Human-AI collaboration essential for effective data engineering

Automation is changing rapidly, especially in data engineering. Traditional robotic process automation (RPA) tools are becoming old-fashioned as artificial intelligence (AI) takes center stage. The next phase of automation is becoming more complex and is closely linked to effective data engineering. Data engineering involves creating and managing systems that help businesses organize and use data efficiently. However, it is not straightforward. Challenges like data duplication and verification require human oversight. While machines can automate many tasks, a successful approach needs a blend of human skills and AI capabilities. The European Commission predicts that the data economy in the EU will be worth over €800 billion by the end of 2025. The U.S. market is also expected to see massive growth, generating around 180 zettabytes of data. This emphasizes the importance of data engineering in driving business success. Gary Sidhu, a senior executive at GTT, emphasizes that working effectively in data engineering requires cooperation between humans and machines. He notes that humans play a key role in setting standards and ensuring data is managed properly. Problems typically arise when businesses have data spread across different systems, especially after rapid growth. To tackle these issues, companies should create a centralized hub for managing data. This hub would connect various systems and ensure all data is accurate and accessible. Establishing clear data management practices and training employees is crucial to making these systems work. Securing data as it flows within and outside the organization is another vital aspect. Companies must focus on protecting data through advanced API management and strong security measures. Network virtualization can help improve security by prioritizing functions that protect data. The future of data engineering looks promising, with an even closer partnership between human data engineers and AI. Humans will continue to develop robust data governance practices while AI monitors compliance and ensures data quality. This synergy could lead to improved productivity for employees and better services for customers. Ultimately, the collaboration of humans and technology will enhance business operations and data management practices.