Data Visualization: Why Does It Matter in Businesses?

Bineesh Mathew | February 18, 2022 | 109 views

Data Visualization

Data visualization refers to a graphical representation of information that displays patterns and trends while allowing viewers to gain rapid insights. Data visualization is critical for businesses to quickly detect trends in data that would otherwise be time-consuming. However, making sense of the quintillion bytes of daily data is difficult without data proliferation, including data visualization.


Understanding data is beneficial to every professional business; hence, data visualization is spreading to all fields where data exists. For any company, data is its most valuable asset. One can effectively communicate their points and use that knowledge by using visualization.

"Data visualization is a great way to simplify data and show it in a form that is understandable, insightful, and actionable. Data visualization is being increasingly seen as the vital final step of any successful data-driven analytics plan."

Caroline Lee, CocoSign

Why Does Data Visualization Matter?

As we acquire more and more data, data visualization becomes increasingly critical, to the point where we are nearly drowning in information, and it is difficult to distinguish what is significant and what is not—for example, the product development program for a new automobile or plane. Analyzing test data is vital, but a massive amount of information is created with each test drive or flight, making processing at the required speed challenging. Visualization tools help comprehend complex data and detect patterns and anomalies.

  • Visual information accounts for 90% of the information sent to the brain.
  • Data visualizations can shorten business meetings by 24%.
  • Managers who use visual data recovery tools are 28 percent more likely than those who rely on managed reporting and dashboards to find timely information.
  • 48% of these managers can find the data they need without the help of I.T. staff.
  • For every dollar spent on business intelligence with data visualization skills, $13.01 will be returned.

Let us look into some of the benefits of data visualization in businesses.

The Creditable Impact of Data Visualizations on Business

While big data is ruling industries, business intelligence transforms much of this data into actionable data points. As a result, data visualization plays a role in transferring information to the human brain by swiftly presenting data.

Visualization has a lot of aesthetic importance in representing and conveying a clear message. Businesses that rely solely on data will eventually go out of business if data visualization is not implemented. Data visualization's competitive benefits can make or kill enterprises. It is critical to know that there are no shortcuts to making faster and better judgments without visualizing the data.

Data Visualization Helps You Take Better Decisions Based on Data

Unlike meetings that focus on text or numbers, business meetings that address visual data tend to be shorter and easier to reach consensus on. Data visualization speeds up decision-making and allows viewers to better understand patterns and trends.

The benefits of data analytics can be accessed across all departments, right from admin to IT, sales to marketing. Even if they are not experts at reading data, your sales team can better understand consumer behavior and impressions if the correct data visualization solutions are in place. With the proper training and tools in place, you can build specialists using data visualization, a combination of technical analytics, and artistic narrative.

When visualizations are created to meet your business goals, you will obtain the best results. For example, some data visualizations help in analysis, while others make the data visually appealing. Some are created to demonstrate concepts, processes, or tactics to various audiences. You can create your own based on your specific goals, data types, and stakeholder requirements.

Data Visualization Is a Medium to Tell a Data Story to the Viewers

Data visualization can also tell a story about data to the audience. The visualization can convey facts in an easy-to-understand format while creating an account and bringing the audience to a predetermined conclusion. This data tale should have a strong start, a basic storyline, and a logical decision like any other story.

If a data analyst is tasked with creating a data visualization for company leaders that details the profitability of various items, the data story could begin with the profits and losses of multiple products before moving on to advice on how to address the failures. Create your own depending on your specific goals, data types, and stakeholder requirements.

Data Visualization Helps You Gather Data Faster and Saves Time

Data visualization is a much faster way to get insights from data than examining a chart. Using data visualization, business meetings can take decisions faster, saving time. When the long meetings are cut short by utilizing data visualization, businesses can dedicate more time to other core business activities.

Summing up

To develop excellent data visualizations, various tools and methodologies are available. You and your team must comprehend the fundamental principles and choose appropriate tools. Above all, the data must be presented accurately. Layouts, colors, text, and dashboards must be appropriately crafted to build data visualizations that best help your business objectives.

Frequently Asked Questions


Why is data visualization important?

Presenting data in a visual or graphical style is known as data visualization. It allows decision-makers to see analytics in a graphic format, making it easier to grasp complex topics or spot new patterns.

What are some of the types of data visualization?

There are several types of data visualization. They are line graphs, scatter plots, pie charts, heat maps, area charts, histograms, and choropleths.

What are the main goals of data visualization?

The main goals of data visualization are to understand your audience, stick to a strict timeline, and deliver a compelling story.

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Veda Advantage Limited

Veda Advantage Limited, formerly Baycorp Advantage Limited, is a provider of credit information. It is engaged in the provision of business intelligence services. The Company's activities include data-driven services and solutions in relation to credit risk, marketing, decisioning, fraud prevention and identity verification. It…

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AtScale Announces Data Science and Enterprise AI Capabilities Within Semantic Layer Platform

AtScale | September 29, 2022

AtScale, the leading provider of semantic layer solutions for modern business intelligence and data science teams, today announced at the Semantic Layer Summit an expanded set of product capabilities for organizations working to accelerate the deployment and adoption of enterprise artificial intelligence (AI). These new capabilities leverage AtScale’s unique position within the data stack with support for common cloud data warehouse and lakehouse platforms including Google BigQuery, Microsoft Azure Synapse, Amazon Redshift, Snowflake, and Databricks. Organizations across every industry are racing to realize the true potential of their data science and enterprise AI investments. IDC predicts spending on AI/ML solutions will grow 19.6% with over $500B spent in 2023. Despite this investment, Gartner reports that only 54% of AI models built will make it into production, with organizations struggling to generate business outcomes that justify investment to operationalize models. This disconnect creates an enormous opportunity for solutions that can simplify and accelerate the path to business impact for AI/ML initiatives. The AtScale Enterprise semantic layer platform now incorporates two new capabilities available to all customers leveraging AtScale AI-Link: Semantic Predictions - Predictions generated by deployed AI/ML models can be written back to cloud data platforms through AtScale. These model-generated predictive statistics inherit semantic model intelligence, including dimensional consistency and discoverability. Predictions are immediately available for exploration by business users using common BI tools (AtScale supports connectivity to Looker, PowerBI, Tableau, and Excel) and can be incorporated into augmented analytics resources for a wider range of business users. Semantic predictions accelerate the business outcomes of AI investments by making it easier and more timely to work with, share, and use AI-generated predictions. Managed Features - AtScale creates a hub of centrally governed metrics and dimensional hierarchies that can be used to create a set of managed features for AI/ML models. Managed features can be sourced from the existing library of models maintained by data stewards or by individual work groups. Furthermore, new features created by AutoML or AI platforms can also become managed features. AtScale managed features inherit semantic context, making them more discoverable and easier to work with, consistently, at any stage in ML model development. Managed features can now be served directly from AtScale, or through a feature store like FEAST, to train models in AutoML or other AI platforms. “Despite rising investments, greater adoption of AI/ML within the modern enterprise is still hindered by complexity. “The need for AI is huge, exploration is on the rise, but many businesses are still not able to use the predictive insights AI models can generate. Here at AtScale we can leverage our unique position in the data stack to streamline and simplify how the business can consume and use AI immediately, generating faster time to value from their enterprise AI investments.” Gaurav Rao, Executive Vice President and General Manager of AI/ML at AtScale About AtScale AtScale enables smarter decision-making by accelerating the flow of data-driven insights. The company’s semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across all industries. With AtScale, customers are empowered to democratize data, implement self-service BI and build a more agile analytics infrastructure for better, more impactful decision making.

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