Training in data science not only includes the behind-the-scenes work of collecting and analyzing data but also communicating the findings that come from the process of analysis.

Through creating dynamic data visualizations, industry professionals are able to communicate key insights and takeaways to a diverse audience that may or may not be familiar with the field. Data visualization tools and software are essential components of the data science toolkit as they can be used to present information and data in a way that is thought-provoking and visually interesting.

The Uses of Data Visualization Tools and Software

Within the data science industry, data visualization tools and software are primarily used for the creation of graphs and charts which offer an image-based representation of data findings.

For data science professionals, there are several fields and industries which prioritize knowledge of data visualization tools. Within spaces where analysts are expected to create presentations or portfolios about their findings and work, data visualization tools are a one-stop-shop for creating graphs and charts, as well as ensuring that your work is both engaging and aesthetically pleasing.

Viewed as an important component of the communication of a project to others, data visualizations are considered to be the final step in the process of completing a data project. However, this does not mean that the analysis and exploration of the dataset are complete. In this final stage, data science professionals are also tasked with the process of evaluating and identifying the best method(s) of representing the dataset and its findings. Therefore data visualization tools and software simplify the process of visualization by offering multiple methods of presenting information and data. This includes, but is not limited to, the inclusion of multiple libraries, charts, graphics, and even colors and interactive components to add to the presentation of a data analysis project.

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Data visualization tools and software are most commonly used within the realm of business intelligence (BI) in order to create data-driven solutions and an understanding of complex equations and analyses. Business dashboards are used to display multiple graphs and charts at the same time in order to learn more about a company or topic. Dashboards are also useful to compare findings from multiple sources or to contrast different aspects of a dataset. Data visualizations and dashboards are especially effective when doing consulting work, product development, or even working with a brand or business.

The Top 5 Data Visualization Tools and Software

While there are many data visualization tools and software to choose from, the following list includes a diverse breadth of data science tools that are useful for both beginners and more advanced data science practitioners. Regardless of your experience level, these tools are accessible and powerful in terms of both versatility and performance.

1. Tableau

As one of the most popular data visualization tools, Tableau is a leading platform within the realm of business intelligence and data analytics. Known for its ease of use, Tableau makes the process of exploring and visualizing a dataset accessible to data science students and professionals of varying backgrounds and experience levels. Through its digital dashboards, Tableau offers a visual approach to engaging with a dataset that can be employed across industries. Whether you require visualization of a marketing funnel in the advertising industry or an expense analysis for a business, Tableau’s Business Dashboards include many options for representing and reporting data findings.

2. Google Charts

With a vast ecosystem of cloud-based tools and products, Google Charts is one of many offerings from this well-known technology company. Paired with collaborative data science tools such as Google Sheets and Colaboratory, Google Charts can turn the data projects you are working on into compelling graphs, visuals, and dashboards. The chart gallery also includes a library of data visualizations, such as timelines, tree-maps, and even interactive tables and pie charts. Through animation and colorful graphics, Google Charts is a flexible tool to use for drawing and charting data.

3. Microsoft Excel

For data science students and professionals that are beginning to learn how to collect and analyze data, Microsoft Excel is a useful introductory data visualization tool. Primarily known as a spreadsheet application, Excel has several features which allow users to turn a dataset into graphs and charts. From simple data visualizations, such as pie charts and line graphs, to more complex visualizations, such as maps, tiles, and cards, Excel offers a comprehensive library of data visualization tools. Through the Power View feature, Excel can also suggest different types of data visualizations based on your dataset. That said, Excel is just one of many data science tools offered by Microsoft which can be used for the process of data visualization.

4. Microsoft Power BI

Offered as a more complex data visualization tool, Microsoft Power BI is a business intelligence platform that can be used for data analysis and to generate and publish reports. By accepting the importation of data from multiple sources, these reports tell a compelling story about a dataset based on the platform’s understanding of the data. As a platform that allows users to work with drag and drop features, Power BI is also accessible to data analysts and industry professionals that want to visualize or work with a dataset without extensive knowledge of programming. This platform can also be used to create data dashboards and applications that make data analysis projects more accessible to diverse audiences.

5. IBM CognosAnalytics

Another popular tool for creating visualizations of data for a business or data science team, IBM CognosAnalytics is widely known for creating unique charts and graphics, such as word clouds, business reports, and digital dashboards. By importing data from a variety of sources and database tools, IBM CognosAnalytics is powered by Watson, an application that supports the mobilization of predictive analytics and data exploration algorithms. Regardless of your background in data science, this visualization tool can also be used to support data-driven decisions that can be showcased within a desktop or mobile environment.

Need more data visualization tools?

As the final stage in the process of completing a data science project, data visualization offers multiple opportunities to present and communicate your findings to an audience or collaborators. Noble Desktop offers several data visualization courses which include bootcamps that engage students through an exploration of data visualization tools and software. As one of the top data science tools for both visualization and analysis, the Tableau Bootcamp offers instruction on using this powerful platform for the creation of graphs, charts, and interactive images. In addition, training in data visualization can also be supported by taking data science classes which include instruction and experience with data science tools and software which can also be used to visually represent data analyses and findings.