Data Visualization Tools Every Data Scientist Should Know

Data visualization helps get a clear picture of the dataset you are working on because we humans can understand things better by combining colours and graphics instead of just numbers. Some amazing data visualization tools can help a data scientist understand the complete information of a dataset and create reports. So, if you want to learn more about data visualization tools that can help you understand your data, then this article is for you. In this article, I’ll walk you through some of the best data visualization tools every data scientist should know.

Data Visualization Tools Every Data Scientist Should Know

Google Data Studio:

Google Data Studio is an online data analysis platform developed by Google to convert data into customizable, informative reports and dashboards. Some of the benefits of using Google Data Studio as a data visualization tool are:

  1. Visualize a dataset in highly interactive charts and tables
  2. Easily connect to a variety of data sources
  3. Share the ideas you have found with your team and the world
  4. Collaborate on reports with your team
  5. Faster reporting tools with integrated templates
  6. Data storytelling with almost any visualization you need
  7. Interactive filters and date range controls

Tableau:

Tableau is one of the most popular data analysis software that every data scientist should know how to use. It helps an analyst get the most out of a dataset. By using Tableau as a data visualization tool, a data scientist can explore and manage data faster than with a programming language when exploring a dataset. While there are many benefits to using a programming language for data visualization, using Tableau for data visualization can help a data scientist be more productive. If you are a student you can access Tableau for free, so if you are a student you should take this opportunity to learn it as it will bring you many benefits in the future.

DataPrep:

DataPrep is one of the fastest data visualization tools you can use when exploring a dataset using the Python programming language. By using DataPrep, from missing values to a complete report of your dataset in the form of interactive, customizable data visualizations, you can get the most out of your dataset with just a few lines of code. It helps explore your data faster with less effort and much better than any other data visualization library you may have used before. Simply put, it helps you prepare and explore your data in just a few lines of code.

Summary

So these were some of the best data visualization tools that every Data Scientist should know. Data visualization helps get a clear picture of the dataset you are working on because we humans can understand things better by combining colours and graphics instead of just numbers. I hope you liked this article on data visualization tools that you should know. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
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