How Charts Help in Data Analysis and Interpretation

Charts can help you to analyze data and interpret it, as well as to make it accessible to an audience. We provide a guide on how to know which chart to use and when. Continue reading

Published by
Boris Petrov

Every chart is different, and although sometimes more than one chart can be used to display a set of data, others will not fit. Charts can help you to analyze data and interpret it, as well as to make it accessible to an audience. We provide a guide on how to know which chart to use and when.

Select the Most Suitable Software

With the right software, you can make a flowchart in minutes or create a bar graph for a presentation. Selecting suitable software will give you multiple options for making various kinds of charts, maps, and graphs.

The more options you have, the more choice you have, and the more likely it is that you will give an outstanding presentation that gets your point across. You can compare tools like visio or visio alternatives to find the right tool for yourself. 

Determine your Objectives

There is always an underlying objective of why you want to analyze a set of data.

  • Is it to determine which teams are not performing to the required standard?
  • Do you need senior management to use the information to make a decision?
  • Are you trying to select between two or more options that you are comparing?

The possibilities are untold.

Start by identifying your objectives and who you are presenting them to. Determine if it is for information purposes only, e.g., background or context, whether you want to propose a new idea, or to solve an issue.

A chart is useful for comparisons of items with different values. It can make the whole and the parts clear. Alternatively, you can use it to analyze trends. Once you are clear on your objectives, choosing the right graph, map, or chart is greatly simplified.

Select the Most Suitable Chart

Select the most suitable chart. You may be familiar with using bar graphs, for example, but this might not be the right way to visualize your data sets. It is essential to become comfortable with using more than one type of chart if your viewers or readers are not to be confused. Deferring to your favorite chart may lead to wrong interpretations of data. The chosen chart must make your point effectively and it needs to be clear, accurately labeled, and appropriate.

Displaying Composition

If you want to express the different aspects of the whole, you will want to use pie, waterfall, area, or stacked bar graphs. This could be how different product sales lead to the total sales income. You can show this in a pie graph, for example, and use percentages for easy comparison.

Distribution of Data

The data may cover a wide range, with some areas denser than others, for example, sales per person. There are also likely to be outliers, such as someone who reaches high targets or those who underperform. Distribution charts include scatter plots, bar, column, or line graphs. You may have to play around with one or two before deciding on the most presentable one that conveys your point clearly.

Analyzing Trends

You may want to compare the quarters of this year to the previous year’s quarters. This will allow you to remove any confusing seasonal trends and is useful for selecting sales strategies but not as pertinent for year-on-year sales. Charts that are good for trend analysis are column, dual-axis line, and line graphs.

How Value Sets Relate

The influence of one variable on another variable can help you understand how a project is doing, or which sales platforms to use. For example, how many sales were closed using an email marketing strategy compared to a social media strategy. Useful charts are line graphs, bubbles, and scatter plots.

Know your objectives, become familiar with using different charts and graphs, and you will add greater meaning to reports and presentations.

How Charts Help in Data Analysis and Interpretation was last updated April 24th, 2026 by Boris Petrov
How Charts Help in Data Analysis and Interpretation was last modified: April 24th, 2026 by Boris Petrov
Boris Petrov

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