Council Post: Robust Data Engineering Practices Can Supercharge AI

As artificial intelligence (AI) reshapes industries with its ability to provide unprecedented insights and automation, the importance of high-quality, well-structured data is becoming increasingly evident. However, many organizations struggle to unlock AI's full potential due to poor data management practices, inconsistent data quality, and inefficient data pipelines.  Without robust data engineering, AI models often receive incomplete, inaccurate, or unstructured data, leading to suboptimal performance and unreliable outcomes. This article explores the critical role of data engineering in addressing these challenges, highlighting how structured data pipelines, effective data integration, and rigorous data quality management are essential for maximizing AI’s capabilities and ensu