Let’s say you have a big table full of sales numbers, and you need to turn it into something clear and easy to understand. If you stare at endless rows of data, you can use Excel to create charts and graphs that make the information visually appealing and useful.
This is why data visualization is so important — it helps you see patterns, spot trends, and make smarter decisions. Excel is a go-to tool for this because it’s easy to use and packed with great features for creating charts, graphs, and dashboards.
Why Excel data visualization matters in decision-making and how to visualize data in Excel? We’ll explain step by step how to visually display data in Excel and what other tools you should pay attention to. Improve your data visualization in Excel and turn data into attractive stories!
- Why data visualization in Excel is essential for analysts
- Built-in Excel data visualization tools: The essentials
- Using PivotTables & PivotCharts for interactive dashboards
- Conditional formatting: Visualizing data without charts
- Integrating external data for advanced Excel visualizations
- Data visualization tools for Excel: Beyond built-in features
- Best practices for effective data visualization in Excel
- Conclusion: Unlocking the full potential of Excel for data visualization
Why data visualization in Excel is essential for analysts
Looking at rows and rows of numbers can be exhausting. Data analysis and visualization with Excel makes it easier to spot trends, patterns, and key insights without digging through endless spreadsheets. If you struggle with raw data, you can use charts and graphs to bring numbers to life.
Excel is for sure the most popular tool for data analysis because it’s simple and powerful at the same time. Moreover, it has many customization options. For example, you can change chart titles, adjust the data, and much more. If you really want to delve deeper into the subject, you can sign up for a comprehensive course on charts and dashboards.
Relying only on tables can slow you down and make reports harder to understand. Using Excel visualizations helps make data clearer and more engaging for teams, clients, and decision-makers. Visualize data in Excel to not only simplify complex information but also improve communication and make it easier to act on important insights.
Built-in Excel data visualization tools: The essentials
Excel has everything you need to turn plain numbers into clear, easy-to-read charts. Whether you’re making a simple bar graph or a detailed financial report, Excel helps you spot trends and patterns without the headache. With just a few clicks, your raw data becomes something useful.
You can also tweak your charts however you like — change colors, add labels, or adjust the layout to make them look just right. Whether it’s a quick report or a full dashboard, Excel gives you the tools to make your data stand out.
How to create basic charts in Excel
How to visualize data in Excel? Making a chart in Excel is super simple. Follow these steps to create bar charts, line graphs, and pie charts.
Bar charts: great for comparing numbers
- Select your data written in the Excel table.
- Click on the Insert tab.
- Choose Column or Bar Chart and select a style (e.g., Clustered Column).
- The chart will appear with your data.
When to use Bar Charts
Bar charts are ideal for illustrating how data is distributed across categories and highlighting differences between them. They work well for comparing integers or percentages, especially when the data is grouped into distinct categories.
When to avoid Bar Charts
Despite their popularity, bar charts aren’t always the best choice. Avoid using them for summarizing continuous data, analyzing long time series, or identifying correlations—other visualization types are better suited for these tasks.
Line graphs: help you see trends over time
- Select your data written in the Excel table.
- Go to the Insert tab.
- Choose Line Chart and pick a 2D or 3D style.
- The line graph will display trends over time.
When to use Line Charts
Line charts are great for visualizing trends within a dataset, showing overall patterns, or comparing multiple trends simultaneously. They are especially useful for making forecasts based on historical data.
When to avoid Line Charts
If your dataset contains only a few values over a short time span, a bar chart may be a better choice. Additionally, if the data consists of discrete values with no logical progression between points, it’s best to use a chart type that doesn’t rely on continuous connections.
Pie charts: show how different pieces make up a whole
- Select your data written in the Excel table.
- Click Insert and choose Pie or Doughnut Chart.
- Pick a 2D or 3D pie chart style.
- The pie chart will show proportions visually.
Once your chart is ready, you can make it look even better. Excel data visualization examples prove that changes in the colors, labels, and style adjustments let your charts look clearer and more professional instantly. A few simple tweaks can turn a basic chart into a powerful way to share your insights!
When to use Pie Charts
Pie charts illustrate part-to-whole relationships. Since these charts rely on color coding, they can display multiple proportions simultaneously, making them useful for emphasizing overall distribution rather than precise differences.
When to avoid Pie Charts
Pie Charts are not fit for pinpointing exact values or making direct comparisons.
Advanced chart types for data analysts
For more detailed analysis, Excel has some advanced chart options and data visualization techniques in Excel.
Scatter plots and bubble charts help you see relationships between different factors, making them perfect for spotting trends or correlations.
Scatter Chart (X, Y Plot)
- Select your dataset with two numerical columns.
- Click the Insert tab and choose Scatter (X, Y) Chart under the Charts group.
- Pick a Standard Scatter Chart to see individual data points.
- Your chart will now display relationships between the two variables.
Bubble Chart
A Bubble Chart is a variation of a scatter chart where the size of each data point (bubble).
- Follow Steps 1 & 2 from the Scatter Chart to create a Bubble Chart.
- Choose the Bubble Chart option.
- The third variable determines the size of each bubble.
- Your chart will now display three data dimensions.
Histograms
Histograms and box plots show how data is spread out, which is helpful for understanding distributions and patterns.
- Select your numerical data.
- Click Insert and choose Statistic Chart > Histogram.
- Excel automatically groups data into bins; you can adjust the bin size by right-clicking the X-axis and selecting Format Axis.
- The histogram will display data distribution.
Box Chart
- Select your dataset with numerical values.
- Click Insert > Statistic Chart > Box & Whisker.
- The chart will display quartiles (box), median (line inside the box), and outliers (dots).
If you’re dealing with financial data, waterfall charts are the best way to visualize data in Excel. They show how different amounts add up to a total, helping you break down things like profits, expenses, or changes in your budget.
- Select your dataset with starting values, increments, and final values.
- Click Insert and select Waterfall Chart.
- You’ll see a column-based visualization of positive and negative contributions. The chart will show how values increase or decrease over time.
These advanced charts give you a clearer picture of more complicated data.
Using PivotTables & PivotCharts for interactive dashboards
Data visualization in Excel for interactive dashboards works great with pivot options. A pivot table structures data in tabular form with minimal effort, summarizes it, and enables its analysis.
Step 1. Set up your data
Step 2. Create a PivotTable
- Select your data, go to Insert > PivotTable.
- Choose New Worksheet and click OK.
- Drag fields into Rows, Columns, and Values to organize your data.
Step 3. Add a PivotChart
- Click inside your PivotTable.
- Go to Insert > PivotChart, pick a chart type, and click OK.
Step 4. Add slicers
- Click the PivotTable, go to Insert > Slicer.
- Select fields you want to filter and place them on your dashboard.
Step 5. Format charts for a clean look and move everything onto one sheet for easy viewing.
Pivot tables and pivot charts are those Excel data visualization tools that eliminate the need to create complex links or formulas within tables. Changes in a pivot table do not update the original data. Thus, visualize data in Excel with pivot tables to achieve data consistency.
The use of pivot tables is always useful when a data source (e.g., a large table with a lot of data) needs to be analyzed and not all columns (fields) are needed.
Example: Building a sales performance dashboard
Think of a real example on how to visualize Excel data? You can create a sales performance dashboard using PivotTables and PivotCharts to track things like revenue, top-selling products, and regional sales. Start by creating a PivotTable to organize sales by category, region, or salesperson. (See the steps above if you need a refresher.) Then, add a PivotChart to show trends visually.
Want to make your dashboard easier to use? Add slicers and filters! As we’ve mentioned before, these tools let you focus on specific fields, like time periods, products, or customer segments with just a click. Don’t stare at a massive spreadsheet, just quickly narrow down the data you need.
Conditional formatting: Visualizing data without charts
Data visualization with Excel offers Conditional Formatting. This feature helps you highlight important patterns without using charts. It automatically changes the look of cells based on their values. This makes it easier to spot trends, outliers, and key insights, especially when you’re working with large sets of data.
Data visualization using Excel shouldn’t be boring. Instead of scrolling through rows of numbers, you can use colors, bars, or icons to make important data pop. For example, you could set high values to show in green, low values in red, and medium values in yellow. These visual cues help you quickly focus on what matters most. How to use them?
- Highlight important numbers, e.g., color cells that are too high, too low, or meet a rule.
- Add mini bars or color scales to compare values easily.
- Add icons, like arrows, checkmarks, or flags, to show trends fast.
- Set custom conditions to format data your way.
Best practices: When to use color scales, data bars, and icon sets
Each type of Conditional Formatting is helpful for different tasks in data visualization techniques in Excel. Color scales are great for showing ranges, like temperature or sales trends over time. Data bars give a quick visual comparison of numbers, making it easy to see which values are high or low just by glancing.
Icon sets are useful for visually categorizing data. For example, you could use arrows to show trends or symbols to mark important items. These tools make your data clearer, more engaging, and easier to interpret. When used correctly, they help ensure your data is easy to understand at a glance.
Integrating external data for advanced Excel visualizations
Think of visualizing data in Excel like a supercharged notebook. Normally, you type in numbers and update them yourself, which can be a hassle. But if you connect Excel to outside sources (like a database, a website, or an online service), it can pull in fresh data by automating it.
Your charts and reports update themselves — no extra work needed! With data visualization in Excel, you can keep an eye on things like sales, stock prices, or customer trends as they change in real time. Plus, you can pull in data from different sources and see everything in one place, making it easier to spot patterns and make smart decisions.
Methods to import data from SQL, APIs, and cloud databases
Excel offers easy ways to import external data. For example, you can use Power Query to pull data from SQL databases, which stores and organizes your data for easy analysis.
If you want up-to-the-minute data, you can link Excel to online sources like stock market updates or customer databases. This way, the latest info flows in automatically instead of you typing it in manually.
For really big data, cloud tools like Google BigQuery or Azure keep things running smoothly without slowing Excel down. Once your data is in, you can use PivotTables, charts, and other tools to make sense of it. And if you set up automatic updates, your reports will always stay fresh without you having to do a thing.
Use case: Combining multiple data sources into one Excel dashboard
Excel data visualization tools are a good-fit for many niches. Let’s say you need to track sales from different regions. With Excel, you can pull customer data from your CRM system, sales figures from a SQL database, and marketing data from a Google Analytics API — and bring it all together in one dashboard.
In data analysis and visualization with Excel and Power Query and PivotTables, you can clean, organize, and visualize all your data in one place. You can also add buttons and filters to let people easily sort through the data and focus on what matters most. This makes it simple to break things down (like seeing sales by region or customer type) without messing with tables.
Data visualization tools for Excel: Beyond built-in features
Excel’s built-in charts are really great, and many analysts use them only. But if you want to take your data visuals even further, you can use extra tools. You can connect to real-time data, automate your analysis, and create more advanced reports as a professional visualizer. Just by adding these external plugins and software, you get a Marvel superhero called Excel whose superpowers are data analysis and visualization.
We offer you to check out some powerful tools you can add to Excel. They include Devart’s ODBC Driver, Power Query, Power Pivot, Power BI, and a few free add-ins.
Excel data visualization with Devart’s ODBC driver
The Excel ODBC Driver connects to databases like SQL, MySQL, PostgreSQL, and cloud storage. You don’t need to manually copy and paste data because Excel pulls in live updates automatically. This way, your charts and dashboards always show the latest info without extra work.
It’s especially useful for analysts dealing with big datasets from multiple sources. No more constant updates — just real-time data whenever you need it. You can try out the Devart ODBC Driver with a free trial to see how it works.
Microsoft Power Query & Power Pivot
Power Query helps you bring in data from different places, clean it up, and get it ready for analysis — all without writing a single line of code. This is quite handy for handling large amounts of information without hassle.
Power Pivot does complex calculations and creates custom formulas. It can handle millions of data rows and helps you build interactive dashboards. Together, Power Query and Power Pivot manage and analyze big data and turn Excel into a tool that competes with full business intelligence software.
Power BI integration with Excel
Power BI takes your Excel data visuals to the next level by offering interactive dashboards and real-time analytics. You can create detailed reports in Power BI and connect them directly to your Excel data. This gives you the ability to tell a clearer story with your data and get more comprehensive insights.
The easiest way to connect Power BI to Excel is by using the Power BI Publisher add-in. It allows you to share your Excel reports within Power BI and keeps your data connected in different platforms. Know businesses that need interactive and shareable dashboards that update in real time? It’s a great option for them!
Free add-ins for data visualization
What is the best way to visualize data in Excel? There are free add-ins that can improve Excel’s data visualization. For example:
- People Graph: Turns raw data into infographics.
- Bing Maps: Makes interactive maps from geographical data.
- ChartExpo: Creates advanced charts that Excel doesn’t support natively.
- Colorizer: Applies consistent color schemes to charts and tables.
- Zebra BI: Adds intuitive AI visuals to financial reporting.
These free data visualization tools for Excel help create better charts, dashboards, and reports with minimal effort.
Best practices for effective data visualization in Excel
Want your Excel charts to actually make sense? Here’s how to keep them clear and useful.
- Pick the Right Chart Type: Bar charts are great for comparisons, line graphs are best for trends over time, and pie charts help show proportions.
- Keep It Simple and Avoid clutter: Too many labels, gridlines, or colors make it hard to focus on what matters. Stick to the key insights and skip the extra noise.
- Stay Consistent: Don’t mix too many colors or chart styles because it can be distracting. Use a simple color scheme and the same fonts if you want everything to look clean and professional.
- Use Live Data: If your numbers change often, connect Excel to an external source. This way, your charts update automatically, and you don’t have to worry about outdated info.
These small changes can make a big difference. They will make your Excel data visualizations more attractive and reliable.
Conclusion: Unlocking the Full Potential of Excel for Data Visualization
Excel is really powerful, as you can see. However, you can make it even cooler with the right tools. Excel’s built-in features, advanced tools like Power Query and Power Pivot, and external integrations like Power BI and Devart’s ODBC Driver will bring your data analysis to the next level.
Experiment with different visualization techniques. Try using PivotCharts, interactive dashboards, etc. to find what works best for your data. The more you practice, the better your visual storytelling will become.
For even more advanced data visualization, think about Devart’s ODBC Driver. It integrates real-time data into Excel, saves your time and eliminates manual updates. It’s a miracle, isn’t it? Download the free trial today to make your Excel dashboards even better!
FAQ
What is Excel data visualization, and why is it important for data analysis?
Excel data visualization refers to the use of charts, graphs, and other visual tools to represent data in a clear and insightful way. It helps identify trends, patterns, and correlations, making data-driven decisions more effective.
How to visualize data in Excel using built-in charts and graphs?
Excel provides various built-in chart types, including bar charts, pie charts, scatter plots, and pivot charts. You can create visualizations by selecting your data, navigating to the Insert tab, and choosing a suitable chart type. Advanced options like conditional formatting and sparklines can enhance the clarity of data representation.
What are the best ways to visualize data in Excel for reports and dashboards?
To create impactful reports and dashboards, it’s crucial to choose the right type of visualization for the data at hand. PivotCharts and PivotTables are excellent for summarizing large datasets dynamically, while conditional formatting can help highlight important trends directly in data tables. Combining multiple chart types, such as bar and line charts, is useful for comparing different data series. Additionally, tools like slicers and timelines can add interactivity, allowing users to filter and adjust the data being presented.
What are some Excel data visualization examples for business and financial analysis?
In business and financial analysis, Excel data visualizations can take many forms. For example, sales performance dashboards can visually represent revenue trends, helping to identify the highest-performing products or regions. Financial statement visualizations might display income and expense trends, while customer segmentation analysis helps categorize customers by various criteria. Inventory tracking visuals can show stock levels and trends, making it easier to manage supply chains.
Which Excel data visualization tools are best for creating interactive dashboards?
Excel offers powerful tools for building interactive dashboards, such as the integration of Power BI for more advanced visualizations. Power Query and Power Pivot can be used to manage and analyze large datasets, while slicers and timelines help users interact with and filter data within dashboards. These features make it easy to create dynamic reports that update automatically based on changing data.
How do I visualize data in Excel using real-time SQL database connections?
To visualize data in Excel using real-time SQL database connections, you can link Excel to an external database through an ODBC driver. This allows you to import live data directly into your spreadsheets, ensuring your charts and reports are always up-to-date. Tools like Devart’s ODBC Driver make it possible to connect Excel with various databases such as MySQL, PostgreSQL, and SQL Server, allowing you to pull the latest data directly into your visualizations.
Does Devart’s ODBC Driver support automating Excel data visualization workflows?
Devart’s ODBC Driver supports the automation of Excel data visualization workflows by establishing real-time connections between Excel and SQL databases. This enables automatic updates of data without manual intervention, ensuring that your visualizations remain current.
Can I create dashboards in Excel using data from MySQL, PostgreSQL, or SQL Server with Devart’s ODBC Driver?
Yes, Devart’s ODBC Driver allows you to create dashboards in Excel using live data from databases like MySQL, PostgreSQL, and SQL Server. This direct integration ensures that your dashboards are always up-to-date, reflecting real-time changes in the data.
