A simple, quick, and efficient way to build a full-stack data application
This article explains how to build user-friendly production-ready data scientists applications.
As a Data Scientist, you might want to create dashboards for data visualization, visualize data and even implement business applications to assist stakeholders in making actionable decisions.
Multiple tools and technology can be used to perform those tasks, whether open-source or proprietary software. However, these might not be ideal for the following reasons:
Some of the open-source technologies require a steep learning curve and hiring individuals with the appropriate expertise. Consequently, organizations may face an increased onboarding time for new employees, higher training costs, and potential challenges in finding qualified candidates.
Other open-source solutions are great for prototypes but will not scale to a production-ready application
Similarly, proprietary tools also come with their own challenges, including higher licensing costs, limited customization, and difficulty for businesses to switch to other solutions.
Wouldn’t it be nice if there was a tool that is not only open-source but also easy to learn and able to scale into a full application?
That’s where Taipy comes in handy 🎉
This article will explain what Taipy is, along with some business cases that it can solve before exploring its key features. Furthermore, it will illustrate all the steps to create a full web application.
In this article
- What is Taipy and why should you care?
- Key Features of Taipy
- Getting started with Taipy
- Time to create a Taipy Dashboard from Scratch
- Taipy Back-end in Action
Data Scientist - MLOps Engineer - Content Creator
Zoumana is a content creator and a highly regarded tech writer on Medium, with a dregree in Computer Science (with a specific focus on Machine Learning) and a second one in Data Science. He’s currently senior data scientist at