Data visualization is a powerful resource for organizing, interpreting and presenting data. Data visualization is a key resource for data-driven companies. For many people, dealing with this new context of constant analysis is still a huge challenge. Data Visualization comes precisely to facilitate this process, being an alternative to facilitate the organization, interpretation and presentation of various data.
In this article, we will explain which data visualization features help to simplify the visualization and understanding of data, especially for Product professionals – who always need to turn to numbers to understand their market context, as well as the needs of users.
What is Data Visualization?
The ability to organize, interpret, and present data via data visualization is a useful tool. Dealing with this new framework of the ongoing study is still a significant issue for many people. Data Visualization, a substitute for facilitating the organizing, interpretation, and presentation of varied data, comes specifically to facilitate this procedure.
We will define data visualization, discuss its importance, and outline some of its advantages in this article.
Data visualization has existed at least since the 18th century, making it much older than computers. You undoubtedly probably know about the iconic line, pie, circle, and bar graphs, mostly developed by English engineer William Playfair.
However, it is undeniable that the development of computers has made the process of processing data easier, and we now have access to a wide range of data visualization tools to make the analysis simpler.
How important is Data Visualization?
Knowing what Data Visualization is now, it is important to point out that this tool is much more than just a means of converting data into an appealing display. By enabling visual modifications that have an impact and the ability to provide several analyses in the same file, this feature intends to facilitate strategic decisions from a more participatory perspective, streamlining the procedure for the entire team engaged.
Data visualization is crucial for Product teams to identify bottlenecks and areas for improvement while making it easier to understand how people utilize the system.
Using data visualization tools to visualize network performance indicators can help Network Operations Center (NOC) operators quickly spot and fix problems, enhancing overall network reliability and reducing downtime.
More information on what is NOC monitoring can be found here.
Additionally, data visualization makes it possible for you to fully comprehend your users and processes, which aids in developing long-term strategies for sustainable business growth.
What are the principles of data visualization?
The Data Visualization representation must adhere to certain rules in order to achieve its goal. This data view ought to be:
Accurate: One benefit of data visualization is that the information is accurate. Hence, it is critical to have trustworthy and current data sources that accurately reflect your product, users, and business.
Useful: Having a large amount of data is useless if it cannot be used to build practical attitudes by using the insights offered by the displayed data. In order for Data Visualization to provide pertinent information, it must be connected to the team's or organization's goals.
Scalable: This means that Data Visualization must be capable of managing a significant amount of data. Data, in one of the PM3 Product Management Course professor's words, is "the voice of our users at scale". Thus, this information must be taken into consideration during visualization.
After briefly discussing the significance of data visualization, let's now delve deeper into its advantages—particularly for Product teams.
Benefits of using data visualization
We've talked a little bit about the importance of data visualization, and now let's take a closer look at the benefits of adopting it, especially with Product teams in mind.
More detailed data analysis
Data visualization enables you to see customer data, product data, and company data in a clearer and more structured way. Also, the level of detail you have in the data is significantly higher because Data Visualization tools enable you to work with a vast amount of data.
Thus, the team can act with more precision, clarity and detail for better analysis.
Ability to identify points of improvement
Since data visualization uses visual documentation, it makes it much easier to compare outcomes and spot problems and potential improvements. Which do you believe requires more time: deciphering a data-filled Excel spreadsheet or a pie chart that displays the results with various colours for each category?
While examining the data and making inferences from it, the visual component is helpful. All the information helps to make better decisions about what needs to be done to improve tactics and maximize outcomes.
Identification of patterns and influencing factors
Data Visualization works in conjunction with qualitative analyses (based, for example, on user interviews) to assist you understand some of the usage habits of your target market.
The team is also able to determine if there is any factor impacting the findings produced thanks to the comparison made possible by the visual documents.
Ease of sharing
You can often share visual documents in real-time with the Product team using Data Visualization tools' functionalities. This makes it easier for stakeholders and everyone else involved in the creation of the solution to align.
Allows quick forecasts from trends
Data visualization ultimately increases predictability for the Product team by making it easier to recognize patterns, influences, and trends.
Team members can decide and take action based on historical data. This reduces the possibility of error and helps to produce better plans.
Ease of understanding and communicating results
A visual document is significantly more useful and understandable than a spreadsheet or informational list. This is due to the fact that this visualization style arranges the data utilizing hues, forms, images, and other visual elements that make it easier for viewers to comprehend.
Information is centralized and categorized in data visualization to hasten the assimilation of this knowledge by individuals who access the visual document. As a result, this paradigm allows for much quicker and more practical outcomes in communication.