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65% of people are visual learners, making data visualization an effective way to communicate information.
Data visualization helps to clarify and communicate complex information, turning vast amounts of data into understandable stories.
When Excel spreadsheets aren’t enough to connect the dots between your data and there’s no possibility to involve data or digital analyst to get the report quickly, data visualization software and other tools and tools is what you need to become data-savvy.
In this article, which was last updated in March 2025, we’ll show you what data visualization techniques are available, how to visualize data correctly, which tools can be used for engaging and interactive visualizations without any help from developers or data professionals, and how to choose a tool that suits your specific needs.
The definition of data visualization is the visual representation of your data. With the help of charts, maps, and other graphical elements, these data visualizations provide a simple and comprehensible way to clearly see and easily discover insights and patterns in your data.
Data visualization is the graphical representation of data using visual elements such as charts, graphs, and maps.
It is a way to communicate complex information in a visual and intuitive manner, making it easier for people to understand and analyze the data. By transforming raw data into visual representations, data visualization allows patterns, trends, and insights to be easily identified and interpreted.
Data visualization is also a powerful storytelling tool. Visual data storytelling helps to uncover hidden patterns, relationships, and correlations that may not be apparent, or not visible in raw data. Through visualizations, data can be presented in a way that is engaging, impactful, and memorable, enabling effective communication and data-driven decision-making.
If you want your Facebook post to be read by as many people as possible, what will you do? You’ll add an interesting visual. This trick works perfectly with reports too. Data Visualization attracts more attention, is easier to understand, and assists in getting your message across to the audience quickly.
With the help of descriptive graphics and dashboards, even difficult information can be clear and comprehensible. Data analytics supports business intelligence through automatic dashboards and performance monitoring, making it easier to track and analyze key performance indicators.
Why is that?
Here are some noteworthy numbers, based on research, that confirm the importance of visualization:
Relevant visualization brings lots of advantages for your business:
There are multiple data visualization methods that can be utilized to present data effectively, ranging from charts and graphs to more complex scientific visualization techniques.
The first thing to do before creating any data visualization chart is to check all information for accuracy and consistency.
For example, if the scaling factor is 800%, whereas the average is 120–130%, you should check where this number is coming from. Maybe it’s some kind of an outlier that you need to delete from the graph so it doesn’t skew the overall picture: 800% downplays the difference between 120% and 130%. This kind of outlying data in a report can lead to incorrect decisions made.
To increase the chances of success in marketing, the right message should be delivered to the right person at the right time.
The same three rules are applied for data visualization:
Data visualization is a crucial component of any business intelligence system, as it transforms complex data into actionable insights. By presenting data in a clear and concise manner, data visualization enables businesses to:
Data visualization plays a crucial role in simplifying complex information, enabling faster decision-making and clearer insights. By representing data in a structured visual format, businesses, analysts, business professionals, and researchers can quickly identify patterns, correlations, and anomalies that might not be apparent in raw datasets.
A well-designed data visualization dashboard makes it easier to communicate findings to stakeholders who may not have technical expertise. For example, a trend in sales performance over time is more intuitive when shown through a line chart rather than a spreadsheet of numbers. Similarly, a heat map can highlight areas of high customer activity without requiring extensive data interpretation. Pie charts are also popular examples for representing parts of a whole within larger datasets, simplifying complex information for better comprehension by audiences.
Beyond improving clarity, data visualization enhances engagement and storytelling. Interactive visualizations, in particular, allow users to manipulate data in real time to create visuals, uncovering deeper insights through filters, hover effects, and zoom features. These dynamic representations are especially useful for dashboards, reports, and presentations where audiences need to explore multiple facets of the data.
Data visualizations have a wide range of applications across various industries, each leveraging visual analytics tools to gain insights and drive decisions.
Here are some examples of how data visualizations are applied in different sectors:
The second important thing that you have to take into account while working with visualization is choosing the right message for the audience. The information you talk about, the story you tell in the visual context of the report should be clear and informative for your readers.
Here’s a chart that was awarded the prestigious Data Journalism Award.
For people who aren’t familiar with the background to the story, this chart looks like a picture made by a three-year-old. However, when you find out a little bit more about it, you can see the huge amount of work done by its authors.
Charles Seife and Peter Aldhous, Buzzfeed News editors, used the R language to visualize flight data obtained by FBI and DHS agents as part of air surveillance. Specifically, this chart shows flights above the house and mosque of those responsible for the mass shooting in December 2015 in San Bernardino, California.
While choosing the parameters you want to visualize on one chart, you have to confirm that they can be combined. Some combinations just aren’t logical, though at first sight the information correlates perfectly. Here’s an example of such a chart with a faulty correlation. It shows that the number of people who drowned by falling into a pool correlates with the number of Nicolas Cage films.
The next things you should take into account when creating a chart are the scale and scope. People are used to the fact that measurements on axes start from the bottom and from the left. If you change the direction of measurement, it will confuse an inattentive audience. Although we should mention that reversing the measurement is possible when used as a tactical maneuver, as in this example:
At first sight, it may seem that the number of murders committed using firearms has been decreasing over the years. In fact, it’s the opposite, as the scale starts from the top. Perhaps the author of the chart did this on purpose to decrease the negative response to the results shown.
A suitable scale also makes your chart clearer. If a report shows data points that are too close and you can’t see any movement, try to change the scale. Start the measurements not from zero or divide the scale into smaller parts and the picture will clear up.
Alt text: Side-by-side bar charts representing interest rates over time, with different y-axis scales affecting data interpretation.
Before giving a report to the stakeholder, make sure that the chart loads fast. Slow loading kills all your efforts.
Remember, the golden rule when you’re crafting your chart design is to keep it simple.
When you’re tasked with putting together a standard report, don’t fret about making it look fancy. You don’t need to dress it up.
Avoid any extra elements that only clutter the chart: too many colors and structures, 3D volume, shadows, gradients, etc.
A bar chart is a fundamental method for visualizing data, allowing for easy comparison of multiple data factors and illustrating changes in data values over time.
The simpler a chart is - the easier it is for the readers to understand the information you want to share.
Don’t make your visualizations too small, and don’t put all charts on the same dashboard page. It’s considered bad style to use more than three types of charts on one slide or the same dashboard page. If you really need so many chart types, put them on different pages, or make a clear separation, so it’s easy to understand them.
Don’t be afraid to experiment. If you have a task that’s not typical, perhaps your solution should also be non-standard. In the infographic below, we can see the wing movement patterns of different animals. The dynamic visualization is totally relevant.
Let’s have a look at some data visualization tools examples and discuss how to choose the right one for your goals.
Nowadays, there are lots of data visualization tools and reporting tools on the market. Some of them are paid, others are for free. Some of them work fully on the web, others can be installed on a desktop but work online, and others are offline only.
We’ve crafted a list of 10 most popular reporting and data visualization software:
There are various data visualization methods available, and these tools offer different ways to present data effectively, including traditional methods like pie charts.
First six tools and services are created by companies specializing in visualization.
Numbers seven through ten are quite interesting tools, mostly free and online. They offer non-standard types of big data visualization tools and may offer new ways of approaching your business information.
What to look for when choosing a reporting tool:
For example, R Studio is a great service, especially for searching for trends and building attribution and correlation models. But if you are not familiar with coding, you won’t be able to connect any specific libraries, and it would be difficult for you to start working with R Studio.
Dynamic reports refer to the possibility to import data from different sources in real time.
For example, Looker Studio (formerly Google Data Studio) doesn’t have dynamic reports in place. Let’s say we’ve connected a Looker Studio request from Google BigQuery and then changed something in this request. To record these changes in the report, we need to at least refresh the page.
However, if we add or delete some fields in Google BigQuery (not just change the logic of the calculation but change the table structure), then Looker Studio would show an error. You’ll have to rebuild the dashboard to get the visualizations in place.
OWOX BI is a comprehensive analytics platform that covers everything from data collection and streaming to attribution modeling and reporting. With OWOX BI, companies get a complete view of their marketing activities across various channels, empowering advertising specialists to optimize their ad spending and achieve better ROI through effective data visualizations.
OWOX BI Pipelines facilitates seamless data collection from various advertising platforms, CRMs, and website builders, enabling organizations to consolidate all their data in one place in order to have a data source of truth and gain better insights. This data collection is a crucial part of the larger field of analytics, which helps organizations track and analyze key performance indicators to derive actionable insights.
OWOX BI Streaming is a cookieless real-time user behavior tracking system, ensuring privacy compliance with regulation and extending the lifespan of cookies. Marketers can accurately track the entire conversion journey, find the true sources of conversions, and gain a deeper understanding of customer behavior.
OWOX BI Transformation saves time on data preparation (avg. of 70 hours per month). With pre-built low- or no-code transformation templates (based on 100’s delivered projects across multiple industries), businesses can quickly produce trusted datasets for reporting, modeling, and operational workflows:
Lastly, OWOX BI integrates with visualization tools like Looker Studio, Tableau, or Power BI, enhancing data-driven decision-making by building customizable reports & keeping the data always up-to-date.
Note: For enterprise customers, OWOX BI expert team will set up a data model tailored to your business. You’ll be able to evaluate the impact of all marketing efforts — both online and offline.
User actions on your site:
There are multiple data visualization methods that can be utilized to present this data effectively, including charts, graphs, and other approaches.
Looker Studio, also known as data studio allows you to connect data sources, easily build charts, reports and add elements to visualize and share reports with colleagues in a way that’s similar to other Google products. It excels in creating data visualizations that simplify data for better understanding and interpretation.
Looker Studio supports a wide range of visualization methods, making it versatile for various data presentation needs.
Advantages:
By the way, if you want to see any Facebook or Yahoo Gemini statistics in reports built in Looker Studio, you can import ad cost data into Google BigQuery with OWOX BI. While you may lose some of the important data with other data connectors, with our Facebook Ads to Google BigQuery pipeline you receive complete data ready for analysis and reporting from your Facebook account.
This is one of the two most popular data reporting tools (together with Microsoft Excel) that’s used by any marketing specialist at least once. The Google Sheets interface is quite simple and easy-to-use, especially for those who just starting analytics out.
Advantages:
The charts and reports types in Google Sheets are the same as that is in Looker Studio, making it a powerful tool for creating data visualizations.
Conditional formatting in Google Sheets allows users to apply formatting rules to cells based on specific conditions.
These conditions can be based on the cell’s value, text, or even a formula. By using conditional formatting, users can visually highlight important data, identify trends, and make their spreadsheets more visually appealing and easier to understand. Data visualizations help to clarify and communicate complex information, making it easier to reveal trends and convey messages effectively.
Pivots allow users to summarize and analyze significant amounts of data. They are used to transform raw flat table data or data sets into insights by organizing numerical data and summarizing it in an easy and structured relatively small table. In the context of data analytics, pivot tables play a crucial role in helping users analyze and visualize data effectively.
With Pivot tables you can quickly explore data from different perspectives, change columns and rows, sort values, identify patterns, and uncover trends or anomalies. They are particularly useful for data aggregation tasks. Pivot tables allow you to group and aggregate data based on different criteria, such as product, sales date, or any other relevant attribute. Additionally, pivot tables can be a powerful tool for creating interactive data visualizations that simplify complex data and enhance understanding.
VLOOKUP is a function in Google Sheets that stands for vertical lookup. It is used to search for a specific value in the leftmost column of a range of cells, and then return a corresponding value from a different column in the same row. Vlookup is commonly used to find and retrieve a hierarchical data, from large datasets or tables.
Imagine having a list of products and their corresponding prices. You can use VLOOKUP to search for a specific product name in the leftmost column, and then retrieve the price of that product from a different column in the same row. This can be useful for tasks such as pricing analysis and creating data visualizations.
If you want to get data from BigQuery to visualized in Google Sheets, there is a Google sheets extension that allows you to query data directly from Google BigQuery and build reports based on the imported data.
There are multiple data visualization methods that can be utilized to present the data effectively, ranging from charts and graphs to more complex visual representations.
Basically, you can request any data stored in your Google BigQuery project directly from the Sheets interface, making it easier to create insightful data visualizations.
Last but not least, we wanted to share with you one of our favorite reports for Google Sheets — the cohort analysis report.
Cohort analysis is a powerful analytical technique used to understand the behavior and common details of a specific group of individuals over time. Data visualization helps to clarify and communicate complex information, making it easier to understand customer behavior through cohort analysis.
It involves dividing a larger audience into smaller groups, or cohorts, based on a common characteristic or event. These cohorts are then analyzed to identify patterns and trends that can help businesses make informed decisions and improve their strategies.
The most common case of cohort analysis in marketing is to track the behavior of customers who made their first purchase in a particular month. By analyzing data from this cohort, businesses can determine the retention rate, average purchase value, and lifetime value of these customers. This information can be valuable in identifying the most effective marketing channels, optimizing customer acquisition strategies, and improving customer loyalty.
Additionally, you can read our detailed guide to cohort analysis in Google Analytics 4 and Google Sheets, where we provide very detailed instructions. We’ve also hosted a webinar on cohort analysis.
There are many resources available to learn data visualization, including online courses, tutorials, and books.
By leveraging these resources, you can continuously improve your data visualization skills and stay ahead in the ever-evolving field of data analytics.
Data visualizations can help you make your reports visually appealing and comprehensive, allowing you to highlight valuable insights in your data easily.
If you want to keep up with the pace of modern business, adding visual storytelling and data exploration to your reports will allow you to accelerate the process of decision-making.
If you still don’t know which of all data visualization tools would fit your business needs, book a free demo to discuss your specific situation with our data experts and discover the ideal solution designed for you.
