Data engineering is the foundation of data science and lays the groundwork for analysis and modeling.
In order for organizations to extract knowledge and insights from structured and unstructured data,
fast access to accurate and complete datasets is critical. Working with massive amounts of
data from disparate sources requires complex infrastructure and expertise. Minor inefficiencies
can result in major costs, both in terms of time and money, when scaled across millions to trillions of data points.

In this workshop, we’ll explore how GPUs can improve data pipelines and how using advanced data engineering tools and techniques can result in significant performance acceleration. Faster pipelines produce fresher dashboards and machine learning (ML) models, so users can have the most current information at their fingertips.