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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.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 :Column charts can show comparisons of different items or a comparison of items over time.A mekko chart not only compares values but also measures their composition and demonstrates how data is distributed across each value.Bar graphs are useful because they prevent clutter when you have a very long data label or a lot of values to compare. 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.Scatter plot charts, show the relationship between two different variables and are useful for determining your data’s distribution.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 chartsLine 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 graphsIf 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 chartsYou 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 chartsPie 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 chartsGauge 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 chartsUse 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.ConclusionThere 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.
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Choosing the Right Visualization Type for a Project Report

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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.

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

Conclusion

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.

Sherie

Sherie Raymond

Professional writer

Sherie Raymond is a project manager at Origin Writings. She regularly writes articles for online business and marketing magazines and blogs, and practices yoga in her free time.

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Google Charts have been coded with  HTML5 and SVG and aims at total cross-border compatibility along with Android, iOS including older Internet Explorer versions supported via VML. All the charts created are interactive with an additional feature of zoom. They are very user-friendly accompanied by their site features - a really appreciative comprehensive gallery where we can see the data visualizations and interactions at our disposal.Pros:Very easy data integration.Data graphs are visually appealing.Can be incorporated into a variety of websites.Compatibility with other Google products.Cons:At times the look and feel of the graphs are way too modern.Feature of exporting the chart should be more straightforward.Lack of demos on advanced tools.Lack of customization ability.They require network connectivity for data visualization.Not feasible with a mobile application.Cost: Free trial available,Open-Source/Licensed: Licensed. 13. Zoho Reports:Zoho reports are very well known as Zoho Analytics. They have an online reporting and business intelligence service that helps get the new insights on the users’ data. It helps in creating and sharing powerful, ad hoc reports within minutes, without any IT help. Data of users can be easily imported from applications and databases, even behind firewalls.Pros:With little extra effort, new reports can be created. Basis the need, existing report can be easily modified. Features like report sharing, scheduling of emails are extremely useful features.In the case of a bigger database, space is not the concern.Quick and prompt level-1 customer support.Cons:Report sharing becomes cumbersome with larger groups of dataTraining for new Zoho Reports' users should be potentially more effective.At times the main dashboard becomes more confusing with a larger number of data.Cost: $25  USD/user/month billed annually (For professional version).Open-Source/Licensed: Licensed. 14. JupyteR:It is basically a web application that supports the open-source. The major highlight is creating and sharing documents which have a live code,  narrative text, equations, and visualization. JupyteR stands for IPython (Interactive Python). In multiple programming languages, it is used for interactive computing. Also, it was originally developed for the Python programming language. It is serving Uses include: data transformation along with cleaning, simulation of numerical, modeling of statistics, data visualization, machine learning, and many more.Pros:Prototyping can be concluded quickly and easily.The end result of the application is visually interesting.Insight of the data can be easily shared.Cons:Tricky collaboration.At times reviewing of codes becomes difficult.More often there comes the challenge of complexity during production.Open-Source/Licensed: 100% Open source and free for all users.15. Dundas BI:Dundas BI comes with highly-customizable visualizations along with interactive charts, gauges, maps, scorecards and many more. In addition to that, there is also granular control over almost all visual design elements. Dundas BI also align them to the enterprise reporting needs in a dedicated reports designer. There is lots of flexibility while creating multi-page reports or ad-hoc reports. In short form, the complex views are available in simplified form for the user.Pros:Lots of Flexibility in the functionality.Anything imagined can be possible through the licensed version.Variety of charts and data sources are available along with flexibility in design.N numbers of built-in options for extracting, modifying and displaying data are available.Cons:Predictive analytics is missing.Too massive to fully exploit the capabilities of a software developer.3D Charts are not supported in this application.Non-essential upgrades need to be removed.Cost: $99 USD/user/month billed annually (For professional version).Open-Source/Licensed: One-time license.16. Visme:Visme has transformed the way of creating & sharing very engaging Presentations along with Infographics and other visual formats. The content creation tool is the most popular tool being used by IBM, General Dynamics, and Accenture and 1.7 million other users. The stories and the boring data’s are being translated into engaging Visuals. The visually available product can be either published online or embed to any site and can be download for offline use.Pros:Customer user-friendly dashboard making the designs of collateral extremely easy and within a short span of time.Templates and individual graphics, stats, objects are adaptable easily. They are immensely helpful in providing ideas for formatting and structuring the graphic.Visme sets a benchmark in itself by providing templates for presentation slides.Cons:At times it becomes difficult to select particular sections when there are many layers in a particular image.Not much effect on the social templatesOften it acts a little funky when on clicking the image.Cost: $70 USD/user/month billed annually (For professional version).Open-Source/Licensed: Licensed. 17. Grafana:Bafana is commonly used for the purpose of dashboard and graph composing. It focuses on providing ample ways to visualize time series metrics, mainly though graphs. They even support ways to visualize data through a pluggable panel architecture. At present,   rich support for Graphite, InfluxDB, and OpenTSDB and even supports other data sources via plugins.In a layman language, it is a tool in the Monitoring category of a tech-savvy user. They can create, edit, search and save the dashboards.Pros:Possibility of templating.Feature of importing and exporting the dashboard available.Rearranging the panel with drag and drop feature.Column span and row heights can be modified.Can be easily deployed.Cons:Dashboard URL keeps on changing.Irregularities in case of notifications.Data storage is a cause of concern hence used with Graphite.Open-Source/Licensed: Open-source.There are other tools as well. Please find below some other alternatives we have on data visualizations:18. ChartBlocks:It offers an online charting service. We need to upload our data then we can easily create interactive charts based on uploaded data.19. NVD3: It is a dynamic collection of components, with the aim of keeping these components very customizable. The highlight of the project is its attempt to build reusable charts. 20. Leaflet:It is basically designed keeping in mind the simplicity, performance, and usability. Leaflet is defined as mobile-friendly interactive maps leading the market with open-source JavaScript.21. N3-charts: They are generally used for creating beautiful charts in Angular JS application with the use of JavaScript library.With so many options available, it becomes difficult sometimes to choose the right visualization tool for organization. The organization needs to carefully select the tool which can fulfill their requirement.  The tool should be able to extract data from different platforms stored in different formats. The enterprise structure also helps in deciding the best data visualization tools.
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