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Building Data Visualization in Excel

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05th Sep, 2023
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    Building Data Visualization in Excel

    Excel is frequently used for data analysis because of its superb data visualization features, which enable the creation of illuminating graphics. Each Excel chart has a specific meaning, and excel comes with a significant selection of built-in charts, which may be elegantly used to make the best use of dataData Visualization online courses help you learn more about Data visualization with tools including Excel and gain expertise in the most in-demand skills for a thriving career in the domain. The article provides information about data visualization with excel dashboards and reports and the steps for data visualization with advanced excel.

    What Is Data Visualization in Excel?

    Data visualization is the graphic depiction of data, simplifying the data's understanding. Utilizing Data visualization tools like Data Wrapper, Google Charts, and others, data visualization can be done. A spreadsheet called Excel is also used to visualize data and organize it. Let's learn about Data Visualization in Excel and the various ways to visualize data in excel. 

    Data visualization can be done in various data visualization excel charts & graphs. Data visualization can also be done by data visualization using excel templates. Excel has charts of many kinds, including column charts, bar charts, pie charts, line charts, area charts, scatter charts, surface charts, and many more. 

    Excel data visualization steps: 

    Step 1: Enter the data into the Excel Spreadsheet or choose the data you want to visualize. 

    Step 2: The shortcut for making a chart is simply selecting a cell in the Excel data and clicking the F11 function key. To create a chart, click on the Insert tab and choose the desired chart from the list of available charts. 

    Step 3: The data entered in the excel sheet is used to create a chart.

    Step 4: By choosing the design option, you may customize and decorate your chart with various colors and designs. 

    The Types of Data Visualization in Excel With Examples

    We will illustrate the uses of various charts to grasp Excel's data visualization functionality better. It will acquaint you with the process of creating these Excel representations and using them to extract insights from data. The different types of data visualization examples using excel are: 

    1. Column Diagram

    It is a basic sort of chart that displays data as vertical bars. To create a column chart, choose the data and the necessary choice from the Column chart menu. As we can see, the Column chart has a number of possibilities, and the appropriate one needs to be chosen. You can format the chart as necessary. 

    2. Pie Diagram

    Pie diagrams or charts show how much percentage each category of data contributes. We can quickly understand the percentage contribution thanks to the pie chart. Select the necessary columns, then click the appropriate pie chart choice from the Pie menu to build a pie chart. 

    3. Bar Graph

    The only distinction between this chart type and a column chart is the presence of horizontal bars. Choose the appropriate bar chart from the Bar option to create a horizontal bar.  

    4. Line Diagram

    This graph helps identify trends. To create a line chart, choose the data and the necessary line chart choice. 

    5. Pivot Table

    Pivot Table in data visualization is a tabular view of data that can summarize, sort, and group large amounts of data. 

    Data Visualization Tools in Excel

    Let's check some of the free excel data visualization tools that can be integrated into excel.  

    • Tableau - Without a doubt, Tableau is a market leader. The Tableau team places a strong emphasis on its usability for all users. This indicates that it is extremely user-friendly and designed for a variety of teams. Tableau is unquestionably the most widely used data visualization tool, and Salesforce even purchased it. Tableau is available to everyone, from data scientists to college students, which has helped increase its appeal. 
    • Microsoft BI - The Gartner Magic Quadrant for Analytics and Business Intelligence Platforms has ranked Microsoft Power BI as a leader for the past fourteen years. Like Tableau, Power BI takes pride in having a data-driven culture accessible to all types of users.  

    Power BI's industry-leading AI is among the most valuable features it can provide enterprises. Microsoft offers two significant visualization tools, with Power BI being the most advanced. It offers standard data visualization tool components, including interactive dashboards and APIs for integration, and is fully connected with Microsoft databases like SQL Server and Sharepoint.  

    • DOMO - Fundamentally, Domo is a dashboarding solution that runs in the cloud. They imply by "creates a genuinely digitally connected organization" what they mean by their platform's ability to give knowledge and access to all of your data sources. You can access any sources that do not have a native connection using the API or the Domo Workbench Connector, which enables you to import data into Domo using a CSV file. 

    Data from any area of your business can be viewed using Domo's data visualization software on a single, user-friendly platform. However, Domo connects directly to data where it resides, feeding your critical metrics with real-time data so you can make quicker, more informed decisions. You can use a data visualization add-in in excel as well. 

    Steps for Visualizing Data in Excel

    The steps for creating data visualizations in excel are as follows: 

    The process for creating data visualizations in Excel varies depending on the graph or chart type you select. Generally speaking, the procedure is the same for simple visualizations. Steps may be added if the datasets and graphics are more complicated. 

    1. Starting with a well-structured spreadsheet, create your data visualization Excel Labels, and your completed dataset should be included. 
    2. Following that, draw attention to the information you want to include in your picture, including the labels. The sort of chart or graph you want to make can be selected by clicking "insert" on the main menu. The visualization will instantly display in your spreadsheet after you've made your choice. 
    3. You can change the title, axes labels, and colors by right-clicking the chart or graph. This will reveal a pop-up or sidebar panel with choices to add a legend, change the scale, and modify the font's size and style. 
    4. Enter the data into the Excel Spreadsheet or choose the data you want to visualize. 
    5. The shortcut key for making a chart is simply selecting a cell in the Excel data and clicking the F11 function key. To create a chart, click on the Insert tab and choose the desired chart from the list of available charts. 
    6. The data entered in the excel sheet is used to create a chart. 
    7. By choosing the design option, you may customize and decorate your chart with various colors and designs. 

    How to Create a Heat Map in Excel?

    Use conditional formatting in Excel to quickly create a geographic heat map in excel. Individual values are depicted as colors on a heat map, which is a graphical representation of data. 

    Follow the steps below to create a heat map: 

    • Pick the range 
    • Click Conditional Formatting under the Styles group on the Home tab. 
    • Click a subtype under Color Scales 
    • Select the range 
    • Format Cells can be selected by right-clicking or by pressing CTRL + 1. 
    • Choose the Custom option. 
    • Enter the following number format code: ;;; 
    • Click ok 

    How to Create a Funnel Chart in Excel?

    A funnel chart is the most effective way to monitor your sales. A sales funnel diagram not only outlines the steps in the procedure but also offers a conversion funnel for your brand-new company. 

    Follow the steps below: 

    • Insert a dummy data column first. 
    • Drag the formula shown below down into cell B2's formula bar. 

    =(MAX($I$4:$I$7)-I4)/2 

    • Just choose the data and insert a stacked bar chart to create a sales funnel. 
    • To turn this chart into a sales funnel chart, we need to make the following modifications. 
    • The category should now be changed to reverse order on the vertical axis. Format Axis -Axis Position - Axis Options 
    • After that, select the data bar for the dummy data, and then take away the fill color and border. 
    • Finally, choose data bars and set the gap width to 0%. Data Series → Series Option → Gap Width. 

    You now have a tidy funnel diagram you can use as a model. 

    How to Create a Bubble Chart in Excel?

    Scatter plots include Excel bubble charts. In order to display the values and comparisons, data points are shown in a scatter plot on the chart. To lead the comparison, we've substituted bubbles for those points in bubble charts. Data comparisons are shown on bubble charts' horizontal and vertical axes, just like scatter plots. 

    The steps to make an Excel bubble chart are listed below: 

    1. The first step is to build a dataset and choose the data range. 
    2. The bubble chart must be chosen by going to "Insert" and "Recommended Charts." 
    3. The next step is to format an Excel Bubble Chart using the formatting shown. 
    4. Format X and Y axis 
    5. Format bubble colors 
    6. We now need to add data labels manually. Add data labels by selecting with the right mouse click on bubbles. Select each data label individually, then manually type the region names. 

    Data Visualization Tips in Excel

    1. Choose the Right Type of Visualization

    It's crucial to pick the appropriate kind of chart or graph when creating a data visualization. Think about the kind of data you're using, the scope of the dataset, and your target market. 

    It can damage viewers' comprehension of the information if the data type and the visual being used to display it are incompatible. For instance, how you present the information depends on whether you're using qualitative or quantitative data. 

    How simple or intricate your graphic is should depend on who it is that you are doing it for. For example, it's beneficial to highlight major trends and findings rather than individual data points when presenting to a huge audience or stakeholders. 

    2. Discard Inaccurate Data

    In the end, the quality of your visualization depends entirely on the data you utilize. Because of this, it's crucial to cleanse data after it has been gathered to get rid of any irrelevant or incorrect information. This procedure is also known as data cleansing or data wrangling. 

    Data integrity can suffer if it is not fully cleaned before use, and erroneous or inaccurate data visualizations can result. 

    3. Create the Context for Visualization

    If appropriate, provide a key, a legend, and additional context to aid visitors in understanding your illustration. 

    Take a look at a heatmap, for instance, to see how frequently COVID-19 infections occurred in a certain area over a predetermined time. Viewers must be aware of factors such as the period being analyzed, the data source, and what each hue denotes to comprehend the information displayed clearly. 

    Because it aids viewers in making sense of the information being displayed, this context is crucial. For example, it would be practically impossible to determine what each hue represents without a detailed definition of the coloring system in the heatmap's key, which would be meaningless. 

    4. Portray a Story 

    Last but not least, the secret to creating an engaging visualization is to use the data to convey a story. Your visualization should be evident if the data shows a pattern or backs up a theory. In the end, the goal of visualizations is to convey information in a simple way for viewers to take in and comprehend. 

    In addition to improving the appeal and engagement of your visualization, telling a story can help you make decisions based on facts. Additionally, it aids in comprehending your research's main points by stakeholders, which influences their decision-making.  

    data visualization in excel

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    Conclusion

    Various visualizations can be employed for a given problem. However, the visualization should be chosen before applying Excel to the problem. 

    Before employing visualization, it is important to understand its components thoroughly. Results could be inaccurate if the visualization is not fully understood. You can enroll in the KnowledgeHut Data Visualization courses online to gain expertise in working with various Big Data tools and technologies from experienced instructors and land your dream job. 

    Frequently Asked Questions (FAQs)

    1What is the main objective of data visualization in data?

    Making it simpler to spot patterns, trends, and outliers in huge data sets is the core objective of data visualization. Information graphics, information visualization, and statistical graphics are all terms that are frequently used interchangeably with one another.

    2State the advantages of data visualization.

    Business users can utilize data visualization to understand their massive data sets. They gain by being able to spot fresh patterns and data mistakes. The users can focus on locations that show red flags or progress by making sense of these patterns. This procedure then propels the company forward. 

    3What type of table does Excel use to create data visualization?

    A data table or spreadsheet is an effective structure when analyzing comparative data on classified objects. In most cases, the classified objects are in rows, and the items being compared are in a column. 

    Profile

    Spandita Hati

    Blog Author

    Spandita is a dynamic content writer who holds a master's degree in Forensics but loves to play with words and dabble in digital marketing. Being an avid travel blogger, she values engaging content that attracts, educates and inspires. With extensive experience in SEO tools and technologies, her writing interests are as varied as the articles themselves. In her leisure, she consumes web content and books in equal measure.

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