Are you Interested in Data Visualization? I think you are searching for Best Data Visualization Tools Right! If I directly tell you this in one line, This will be unfair. The Reason is nothing is best, There are some pros and cons in every tool. So I will explore the top 5 data visualization tools which are popular among all data scientist. I will involve you in decision making to choose the best out of all for you. Anyways, Before we go for data visualization tools I will ask a question to you –
Table of Contents
- Why is Data Visualization important?
- Top 10 Data Visualization Tools-
- 2. Qlik View –
- 3.Qlik Sense –
- 4. SAS Visual Analytics –
- 5. D3.js–
- 6. Datawrapper–
- 7. Plotly –
- 8. E Charts
- 10. RAW-
- 11.Other Data Visualization Tools-
- How to Choose the Best Data Visualization Tool –
- Machine Learning with Data Visualization –
Why is Data Visualization important?
No direct answer for you. I will make it more interesting with an example. At least, If you are reading this article I can assume you must be an Internet user Right ?. If you use Internet Data, You must check your data usages like available data, consumed data, and so on. When you go for such kind of data analysis, If you will find so many long lines text in the place of graphs and numbers, How you will feel then?
See, To understand figures and remember them is easier than text Right? You can not make a better decision if you do not understand the complete data. I think till now we have understood why data visualization is important.
Let’s explore what are the best data visualization tools available in the market.
Top 10 Data Visualization Tools-
Data visualization tools not only helps to draw a simple chart using your data, but they help to draw Interactive charts. By saying Charts interactive chart, I mean extra functionality in charts for example drill down which can make you chart dynamic and more informative.
One of the major tools in this category. Tableau is famous for his drag and drops features in user Interface. This data visualization tool is free for some basic versions. It also supports multi-format data like xls,CSV, XML, database connections, etc. For more information on Tableau, You can reach out to Tableau’s official website.
Qlik view is again a powerful BI tool for decision making. It is easily configurable and Deployable. It is scalable with few constrains of RAM. The most loving feature of Qlik view is visual drill down. In case you want to read more about Qlik View, You can reach out Qlik View official website. Here you can find all the installation guide with other details.
Another powerful tool from the Qlik family. Its popularity is because of its user-friendly features like drag and drop. It is designed in such a manner that even a business user can use it. Its cloud-based infrastructure makes it strong among other data visualization tools. You can download the free desktop version of Qlik Sense and use it.
SAS VA is not only a data visualization tool but it is capable of predictive modeling and forecasting. It is easy to operate with drag and drop features. There is awesome community support for SAS Visual Analytics. You can directly reach SAS Visual Analytics from here.
Let me tell you the best thing about the Datawrapper Data Visualization tool. Here you do not need any coding skills. It is just a few click game. Hence the It is one the best option for beginners in the data science visualization tool.
7. Plotly –
When it comes to data visualization tools. No one can forget the name of Plotly. It is built on the top of d3.js. Although we have already included the name of d3.js on the list. It provides a better interface in Python, R, and Matlab Language.
8. E Charts
5. Timeline js
This is an amazing data visualization tool for data scientists. You may save a lot of time in importing data because It works on CSV and TSV files data. You may easily copy & paste data directly from these CSV and TSV type of files. Again It is a client-side API hence there is no server-side processing. Hence your data is highly secure. You may export charts in vector (SVG) or raster (PNG).
11.Other Data Visualization Tools-
Along with the above-written data visualization and BI tools, There are also some more popular data visualization tools. I am listing down. You can reach them here-
How to Choose the Best Data Visualization Tool –
I never claim any product best because every product has some advantages and disadvantages. We need to just figure out which set of features is required to solve our problem. I am going to list some required question which you should answer before choosing any data visualization tool or Software-
- What type of business problem, You are going to answer with data?
- How is your technical skill? ( For Example-DO you know SQL ?)
- which type of data you have? (Structured /Unstructured)
In other words, If you can answer these questions with reference to your selected tool, That data visualization tool is going to be best for you.
Congratulation, we have done an overview of data visualization tools. In case, You want to read more about other required skills for a data scientist you can refer the article complete skill set required for a data scientist.
Machine Learning with Data Visualization –
Hey, One of my favorite topics Machine Learning. How can We ignore to relate it with data visualization but before discussion If you want to take an overview of Machine Learning, You can refer to our article What is Machine Learning?
So lets Come to the point, When you write a machine learning code you need a visual display for some component like your accuracy, precision, recall, clusters or regression line, etc. In this situation, It is not mandatory to use any data visualization tool specifically. There must be some basic libraries to plot basic level graphs. if you check out any of the best machine learning languages For example lets take Python, There is a separate library Matplotlib for all such tasks. It has so many inbuilt functions for basic level graph drawing.
Better visualization leads to more satisfaction while exploring the hidden facts in the data. If you need to uncover the hidden information out of data, These tools are enough capable.
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Data Science Learner Team
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