Data visualization is the process of making data easier to understand and interpret. It can be used in many ways, such as for reporting, interactive dashboards, presentations, and more. The purpose of data visualization is to help people from a variety of professions understand the information they are looking at so that they can make better decisions based on it.
The purpose of data visualization
Data visualization is a powerful tool that can help you tell your story, find patterns and trends, communicate effectively with others and make decisions. Data visualization is also used to understand complex data sets by breaking them down into smaller pieces so they can be analyzed in a more meaningful way.
Data visualization is an important part of any data analytics project because it helps you visualize the results of the analysis so they are easier to understand.
Types of data visualization techniques
- Charts: Using charts to visualize data is the most common way to show your data. Charts are a visual representation of a set of discrete values in a grid or table form, and they help you quickly understand how each category compares with others.
- Graphs: Graphs are used by presenting two sets of values on either side of a line (or curve). The distance between them is called the “slope” and represents how different topics relate to each other. A graph can be used as an effective way to communicate complex relationships that would be difficult for readers to understand from tables alone.
- Tables: Tables use rows and columns containing numerical data; there’s no need for any additional information about what type of information goes where! You’ll find this useful when your audience has certain questions about their statuses—for example, if you’re working on something related directly to health issues like cancer treatment costs or mental illness statistics across various ages groups who would benefit most from these services being available at affordable prices within reach so everyone could afford them without having too much stress over finding ways around budget constraints preventing people being able to go ahead buy themselves one such item immediately after diagnosis happens all while still keeping hope alive until tomorrow morning comes along
Data Visualization Examples
There are many ways to display data. Data visualization techniques can be used in conjunction with any analytical technique, or on their own. Some examples of data visualization techniques include:
Bar charts
A bar chart is one way to represent the values of different variables by showing them as vertical bars in a graph. For example, if you wanted to show how many people had been vaccinated against chickenpox this year compared with last year (in 2007), you could create a bar graph showing these two numbers next to each other and then colour-code them based on whether they are above or below zero (i.e., vaccination rate).
Line graphs
Line graphs show trends over time by connecting consecutive points on an axis (vertical axis) with straight lines that go from left to right across each point until it reaches its end point at infinity on the horizontal axis (horizontal axis). For example, instead of just displaying how many people were vaccinated against chickenpox last year versus how many were vaccinated this year—which would result in two separate lines—you could also draw an imaginary line through both points so your reader knows where those two lines intersected during each period when there was no change between years’ vaccination rates; then colour code either side based upon whether their rate went up/down between 2009-2012.
Pie charts
Pie charts use slices cut out from circles representing percentages instead of actual numbers like most other types of graphs do.
Scatterplots
Scatterplots allow readers’ eyes to travel freely around axes without having initial assumptions about what kind(s) might lie within one particular region before seeing any data being plotted therein.” Scatterplots are perfect for displaying relationships between two variables and determining if there is any correlation between them. For example, if you were a PT at a clinic that offered free physical therapy services to anyone who could not afford them and wanted to see if there was any correlation between the number of time patients spent in treatment before and after having received their free services, then you would use a scatterplot—because it shows how many people came into the clinic each month versus how many left after receiving their free treatments over several months, allowing readers to see if there was any correlation between the two variables.
Benefits of using data visualization techniques
- Data visualization can help you see patterns and trends, which will allow you to make better decisions.
- It allows people who are unfamiliar with data analysis and visualization to understand what the information means.
- Visualizing your findings helps others understand what they mean as well as how they came about.
- Data visualization techniques allow people to explore their data more fully than if they were simply looking at numbers on a piece of paper or computer screen alone (for example bar graphs). This allows them to become familiar with all aspects of their findings before presenting them in an organized fashion.
- Data visualization techniques also allow users access through their computer systems – whether it’s Excel spreadsheets saved locally onto USB drives or cloud storage services like Dropbox where files can be uploaded remotely via email address and password. Data visualization is also a great tool for saving your work in progress, so if something happens to your computer or hard drive, you have a backup of all your data on another machine. Data visualization can be used in many different ways – whether it’s creating charts, graphs and diagrams that show trends and relationships in the data being analyzed; or by creating interactive visualizations that allow users to explore their findings through multiple dimensions of information at once (for example: using 3D mapping to display geographical data).
5 things to remember about data visualization techniques
- Data visualization is a way to present data.
- It can be used for many purposes, including telling stories and conveying information.
- Data visualization is an important part of data analysis because it helps you see patterns in your data that might not be obvious at first glance.
- Data visualization techniques are available for many types of data and can help you create effective presentations or infographics.
Conclusion
If you are looking for a tool that can help you to visualize your data, then look no further. Data Visualization Tools have come a long way since the first web-based application was launched. Nowadays there are many different types of data visualization applications available on the market and each one has its unique features. One thing is certain though, these tools will enable your business to make better decisions based on the insights provided by their use.
