Data visualization

From raw data to actionable insights: The role of data visualization in business analytics

Imagine a world where instead of looking at huge rows and columns of data, you could see the story behind the numbers come to life in colorful and interactive charts and graphs.

Studies show that 90% of the information transmitted to our brain is visual and 50% of the human brain is used for processing visual information. Yes! That’s what Data visualization is all about.

What is data visualization in the context of business intelligence?

Data visualization is the process of representing data and information in a visual format, such as charts, graphs, and maps. The purpose of data visualization in BI is to communicate complex data sets in a clear, concise, and easily understandable way, and to help business users and decision-makers understand, analyze, and make better decisions based on data.

Data visualization can be used to represent a wide variety of data, including numerical data, categorical data, and spatial data. It can be used in a variety of fields, including business, science, education, and journalism.

There are many different tools and techniques used in data visualization, including bar charts, line graphs, scatter plots, heat maps, and geographical maps. These visualizations can be created using software tools or by hand using drawing tools.

Overall, data visualization plays an important role in helping people understand and make sense of data, and it is used in many different contexts to help people make informed decisions based on data.

To understand this in simpler terms, let's say a company wants to know how many products it sold last year. They might have a table with all of the sales data, but it could be hard to understand just by looking at the numbers. Instead, they could use data visualization to create a bar chart that shows how many products were sold each month. This would make it easier to see how the sales changed over time and identify any patterns or trends.

Why is data visualization important for business intelligence?

Data visualization is like the cherry on top of your business intelligence sundae - it takes all of the insights and information you've gathered and presents it in a way that's not only easy to understand but also visually appealing.

Data visualization can be helpful in many different ways in business intelligence. It can be used to see how a company's sales or profits are changing, to compare different products or regions, or to understand customer behaviours. By using data visualization, people can make better-informed decisions based on the data they have.

It allows users to quickly see patterns and trends in data, identify outliers, and discover relationships and correlations that may not be immediately apparent from looking at raw data. It can also help users to identify key performance indicators (KPIs) and measure the success of business strategies, processes, and initiatives.

How does data visualization help enhance the value of business intelligence?

Data visualization plays a key role in BI by helping users to understand and make sense of data, communicate data-driven insights, and make better-informed business decisions.

1. Improved understanding: Data visualization helps to make complex data sets more understandable and easier to interpret. It allows users to quickly see patterns and trends in data and identify key performance indicators (KPIs), which can help inform business decisions.
2. Enhanced communication: Data visualization can be a powerful tool for communicating data-driven insights to a wide audience. It allows users to present data in a clear and visually appealing way that can be easily understood by non-technical stakeholders.
3. Increased efficiency: Data visualization can help users to quickly identify trends and patterns in data, which can save time and effort in data analysis and decision-making processes.
4. Increased collaboration: Data visualization can facilitate collaboration among team members by providing a shared view of data and allowing users to discuss and analyze data together.
5. Improved decision-making: Data visualization can help users to identify key trends and patterns in data, which can inform better business decisions. It can also help users to identify areas for improvement and measure the success of business strategies, processes, and initiatives.

What are the best practices for data visualization in business intelligence?

Here are some best practices for data visualization in Business Intelligence (BI):

1. Use appropriate chart types for the data: Choose the right type of chart or graph to effectively display your data. For example, use a bar chart for comparing categorical data, and a line graph for showing trends over time.
2. Use clear and concise labelling: Label your charts and graphs clearly and concisely to help users understand the data. Use meaningful titles and axis labels and consider adding data labels or hover-over text for additional context.
3. Avoid clutter: Keep your visualizations clean and uncluttered to avoid overwhelming users with too much information. Use effective design principles, such as using white space, aligning elements, and using consistent colours and fonts.
4. Use accurate scales: Use appropriate scales on your axes to accurately represent the data. Avoid using a scale that distorts the data or misleads the viewer.
5. Use meaningful summaries: Summarize your data effectively by using appropriate measures of central tendencies, such as mean, median, or mode. Avoid using misleading statistics, such as the range or standard deviation, without proper context.
6. Test your visualizations: Test your visualizations with a small group of users to ensure that they are effective and easy to understand. Seek feedback and make adjustments as needed.

By following these simple practices, you can create effective and meaningful data visualizations that help users to understand and make better decisions based on data.

We at Kulsys understand the importance of data visualization in Business Intelligence (BI). Our team of expert data analysts and visualization specialists can help you to effectively communicate complex data sets and drive better decision-making within your organization.

Still, confused about where and how to start with business intelligence visualization in your organization?

Contact us today to learn more about how our data visualization services can help your business succeed.