Building reliant, scalable, efficient and production-ready data pipelines is vital to many modern businesses today to manage and visualize data effectively and make data-driven business decisions.
What’s more, teams are often required to integrate the data pipeline with a full-fledged GUI application that offers a seamless interaction.
But with increasing data, they are often faced with the challenge of efficient processing and analyzing it in existing data pipelines, resulting in:
- Issues with increasing data
- Increased run-time
- Inefficient use of resources
- Difficulty in scaling,
- Laggy interface, and many more.
Typically, these problems arise due to the lack of an efficient pipeline orchestration tool — one that can manage the execution of functions and pipelines effectively by:
- Optimizing pipeline performance through parallel processing and efficient resource allocation.
- Providing easy management of multiple pipelines and their dependencies
Ensuring the correct order of the pipeline tasks executions and more.
- To this end, Taipy is an open-source tool that streamlines the creation, management, and execution of reliable data-driven pipelines with low code.
Thus, in this article, I will demonstrate how you can utilize Taipy to create a complex and interactive data pipeline.
Let’s begin 🚀!
In this article
- Building blocks of Taipy Core
- Getting started with Taipy Core
- Developing a data pipeline with Taipy Core
- Latest Updates in Taipy 2.3
Data Scientist, Author of Daily Dose of Data Science
Avi is a Data Scientist and Data Science Writer. He writes about data science guides, tricks and tips, Machine Learning, SQL, Python, and more.