Data scientists must to analyzeinterpret and view large datasets on a daily basis. That’s 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 understand what data scientists are telling them if all they get is a written brief or an Excel spreadsheet full of numbers without any context.

The best data visualization tools to know

  1. Picture
  2. QlikView
  3. Microsoft Power BI
  4. Data wrappers
  5. Plot
  6. Sisense
  7. Microsoft Excel
  8. Zoho Analytics

Data visualization tools enable 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.

The 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 more informed decisions.

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1. Framework

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

Public table 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 you learn and use in your day-to-day business.


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

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

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

3. Microsoft PowerBI

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

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

It provides a platform for the end user to create reports and share insights with others in their organization. It acts as a centralized repository for all your business data and is accessible to 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 across the organization and hence, make it a very important tool for organizations looking for a centralized data reporting system.

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4. Data wrappers

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

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

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

For example, it only allows you to upload 500 rows of data and one sheet (or 5MB) of data at a time. 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. Texture

Plot 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 dataset, then share that visualization’s link with your readers on social media or on your blog.

Charts made on Plotly are interactive and have a unique URL, so they’re easy 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 crack your code, making it perfect for sharing both interactive graphs and datasets with your audience.

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

6. Sense

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 expansive and informative dashboards that will help you better understand your data.

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 just a few mouse clicks.

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

Sisense uses multidimensional in-memory technology designed for big data. It also has a built-in AI engine with predictive analytics, making it easy to see 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 to view data in Excel. One of them is the use of scatter plots. Scatter plots show the relationship between two data sets that you want to compare. You can also see how different variables are related to each other to determine whether or not they are related.

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 analysis

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.
  • Gain insights into your data with interactive charts and graphs.
  • Share reports and dashboards with colleagues or clients 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 external sources like MySQL, SQL Server, Oracle, and Google Sheets.

Why data visualization tools matter

Data is everywhere and it is important that brands are able to decode and communicate their message effectively.

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

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