Would you prefer to view large data tables and then make sense of that data or view a data visualization that represents that data in an easy to understand visual format? Well, most of you would prefer data visualization! And that is because data visualization is extremely useful in understanding the data and obtaining useful insights. It can allow you to get an instant understanding of the data that is just not possible by observing rows of data in a table. That’s what makes it so important in Data Science!
Data visualization is a critical aspect of data science because it allows data scientists to present complex data in an easily understandable and digestible format. Here are a few reasons why data visualization is so important in data science:
- Helps with data exploration: Data visualization enables data scientists to explore the data and identify patterns, trends, and outliers quickly. By visualizing data, one can identify relationships between variables that may not be apparent when looking at data in a tabular format.
- Communicates insights: Data visualization helps data scientists communicate insights to stakeholders in an easy-to-understand format. A well-designed visualization can help non-technical stakeholders understand complex data and make informed decisions based on that data.
- Aids in decision-making: Data visualization is critical to decision-making because it enables stakeholders to see trends and patterns that may not be immediately apparent in a raw data set. By presenting data in a visual format, data scientists can help stakeholders make informed decisions quickly.
- Facilitates storytelling: Data visualization is an essential component of data storytelling. By creating compelling visualizations, data scientists can create a narrative around the data that resonates with stakeholders.
Overall, data visualization is critical to data science because it helps data scientists communicate insights, aid in decision-making, facilitate storytelling, and explore data. Without data visualization, it would be challenging to gain insights from complex data sets and make informed decisions.
Let’s take an example. Suppose you compile a data visualization of the company’s profits from 2010 to 2020 and create a line chart. It would be very easy to see the line going constantly up with a drop in just 2018. So you can observe in a second that the company has had continuous profits in all the years except a loss in 2018. It would not be that easy to get this information so fast from a data table.
This is just one demonstration of the usefulness of data visualization that makes it so popular in data science. Let’s see some more reasons why data visualization is so important.
1. Data Visualization Discovers the Trends in Data
The most important thing that data visualization does is discovering the trends in data. After all, it is much easier to observe data trends when all the data is laid out in front of you in a visual form as compared to data in a table. For example, The below screenshot on Tableau demonstrates the sum of sales made by each customer in descending order. However, the color red denotes loss while grey denotes profits. So it is very easy to observe from this visualization that even though some customers may have huge sales, they are still in the loss. This would be very difficult to observe from a table.
2. Data Visualization is Interactive
Data Visualization can be used to interact with the users in a way that textual table-based data cannot. After all, data visualization tells a story from a particular angle to the users, and that by default makes it interactive. Users can also focus on aspects of the data visualization that they find particularly interesting and then they can learn more about that aspect of the data. The data visualization also allows the user to obtain a holistic view of the data using different types of charts and ample usage of colors, shapes, etc. This interactivity also allows the viewers to understand the data visualization at a single glance which is rather difficult for
3. Data Visualization Provides a Perspective on the Data
Data Visualization provides a perspective on data by showing it’s meaning in the larger scheme of things. It demonstrates how particular data references stand with respect to the overall data picture. In the below data visualization on Tableau, the between the Sales and Profit provides a data perspective with respect to these two measures. It also demonstrates that there are very few sales above 12K and higher sales do not necessarily mean a higher profit.
4. Data Visualization Explains a Data Process
Data Visualizations can be used to demonstrate a data process from the beginning to the end. This can be done by using many different charts in a dashboard on a data story to convey a process. This method allows the viewers to get a lot of information in multiple smaller visualizations so that they can easily digest the data and understand the overarching data process. This might be difficult to convey without visualizations as viewers would not be able to understand the data process by just looking at data tables.
5. Data Visualization Strokes the Imagination
There is nothing that can ignite viewer imaginations more than beautiful and well-presented data visualization! There is so much more power in the visual images to stroke imagination as compared to textual tables. This is because humans are primarily visual beings and they can understand data much faster if it is presented to them in a visual format. This also allows them to use their own imagination and deeply analyze the visualization which may provide them more insights than just reading dry acts and analyzing a data table.
6. Data Visualization Tells a Data Story
A data visualization is also a medium to tell a data story to the viewers. The visualization can be used to present the data facts in an easy to understand form while telling a story and leading the viewers to an inevitable conclusion. This data story like any other type of story should have a good beginning, a basic plot, and an ending that it is leading towards. For example, if a data analyst has to craft a data visualization for company executives detailing the profits in various products, then the data story can start with the profits and losses of various products and move on to recommendations on how to tackle the losses.
7. Data Visualization Puts the Data into the Correct Context
It is very difficult to understand the context of the data with data visualization. Since context provides the whole circumstances of the data, it is very difficult to grasp by just reading numbers in a table. In the below data visualization on Tableau, a TreeMap is used to demonstrate the number of sales in each region of the United States. It is very easy to understand from this data visualization that California has the largest amount of sales out of the total since the rectangle for California is the largest. But this information is not easy to understand out of context without data visualization.
8. Data Visualization is Educational for Users
Data contains knowledge! But it is very difficult to teach this knowledge just by observing this data in tables. After all, it would be able to synthesize this data to obtain anything useful or educational. However, data visualization can present this knowledge n easily understandable forms. That is why it can be used in an educational manner to easily provide information about a vast category to topics to the viewers.
9. Data Visualization Saves Time
It is definitely faster to gather some insights from the data using a data visualization rather than just studying a chart. In the below screenshot on Tableau, it is very easy to identify the states that have suffered a net loss rather than a profit. This is because all the cells with a loss are colored red using a heat map so it is obvious states have suffered a loss. Compare this to a normal table where you would need to check each cell to see if it has a negative value to determine a loss. Obviously data visualization saves a lot of time in this situation!
10. Data Visualization Presents Data Beautifully
Raw data can be called informative but it cannot be called beautiful! And data visualization is the skill of presenting this data beautifully so that the viewers are also interested in this data. After all, humans are primarily visual beings and they can understand information much faster if it is visually stimulating. But it is very important not to sacrifice function for beauty in a data visualization. After all, the primary purpose of data visualization is to easily impart information to its viewers and there is no point in making it beautiful if that also makes it harder to understand.
All of these reasons demonstrate the importance of data visualization in data science. Basically, it is a much more user-friendly method to understand the data and also demonstrate the trends and patterns in the data to other people. And it doesn’t hurt that data visualization is beautiful to look at and so more appealing to people than rows of boring data!
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