Before moving to the term data visualization, let’s discuss the term data science because this is where the word data visualization comes from. Data science is defined as the science of analyzing any data using statistics and machine learning techniques in order to make inferences about that data. But do you have any idea about what the data science pipeline is?
In data science, a pipeline is a set of actions that converts raw (and confusing) data from various sources (surveys, feedback, lists of purchases, votes, and so on) into an understandable format to store and analyze. Within a pipeline, raw data passes through several stages, including:
Here in this article, we will go deeper into data visualization.
What is Data Visualization?
The graphical representation of information and data in a visual or graphic format is known as data visualization (Example: charts, graphs, and maps). Data visualization tools make it easy to see and recognize patterns, trends, and anomalies in data. Data visualization tools and technologies are critical for analyzing large amounts of data and making data-driven decisions.
Categories of Data Visualization
Data visualization is an essential tool in the iterative process of grasping the massive amounts of data generated by big data. It is difficult enough to sift through the severe flooding of big data to find related, beneficial information, let alone identifying trends and developments. That’s why data visualization is essential for today’s big data and other users, which makes it easier for data collectors to communicate their findings and readers to see trends and patterns.
We’ve talked about how big data necessitates data visualization, so let’s continue the conversation by looking at the five main data visualization subgroups that can be discovered in big data instances.
Importance of Data Visualization
People can see and understand data patterns, trends, and outliers by visually representing insights derived from data. “Do you want me to draw you a picture?” is a counterargument that you should be aware of intended for someone who has difficulty understanding what the speaker is saying. On the other hand, data visualization paints that picture by presenting facts and figures clearly and visually strikingly. It’s also a valuable tool in the iterative effort to grasp the massive amounts of data generated by big data. The following are some of the benefits of data visualization:
Top Data Visualization Tools
The best interactive data visualization tools are listed below:
Advantages of Data Visualization
Real-world examples, of which there are many, are the best way to demonstrate the capabilities of data visualization techniques. As an example:
Data visualization is helpful in a wide range of fields, including:
How can InfosecTrain help you in your career?
The world is increasingly reliant on data to make life easier and design more effective ways to address the commercial sector’s numerous difficulties. As a result, Data Analysts is one of the most in-demand personnel in today’s global business. They are knowledgeable IT data stars who understand how to transform the tons of data generated by big data into tangible, valuable information. With this popular Data Science certification training course, InfosecTrain can help you kickstart your Data Analytics career.