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Why Visual Analytics is important?

Blog | December 30, 2022 | By Karishma Vadher

There is no doubt on how data visualization is significant for companies to make remarkable decisions throughout their business.

At the current time companies has their data warehouse systems to record their activities and operation in different databases, searching for a method to represent your data creatively to ensure that it will be understood and remembered. The human brain processes images 60,000 times faster than text, and 90 percent of information transmitted to the brain is visual.

The purpose of data visual analytics in any company is to help the business to recognize the behavior of certain trends and understand the areas which need attention, it facilitates understanding the statistics to measure its impact at the commercial & enterprise level and communicates the perception visually to internal and external audiences. Preparing a plan to create a visual report is the most essential element of any visual analytics. It is an iterative plan which would help us to save future hours of blood, sweat, and tears.

Wait! Please do not start to create graphs. Let’s do our planning first so, we can save hours of blood, sweat, and tears in the long run.

Here are a few crucial steps to create a data visualization strategy and prepare easily interpreted visualizations.

1. Define the clear problem: The first and foremost step is to identify the issue we are trying to resolve and think about deliberate questions we need to answer. What strategic problem would you be solving? To answer this question, you need to determine various metrics and KPIs (Key Performance Indicators). KPI will help you understand the performance of the organization in a particular area. Correct should act as a compass that would show whether the path you are taking is valid to solve your strategic issues. More information can be found in USEReady MAD methodology article Mad Framework For Actionable Dashboards

2. Who will be your audience? What level of complexity your audience would understand? The visualization strategy you select should be able to convey your message precisely. For example, an executive would prefer a high-level summary whereas a financial analyst would be more interested in a granular level of details.

3. Do you know the data? You need to have the right data to highlight your strategic questions. Do you have the right data available? If yes, do you understand the data? Perceiving data will give a direction to your thought process and discover different hidden patterns of data. Is the data clean and in an understandable format? Before creating any graph, it is important to check if we have cleaned data. If not, what data structure we would need to create the report There are a few data exploratory methods and tools which will help you to succeed in this step.

4. Create a Wireframe of your report: Wireframe act as a skeleton of your dashboard. The most visually engaging phase of the visualization creation is the design phase where the wireframe is prepared. It helps to identify any issue early in the design phase which saves time and money that is often lost in solving strategy problems down the road. It consists of various dashboard elements such as what functionalities will be available on the dashboard, what type of graphs will be used, what parameters and filters would be used, how each element will be placed on the dashboard, Font style & type, graphs & font colors, etc. It helps to map out the dashboard in the early stage, so it is much less painful to make changes at this stage and create an efficient dashboard visualization.

  • Choose the right Visuals: There is an enormous number of graphs or charts available. However, selecting the correct chart type is dominant. It might sound easy but trust me it’s not as easy as it looks. Wrong chart representation could mislead the audience and affect the decision making hence to convey the right message it is consequential to pay supreme attention to graph selection. How to select the chart is based on what message you want to transfer. Whether you want to show trends to analyze historic patterns, the relationship between various elements (majorly used to show categorical data), Break up points of whole data, data distribution, or compare categories with each other. Find more details here using Tableau Chart selection white paper (
  • Select the right colors: As we know, color affects the perception of information we take it so, selecting the right colors is as important as choosing the correct graph. According to  MIT neuroscientists color shape and orientation is processed in a bit of 13 milliseconds hence meticulously selected colors equipage the pre-attentive processing power of the human brain this helps your audience to encode the value of the visuals and distinguish the important data points. On the contrary, badly selected colors could make your visualization less efficient and mislead the information. Check the color palette requirement from the client

5. Prepare a story: Telling the story behind the data is the most significant step. Data-driven storytelling is the dominant method of communicating statistics and numeric to the intended audience based on the visuals. Ask yourself how you would like to convey the story. What was the purpose of preparing the visual report? How are these graphs helping you to answer all your questions? Is there any correlation or trend you found in the visuals which audience should focus on? How would you guide audiences to a conclusion? These questions would help to prepare an excellent visual story for your audiences.

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About the Author
Business Intelligence Analyst with experience in Tableau Development, Data Analytics, Data Wrangling and Machine Learning in various domains.
Karishma Vadher | BI Analyst | USEReady
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