Build Large Data Pipelines Using Taipy

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 <ul> <li>Increased run-time</li> <li>Inefficient use of resources</li> <li>Difficulty in scaling,</li> <li>Laggy interface, and many more.</li> </ul> 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:   Processing types <ul> <li>Optimizing pipeline performance through parallel processing and efficient resource allocation.</li> <li>Providing easy management of multiple pipelines and their dependencies</li> <li>Ensuring the correct order of the pipeline tasks executions and more.</li> </ul> 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. <a href="https://towardsdev.com/build-large-data-pipelines-using-taipy-22922714751b">Read More</a>