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Choosing the Right Visualization Type for a Project Report

03rd May, 2024
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    Choosing the Right Visualization Type for a Project Report

    Data visualization is a way of creating a picture with your data rather than leaving it on a spreadsheet. There are a lot of different types of data visualization, and selecting the Right Data Visualizations for a project depends on what you’re trying to show. Visualization can be used to compare values, show the composition of something, and help you to analyze trends in the data. 

    Before proceeding further, check out the article on Power BI Developer Future.

    Are you comparing values?

    If you want to compare values, there are different types of charts to represent data that can be used. These are as follows :

    1. Column charts can show comparisons of different items or a comparison of items over time.
    2. A mekko chart not only compares values but also measures their composition and demonstrates how data is distributed across each value.
    3. Bar graphs are useful because they prevent clutter when you have a very long data label or a lot of values to compare. 
    4. A pie chart shows how much certain categories make up the total percentage. Line graphs can show how values progress and change over a period of time, and can show many categories at once.
    5. Scatter plot charts, show the relationship between two different variables and are useful for determining your data’s distribution.
    6. Bullet graphs show progress towards a goal, compared to another value, and given a rating.

    Let’s take a look at the different types of charts and their uses-

    1. Are you showing the composition of something?

    If you want to visually represent how much certain parts contribute to the whole, you can use pie charts, stacked bar graphs, mekko charts, stacked columns, area charts, and waterfall charts. These kinds of visualizations and graphs for your project are useful for displaying data such as your total sales, broken down by representative, or by-product.

    2. Are you trying to better understand the distribution of your data?

    If you’re looking closely at your distribution, it probably means you’re searching for outliers and trying to see what the normal tendency actually is. Mekko charts, line charts, columns, bar graphs, and scatter plots can be used. Scatter plot charts and show the relationship between two sets of variables.

    3. Are you analyzing trends in your data?

    Sometimes you’ll want to know how your variables did during a certain time period. It is good to display this kind of information using line charts, dual-axis charts, and columns. A dual-axis chart is unique. It allows you to plot two y-axes that share an x-axis. Dual-axis is used to see if there is a correlation between the three data sets.

    Proper use of number charts

    “Number charts are used for showing an overview of key performance indicators (KPI), the only decision to be made with number charts is the time period you would like to show. They can show the latest quarter or a company’s entire history,” advises Paul Drolet, data analyst at Writemyx. Avoid using too many number charts, or your point will become diluted.

    Proper use of line charts

    Line charts are mostly used to show trends because they visualize a continuous string of data over time. Adding in goal lines can show how close actual performance came to reaching, or exceeding, benchmarks that were set. Very useful because they can be effectively combined with other types of visualization, such as bar graphs. Try to avoid creating line charts with a lot of variables, because they will become very hard to read.

    Proper use of horizontal bar graphs

    If you’re wanting to visualize some comparative rankings, then horizontal bar graphs are your go-to. They can also be used to represent values with very long names, just be sure they are placed in a logical order in that case, such as alphabetical. Avoid using horizontal bar graphs if you have a lot of values to represent because it looks overcrowded.

    Proper use of stacked charts

    You can use stacked charts when you are comparing data to itself, basically comparing percentages of a whole. “Pie charts and stacked bar graphs are two examples of stacked charts, but best used for different purposes. Pie charts should be used to represent single part-to-whole relationships, while stacked bar charts can be used to visualize multiple part-to-whole relationships,” Jacob Harris, Data Scientist at AcademicBrits and 1Day2Write.

    Proper use of pie charts

    Pie charts are useful for showing how much percentage a variable can make out of a static value, at any given time, but not overtime. As mentioned, they’re useful for showing single part-to-whole relationships. Overall pie charts are very limited and best used for showing approximations, and for the right audience, i.e. an audience not made up of data scientists. The pie-charts are good for showing data in a simple way.

    Usage of gauge charts

    Gauge charts use needles and colors to show data as if it were being measured on a speedometer. They are easy to understand and very good for showing one value at a time, usually side by side with another for a comparison of two variables. Their weakness is that you cannot use them to show trends and they take up a lot of space.

    Proper use of spider charts

    Use a spider chart, when you need to compare data with three or more variables. This means comparing items with several different aspects at once. They are great for rankings, appraisals, and reviews. Don’t use a spider chart if you’re comparing more than five things otherwise they become very hard to read.

    Proper use of spider charts

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    There are many different ways of showing data visually. The types of data visualization that you use depends on what you are trying to show with your data. Knowing what type of chart to use to compare data make your report much more effective and informative for the reader’s perspective.


    Utpal Kar

    Blog Author

    Utpal Kar, a seasoned Corporate Trainer, excels in conducting training programs encompassing Advanced Excel, Power BI, Python, SQL Server, and Unix/Linux technologies. Notably, he holds a Python Certification from LinkedIn, showcasing his proficiency in the domain. Currently serving as a Corporate Trainer at Innovative Technology Solutions, Utpal specializes in Python, VBA Macro, Advance Excel, Power BI, and PostgreSQL, along with a breadth of other languages like .Net and Java. Prior to this role, he made significant contributions at NIIT Ltd., providing technical support and solutions to Franchisee Centres. With over 4 years at Innovative Technology Solutions, Utpal remains dedicated to enhancing skill sets and driving performance for professionals across various industries.

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