Data Visualization Tools for Data Scientists
Big data and artificial intelligence techniques are sweeping across industries. Organizing, interpreting, and communicating key trends and patterns within the data is vital for a company’s success. Recently, a wide variety of data visualization tools have become available to support the extraction and delivery of insight to business stakeholders. Today, data scientists are at the front line of deploying these visualization tools. Data scientists are often expected to communicate a model’s findings to customers and managers with clear and concise visualizations. Below, we discuss some of the major data visualization tools currently at use by data scientists across a wide variety of industries.
Tableau software is a leading visualization tool ever since its founding in 2003. Tableau is accessible to both individuals and enterprises with Tableau Desktop and Tableau Server as key products. Tableau connects to a wide variety of data sources including excel, SQL databases, and SAS files. Tableau's drag and drop technology enable quick calculations and the construction of interactive charts and dashboards from structured and unstructured data. Moreover, Tableau is mobile friendly, handles vast amounts of data seamlessly, and has a large and loyal customer base among data scientists. Of note, Tableau licenses costs may be a limiting factor for start-ups and smaller sized enterprises.
Power BI is a Microsoft business visual analytics tool that is a close competitor to Tableau. Power BI also connects to a wide range of data sources such as excel worksheets and SQL databases. In addition, Power BI is a simple and user-friendly tool that builds dynamic interactive charts and dashboards. Power BI is particularly effective as a business visualization tool for business analysts. Some of the popular products include Power BI Desktop and Power BI Service. A key strength of Power BI is its connectivity to other Microsoft products including Azure analytics services. Its usability, visualization capabilities, and affordability ensure Power BI’s growing popularity.
Dash & Shiny
There are a wide variety of data visualization tools available to data scientists. Excel dashboards are a quick and straightforward approach to translate a worksheet into an interactive visualization. However, excel dashboards are limited by the data sources, data volume, user friendliness, and does not have automated analytics capabilities. Dash and Shiny are popular web-based applications to build out interactive dashboards. These tools connect seamlessly to existing R or Python data science and machine learning toolkits, analytics capabilities, and visualization libraries. This enables unparalleled flexibility to build out a dashboard from the bottom-up without the limitation of pre-existing visualization charts or approaches.