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4 Ways the Finance Sector Can Benefit from Data Visualization

When using data, visualization for explaining the information is more transparent. Data visualization is leading the way in advanced data analytics for everyday operations.
Desireé Duffy is a marketer, author, media expert, and Founder of Black Château—a public relations and marketing agency specializing in promoting authors, books, small press, personality brands and creative companies. She chairs AWM SoCal’s Advisory Board and sits on two advisory boards for the Lifeboat Foundation. An award-winning marketer, she writes about digital media, online marketing, technology, and topics with social impact.
Desireé Duffy is a marketer, author, media expert, and Founder of Black Château—a public relations and marketing agency specializing in promoting authors, books, small press, personality brands and creative companies. She chairs AWM SoCal’s Advisory Board and sits on two advisory boards for the Lifeboat Foundation. An award-winning marketer, she writes about digital media, online marketing, technology, and topics with social impact.

There are piles of data used in the financial sector, and with so much data to sift through, traditional business tools that were created for tabular reporting, sometimes just don’t cut it in today’s business world. Business intelligence (BI) tools designed today can process and analyze large volumes of data with real-time speed and unseen sophistication. Data visualization is leading the way in advanced data analytics for everyday operations.

Data visualization is the graphic demonstration of data, which involves producing images that communicate relationships among the represented data to viewers of the pictures. This type of communication is received through the use of a systematic mapping between visual characters and data values in the formatting of the visualization. Excel data visualization uses graphical representation to display sets of data. A chart is a visual representation of the data, in which the statistics are signified by figures such as bars in a bar chart, or lines in a line chart.

Data visualization tools are used for both data discovery and for explaining data to others. Using data visualization for exploring is useful when you are not sure what the data will tell you. And when you are trying to get a sense of the relationships and patterns contained in the information. Exploring data visualization is best completed in a way that it can be repeated quickly and experimented upon, so that you can find valuable information and disregard the noise.

When using data, visualization for explaining the information is more transparent. The ability to pare down the information from its basic form will increase the efficiency so decision-makers can better understand it. This approach is usually taken once you have an understanding of what the data is telling you, and when you know what you want to communicate with others.

Whether for managing business operations, meeting regulatory, compliance requirements or understanding customer behaviors, data visualization is evolving from being the nice-to-have to the must-have tool for the financial sector. Data visualization tools transform data into something visual, tangible and relatable, which helps in making informed, data-driven decisions. Here are four ways data visualization is beneficial to the financial sector:

1. Building and Absorbing Information

Data visualization enables users to receive large amounts of information regarding operational and business conditions. The information reported allows decision-makers to see connections between multidimensional data sets and provides new ways to interpret data through the use of heat maps, fever charts or other graphical representations. The application of visual data helps businesses quickly find the information they need and boosts productivity.

2. Visualize Connects and Patterns in Businesses

Data visualization provides a multifaceted view of business and operating dynamics and permits senior executives to effectively see connections that are occurring between working conditions and business performance. The opportunity to make these correlations about the data allows executives to identify problems and act quickly to resolve it.

3. Working on Developing Trends Faster

Companies can collect a lot of data on customers and market conditions, which in return, can provide them with insights into new revenue and business opportunities. Data visualization enables decision-makers to grasp shifts in customer behavior, and market conditions across multiple data sets much more efficiently. It can be used to get insight into customers’ sentiments, and other data reveals emerging opportunities.

4. Promotes Comprehension and Simplifies Information

Today, data visualization is being embraced in businesses like never before. Companies that understand the importance of data visualization are happy that these tools exists. Businesses are looking for better data visualization tools to turn their essential information into something more understandable. For example, the reasons below can further explain why data visualization is crucial in interpreting data:

  • The human brain processes entire images that are seen through the eyes in 13 milliseconds.
  • Approximately 80% of the information that consumers take in is through the eyes.
  • The human brain is able to handle images 60,000 times faster than words.

Data visualization is one of the most significant ways for our brains to analyze and comprehend data. The process of placing data in graphic form will help decision-makers better understand the data and present it quickly. They will be able to compare multiple pieces of information, set goals and objectives based on the information given.

The best data visualization tools expose new information about underlying patterns and relationships contained within the data. Understanding those relationships and to be able to observe them is vital to making better decisions.

As the need for data continues to grow, more and more businesses will deal with numerous variables, and data visualization will become more critical.