6 Ways of Presenting Data Insights

Presenting data insights doesn’t have to be time-consuming and confusing. This guide covers the top six ways to present data insights effectively and guide stakeholders toward making strategic business decisions.

February 14, 2024
Written By
Rand Owens
Founding team member at Motive (Formerly KeepTruckin) and passionate about all things Marketing, RevOps, and Go-To-Market. VP of Marketing @ Polymer Search.

6 Ways of Presenting Data Insights

Presenting data insights doesn’t have to be time-consuming and confusing.

With the right tools and methods, you can extract vital insights from raw data, analyze them, and present your findings in an understandable manner.

Even if you have a wealth of data, it's of little to no use if not presented effectively; without proper presentation, you and your stakeholders might miss valuable insights.

Presenting data allows you to transform data into actionable insights and communicate them effectively to drive decision-making. 

Data backs this, showing that 65% of the population are visual learners. 

The number highlights how people are more likely to understand and retain information when presented in visual and easy-to-understand formats. 

This guide covers the top six ways to present data insights effectively and guide stakeholders toward making strategic business decisions. 

What is data presentation?

Data presentation is an important step in data analysis that refers to turning raw data into easy-to-understand and interpret formats.

You can present data using charts, graphs, and visualizations to compare two or more datasets and how they relate to other information.

Data presentation turns numbers and figures into compelling stories and visualizations that target audiences can quickly grasp to help them make the right decisions. 

Why presenting data insights is important

95% of businesses see the need to manage unstructured data, which includes presenting data. 

As a crucial aspect of the fundamentals of data analysis, presenting data insights is important because of the following:

  • Alignment and engagement. Presenting data helps foster alignment and engagement among your stakeholders. It ensures everyone is on the same page and understands your company’s objectives and KPIs or metrics.
  • Informed and strategic decision-making. Data presentations allow you to convey the required information to make the right decisions effectively. Presenting data helps you extract insights to spot opportunities, understand trends, and make strategic decisions to improve profitability and business growth.    
  • Effective communication. Data presentations let you convey complex, technical information by turning them into easy-to-digest and actionable insights. It can bridge the gap between your non-technical stakeholders and technical teams. 
  • Competitive advantage. Effective data presentations give you clear, actionable data. It empowers your business to adapt to sudden shifts in the industry, spot market trend opportunities, and stay ahead of your competitors. 

Data visualization pioneer and statistician Edward R. Tufte stresses the importance of presenting and visualizing data to use it effectively by saying, 

“Above all else, show the data.”

How to present data: 6 Steps

Presenting data includes the following essential steps. 

Step 1: Organize your data

Organize your data after going through your objective setting and data collection processes. 

You can categorize your data by time, space, quantity, or quality. 

The process can include making conclusions and determining the relationships between the data points.  

Organizing your data based on identifiable features helps you decide how to present your data best. 

It also makes it easier to compare data and draw critical conclusions to address your research or data analysis questions. 

For instance, you can dive deeper by analyzing productivity among various departments and teams to determine which day of the week your employees are most productive.

Step 2: Determine your target audience

Knowing your target audiences lets you determine how to best present your data to them. 

For example, a more knowledgeable audience means you can present your data with more in-depth information. 

If you present data on your product’s performance to a team, you won’t need to provide as much context and background information as when presenting to investors. 

You can also consider the key information and insights your audience wants to know from your data, including the reaction you expect from them.

For instance, if you want potential investors to invest, present your data to highlight the expected market demands and returns of investing in your product. 

Step 3: Select a presentation type

Choose a presentation type that best fits and conveys your data insights. 

Start by determining the most suitable format for your presentation, including the information you compare with your data. 

Data analysis examples to illustrate this include using pie charts to compare the values of three or four variables to show their percentages. 

You can also use a bar graph to show more precise data value comparisons. 

On the other hand, if the data variable is time or certain characteristics, you can compare them better in tabular format or use textual presentation to provide more context and explain your analysis results. 

Step 4: Label your data

Label your data to make it easier to present. 

You can add diagrams and table titles or labels for the specific data variables. 

Cartograms or pictograms often need a key to share the scale during data presentation. 

The labels help you provide context and emphasize the main points when presenting data. 

Step 5: Highlight your main data points

Convey the main data points easily by highlighting how key data relate. 

For instance, if you present data on the time each team member completes a task, highlight the time intervals and the members who finish tasks quickest or slowest. 

You can also include factors impacting team members' ability to complete tasks.

Determining and emphasizing your data’s main ideas helps organize your presentation. It allows you to communicate data insights and their significance to audiences.  

Step 6: Summarize your findings

Summarize your data findings at the end of your presentation to ensure your audience understands what you want your data to convey. 

Allow time for questions and answers and reiterate key data points and insights. 

Also, anticipate questions on how the data impacts your audiences and the potential actions they can take after understanding your data.  

Best way to present data visually

The best method to present data depends on your data type, audience, how you want to present it, and your data analysis techniques and methods.

Some of the top ways to present your data visually include the following:

  • Bar chart. Bar charts show items or variables from the same category, typically in rectangular bars positioned at equal distances from each other. Bar charts can be simple; each height or length represents its values. They can also be more detailed and complex, such as clustering and stacking bar charts to compare groups within other groups. 
  • Pie chart. Pie charts (or donut charts if they have holes in the middle) are circle charts divided into slices. Each slice represents the relative size of specific data within a whole. You can use a pie chart to show proportions or percentages of survey results with demographic data or customer menu item preferences. 
  • Line graph. A line graph represents a group of data points joined by a straight line. Line graphs can have one or multiple lines to compare how related variables change over time. 
  • Histogram. Histograms are commonly used for understanding a single variable’s distribution and frequency. The data is divided into intervals or bins—each bar’s height represents the count or frequency of data points within that interval.  
  • Heat map. Heat maps represent data density in colors. The higher the number, the more intense the color. 
  • Radar chart. A radar chart shows how data variables start from the same point compared. A radar chart can be better than a bar chart if your data has too many variables. 
  • Scatter plot. Scatter plots are grids that show the relationship between two data variables. Using scatter plots is great for presenting seemingly random data and trends. 

Different ways to present data

Below are the three main ways to present your data. 


Textual data presentation refers to using words to describe relationships between information that you usually can’t display in graphs and other visualizations.  

For instance, you can use text to provide additional context or explanation for your study’s findings. 

Textual data presentations are commonly used for presenting research and sharing new ideas.


Tabular data presentation is about using tables to share large amounts of data. 

The data is organized in columns and rows based on their characteristics for easy comparison and visualization. 

Tabular presentation is easy for audiences to consume since it displays a side-by-side comparison of your data variables.

It’s also a space saver since you can condense information into neat columns and rows. 


As the name suggests, diagrammatic presentation means using images, diagrams, and other visualizations to show data insights. 

The visual presentation gives audiences a glance at your statistical data and includes visualization types such as bar graphs, pictograms, pie charts, and more. 

Diagrammatic presentations are more visual than other methods. These make them great for data optimization and sharing more information about dataset variable relationships and comparisons.

Data alone isn’t enough. You must present data in a way that tells a story, allowing your audience to draw meaningful insights effectively. 

As Bestselling author, Dan Heath once said…

“Data are just summaries of thousands of stories—tell a few of those stories to help make the data meaningful.”

Perfect tool for data presentation

Presenting data can be quick and easy with reliable data analysis tools and Business Intelligence (BI) software like Polymer. 

Polymer offers integrations with multiple platforms such as Google Analytics, Shopify, Facebook Ads, Google Sheets, and more, allowing you to seamlessly pull data sets from your data sources to the platform. 

Polymer’s AI technology can facilitate automated data analysis. It can analyze your data and auto-generate charts and graphs to bring out relevant insights.

Click on the AI’s suggested insights, and you’ll get a stunning and appropriate chart, graph, or map in seconds. 

Polymer’s intuitive Board Designer allows you to edit and customize your data visualizations without a hitch.  

The editing features let you add, switch, and change your data visualizations’ elements, order, and arrangement. 

You can also use the AI to get suggestions, making it easy to learn how to build an ecommerce dashboard and other visualization and presentations in seconds. 

If you don’t want to build your presentations, resorts, and dashboards from scratch, use Polymer’s customizable templates. 

You can replace the data and tweak the visualizations, and your data is ready for presentation and sharing with stakeholders. 

Presenting data is a breeze with the right tactics and tools

Get the most out of your data by creating beautiful, easy-to-understand presentations, enabling swift insights and informed decision-making for all stakeholders.

Leverage BI platforms like Polymer to supercharge your data presentation process.

Try Polymer for free to explore its features and benefits, including how it can streamline presenting data. 

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