What is Data Visualization?
Let’s take a step back to discuss the data science pipeline to understand data visualization better. Data science is the science of processing raw data using different methods, such as statistical analysis and machine learning, to arrive at simplified and understandable pieces of information.
This set of methods converts raw data into more meaningful chunks and is known as the data science pipeline.
Raw data undergo different stages within this pipeline, the third of which is data visualization. After data collection and scrubbing, you must interpret your data; identify trends and outliers that’ll lead to business values. This is where data visualization is crucial.
Data visualization is the representation of raw data, using tools such as charts, graphs, and maps, to make it easier for the human brain to comprehend.
This way, your users and stakeholders can easily pull insights, infer values, and make data-driven decisions. Data visualization is particularly essential for analyzing large data sets.
This is because you can easily convert large amounts of data into easy-to-understand charts, maps, graphs, and 3D models.
Why is Data Visualization Important in This Modern Era?
In today’s fast-paced era of constantly changing market conditions and customer expectations, businesses must innovate to remain competitive in any market.
This involves continuously using business data, predicting trends, and making data-driven decisions. Data visualization helps businesses achieve all this.
What’s more, in the modern business era, agility is the game’s name. In other words, quickly predicting trends and inferring business values are crucial in today’s business world.
Data visualization is a quick and effective method of statistical communication. Therefore, you can leverage data visualization tools to identify patterns and trends and become more agile quickly.
However, your bottom line (ROI) is most important in business. So how can data visualization affect your bottom line? Quickly identifying patterns and predicting trends makes for faster and more informed decision-making processes.
And faster decision-making means a shorter market time, ultimately boosting your bottom line.
What Is The Role of Charts, Graphs, and Maps in Data Visualization?
Charts, graphs, and maps are the most popular tools for visualizing large data sets. Charts or graphs can help you identify the relationship between two or more variables, depending on your chart type.
It can tell you how one variable impacts the whole or what data values skew from what you know as the norm.
On the other hand, maps display geographically related data. They can help you compare different regions or geographical locations.
With maps, you understand how one variable change affects your various regions or product distribution in each region. Maps can also show sales and profits in your areas or warehouse distribution to enhance your supply chain.
- 2D and 3D charts (also known as XY and XYZ charts)
- Line charts
- Bar charts
- Pie charts
- Polar charts
The ability to implement natural user-action features like pin to zoom, scrolling, panning, or clicking.
- Google charts