News24

To grow and thrive in the rapidly evolving AI landscape, organizations must strategically invest in their data engineering capabilities.

In today’s modern digital landscape, businesses are generating heavy data daily which can be processed, analyzed and interpreted for future scalability and growth. This is when AI-driven systems become integral across industries to help create real-time analytics, forecasting and initiating AI-driven automation. Beverly D’Souza, a Data Engineer at Patreon (previously worked at Meta) has played a key role in improving data workflows, processing data at pace and launching machine learning models. Having experience with ETL pipelines, cloud data systems, and AI analytics, she shared, “Building scalable AI-powered data pipelines comes with key challenges and to overcome these obstacles, organizations must implement distributed computing frameworks that can handle large-scale data processing efficiently. Incorporating AI-driven automation helps streamline data processing tasks, making the entire system faster and more efficient.”