Turning Data into Insights and Business Value


It’s more crucial than ever to have easy ways to see and comprehend data in our increasingly data-driven environment. After all, employers are increasingly looking for workers with data capabilities. Every level of employees and business owners must comprehend data and its implications.

Data visualization is helpful in this situation. Data visualization in the form of dashboards is the preferred method for many firms to evaluate and communicate information with the aim of making data more accessible and intelligible.

What is data visualization ?

Data visualization is the process of displaying data using common graphics like infographics, charts, and even animations. These informational visual displays convey complicated data relationships and data-driven insights in a simple manner.

Data trends, outliers, and patterns can be seen and understood more easily with the help of data visualization tools. Additionally, it gives staff members or business owners a fantastic way to present data to non-technical audiences without causing confusion.

Data visualization is an important step in the data science process because it allows teams and individuals to communicate data more effectively to colleagues and decision makers. To monitor performance, teams that manage reporting systems typically use defined template views.

Are there any advantages or drawbacks to data visualization ?

It may seem like there are no drawbacks to something as straightforward as presenting data as graphics. However, when data is presented in the incorrect data visualization style, it can occasionally be misrepresented or misinterpreted. The best course of action is to consider both the benefits and drawbacks before deciding whether to create a data visualization.


Colors and patterns catch our attention. We can quickly distinguish between red and blue, as well as squares and circles. Everything in our culture is visual, from art and advertisements to TV and movies. Data visualization is another form of visual art that captures our attention and keeps it there. When we look at a chart, we can quickly identify trends and outliers. When we see something, we quickly internalize it. It’s narrative with a purpose. If you’ve ever looked at a massive spreadsheet of data and couldn’t find a trend, you understand how much more effective a visualization can be.

Other benefits of data visualization include :
  • Easily sharing information.
  • Interactively explore opportunities.
  • Visualize patterns and relationships.

While there are numerous advantages, some disadvantages may be less obvious. When viewing a visualization with many different datapoints, for example, it’s easy to make an incorrect assumption. Sometimes the visualization is simply designed incorrectly, resulting in bias or confusion.

Other disadvantages include :
  • Biased or inaccurate information.
  • Correlation doesn’t always mean causation.
  • Core messages can get lost in translation.
Types of data visualization
  • Pie charts and stacked bar charts : These graphs are divided into sections that represent parts of a whole. They provide a simple way to organize data and compare the size of each component to one other.
  • Line charts and area charts : These visuals show change in one or more quantities by plotting a series of data points over time and are frequently used within predictive analytics. Line graphs utilize lines to demonstrate these changes while area charts connect data points with line segments, stacking variables on top of one another and using color to distinguish between variables.
  • Histograms : This graph plots a distribution of numbers using a bar chart (with no spaces between the bars), representing the quantity of data that falls within a particular range. This visual makes it easy for an end user to identify outliers within a given dataset.
  • Scatter plots : These visuals are beneficial in reveling the relationship between two variables, and they are commonly used within regression data analysis. However, these can sometimes be confused with bubble charts, which are used to visualize three variables via the x-axis, the y-axis, and the size of the bubble.
  • Heat maps : These graphical representation displays are helpful in visualizing behavioral data by location. This can be a location on a map, or even a webpage.
  • Tree maps : which display hierarchical data as a set of nested shapes, typically rectangles. Tree maps are great for comparing the proportions between categories via their area size.
Why is data visualization important ?

The significance of data visualization is straightforward. It allows people to see, interact with, and better understand data. The right visualization, whether simple or complex, can bring everyone on the same page, regardless of their level of expertise.

How Data Visualization helps businesses  ?

Data visualization helps business users to get insight into huge amounts of data. It helps them recognize new patterns and imperfections in the data. Making sense of these patterns allows users to pay focus on areas that represent red flags or progress. This process, in turn, moves a company forward.

Another advantage that data visualization provides is a wonderful method to extract meaningful tales from data. For example, you may use heat maps to track the growth of a given product or how it has performed over time in different geographic areas.

It allows decision-makers to rapidly evaluate which items and locations are working very well vs which are underperforming, allowing them to make the required changes quickly. Big data visualization tools provide a profitable approach to leverage data and deliver crucial insights that can be used to design better marketing strategies that are tailored to each location and assist support sales growth.

Using the Right Visualizations

A graph may look nice, but that doesn’t guarantee it expresses information in an easy-to-understand and analyze manner. Nothing is worse than looking at a chart and not knowing what you’re supposed to get out of it.


Data visualizations should organize and show data in a consistent manner so that the audience can understand what is going on and take appropriate action. As firms acquire more data, visualizations become increasingly important in communicating real-time, actionable information.

However, organizations frequently fail to select acceptable visualizations for their data, which obscures the “so what?” and leaves the audience unsure of what to do. To ensure that data visualizations have genuine commercial value, you must understand how to represent your data graphically.