Open-source data visualization packages HoloViz and DASH may both be used to make interactive graphs and charts in Python. Both of them are constructed with ease of use and flexibility in mind, and they both build on top of other well-known Python libraries like Plotly and Bokeh.

Python web-based data visualization apps can be created using the DASH (short for "Dynamic Applications in SHiny") module. It is based on the Shiny framework and enables Python-only development of interactive dashboards and data visualization applications.

A collection of Python packages called HoloViz (short for "Holographic Visualizations") is used to visualize huge, complex datasets. It is intended to be simple to use and flexible, and it contains tools for making interactive plots, maps, and 3D visualizations. Built on top of other well-known libraries like Matplotlib, Bokeh, and HoloViews, HoloViz is made to function effectively with huge and intricate datasets.

While HoloViz is a collection of modules for producing interactive visualizations of huge and complicated datasets in Python, DASH is a library for developing web-based data visualization apps. Although both are effective tools for data visualization, their purposes are quite different.

Which is the best?

The "best" data visualization library cannot be determined because the library to choose relies on your unique demands and objectives. Both DASH and HoloViz are effective data visualization systems with unique advantages and disadvantages.

If you want to create a web-based data visualization application that can be used on any device with a web browser, DASH is a fantastic option. The Shiny framework, on top of which it is developed, makes it simple to develop interactive dashboards and data visualization applications using only Python code.

If you want to build interactive visualizations of vast and complex datasets, HoloViz is a good option. It is intended to be simple to use and versatile, and it comes with a number of tools for making plots, maps, and 3D visualizations. Built on top of other well-known libraries like Matplotlib, Bokeh, and HoloViews, HoloViz is made to function effectively with huge and intricate datasets.

The optimal data visualization library for you will ultimately depend on your unique requirements and objectives. Consider using both libraries to determine which one is best for your use case.

What distinct advantage do they have over Tableau and Powerbi?

Power BI and Tableau are for-profit software applications, whereas DASH and HoloViz are open-source data visualization frameworks. This indicates that although Power BI and Tableau must be purchased and are subject to the terms of their individual licenses, DASH and HoloViz are freely accessible and can be updated and distributed by anybody.

Utilizing DASH or HoloViz has the benefit of being highly adaptable and can be adjusted to specific needs and objectives. You can access the source code and make adjustments or add new features as necessary because they are open-source. They can also be quickly integrated into current Python-based workflows and data pipelines because they are developed in Python.

Business customers frequently employ the robust and user-friendly data visualization tools Power BI and Tableau. Intuitive user interfaces and a vast selection of pre-built charts and visualizations make it simple to build dashboards and reports of industry-standard quality. They might not, however, provide the same degree of adaptability and personalization as DASH and HoloViz.

The optimal data visualization tool for you will ultimately depend on your unique requirements and objectives. Power BI or Tableau can be a suitable option if you require a robust and user-friendly tool to build dashboards and reports of a professional caliber. DASH or HoloViz may be better options if you require a very flexible and adaptable data visualization solution that can be adjusted to particular needs.