Data scientists have to analyze, interpret and visualize large data sets on a daily basis. This is why it’s important for them to have the right data visualization tools at their disposal.

It can be difficult for people who don’t work closely with data every day (such as managers or executives) to grasp what data scientists are telling them if all they receive is a written brief or an Excel spreadsheet full of numbers without any context. 

Best Data Visualization Tools to Know

  1. Tableau
  2. QlikView
  3. Microsoft Power BI
  4. Datawrapper
  5. Plotly
  6. Sisense
  7. Microsoft Excel
  8. Zoho Analytics

Data visualization tools allow data scientists to communicate their findings more effectively, which allows them to share their insights with other people who may not be familiar with data science concepts.


Best Data Visualization Tools for Every Data Scientist

In this article, we’ll take a look at some of the best data visualization tools for data scientists and how they can effectively increase the efficiency of data scientists. Below are eight important data visualization tools to help data scientists make better-informed decisions.

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1. Tableau

Tableau is a data visualization tool that can be used to create interactive graphs, charts and maps. It allows you to connect to different data sources and create visualizations in minutes.

You can also share your work with others and collaborate on projects.

Tableau Desktop is the original product. It’s made for creating static visualizations that can be published on one or more web pages, but it doesn’t create interactive maps.

Tableau Public is the free distribution of the Desktop product with some limitations.

Learning Tableau takes time and practice, but there are plenty of resources out there to help you learn how to use it. As a data scientist, Tableau should be the number one tool for you to learn and use in your everyday tasks.


2. QlikView

QlikView is not just another data visualization tool, it’s a data discovery platform that empowers users to make faster, more informed decisions by accelerating analytics, revealing new business insights and increasing the accuracy of results.

It’s been an intuitive software development kit that’s been used in organizations around the world for years. It can combine various kinds of data sources with visualizations in color-coded tables, bar charts, line graphs, pie charts and sliders.

QlikView has been developed using a “drag and drops” visualization interface, allowing users to easily add data from many different sources, such as databases or spreadsheets, without having to write any code. These characteristics also make it a relatively easier tool to learn and grasp.


3. Microsoft Power BI

Microsoft Power BI is a common data visualization tool used for business intelligence data. It’s often used for reporting, self-service analytics, and predictive analytics.

There are more than 200,000 organizations that are using this tool for their business intelligence needs, according to Microsoft.

It provides an end-user platform to create reports and share insights with others in their organization. It acts as a centralized repository for all your business data and can be accessed by all your business users.

Power BI also integrates with other SaaS products like Google Analytics, MailChimp and Office 365, etc.

Through such integrations, the reports created can be shared within the organization, and thus, make it a very important tool for organizations looking for a centralized data reporting system.

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4. Datawrapper

Datawrapper is an online data visualization tool that can be used in various contexts. It’s easy to use and has a clean and intuitive user interface.

Datawrapper allows users to upload their data files and create charts and maps directly in the browser. The charts and maps created in Datawrapper are responsive and designed for all kinds of devices, so readers will be able to view them on any device that they are using.

Datawrapper is free to use, however, there are certain limitations in the free version.

For example, it only lets you upload 500 rows of data and one sheet (or 5 MB) of data at a time. The available chart types include line, bar, area, column, pie and scatter. The data files that can be uploaded are .csv,.tsv and .txt files.


5. Plotly

Plotly is a data visualization tool that allows users to create interactive graphs, charts, and maps. You can also use Plotly to create a visualization of a data set, then share the link of that visualization with your readers on social media or your blog.

Graphs made on Plotly are interactive and have a unique URL, so they’re easy for you to share. Readers can hover over data points to view information about them and explore how you created them.

Readers can also explore all the data interactively instead of trying to decipher your code, which makes it perfect for sharing both interactive plots and data sets with your audience.

Plotly’s interface is easy to use, so you can create beautiful graphs in less time than ever before. Also, Plotly features a large library of open-source visualization types, allowing you to choose from a variety of plots and maps.


6. Sisense

Sisense is a data visualization tool that allows you to easily create interactive visualizations from your data. With Sisense, you can quickly and easily create extensive, informative dashboards that will help you understand your data better.

It has a very powerful yet simple and intuitive interface that allows you to drag-and-drop your data onto the canvas and create visualizations with a few mouse clicks.

Sisense is also fully integrated with several BI tools such as Microsoft Excel, BIRT, Pentaho, Qlikview and Tableau.

Sisense utilizes multi-dimensional in-memory technology that is designed for big data. It also has an embedded artificial intelligence engine with predictive analytics, making it easier to visualize data trends and discover hidden patterns in your data.


7. Microsoft Excel

Microsoft Excel is a data visualization tool with an easy-to-use interface.

There are many different ways of visualizing data in Excel. One of them is by using scatter plots. Scatter plots display the relationship between two data sets that you want to compare. You can also see how different variables are related to one another in order to determine if they’re connected or not.

Many data analysts use scatter plots to analyze statistical, scientific, medical and economic data for purposes such as market research or financial planning.


8. Zoho Analytics

Zoho Analytics is a data visualization and reporting tool that can help you easily create custom reports and dashboards. With Zoho Analytics, you can:

  • Quickly create custom reports and dashboards with drag-and-drop ease.
  • Get insights into your data with interactive charts and graphs.
  • Share reports and dashboards with colleagues or customers in just a few clicks.

It’s also part of the Zoho Office Suite, which also includes Zoho Writer, Zoho Sheet and Zoho Show. You can use Zoho Analytics to report on data from any of these applications, as well as from external sources such as MySQL, SQL Server, Oracle and Google Sheets.


Why Data Visualization Tools Are Important

Data is everywhere, and it’s important for brands to be able to decode and communicate their message in an effective manner.

And for data scientists, learning and keeping up with all the latest data visualization tools is paramount to success. Only after they master this art can they keep up with the pace of big data, and the fast-moving realms of artificial intelligence and machine learning.

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