provide a holistic approach in understanding your requirements and connecting them with the best possible measures. We are happy to provide you services like Data Management Platforms, Analytics Platforms, Web Personalization Platforms, Tag management services etc.
If your business needs help in utilizing the best out of Data Analytics and Visualization, we’re here to help.