Enhancing data engineering requires human and AI collaboration

In Europe, the European Commission predicts that the value of the EU data economy will exceed €800 billion by 2025. The USA is also expecting rapid growth, with an estimated 180 zettabytes of data projected to be generated by then. These figures highlight the growing importance of data engineering, which encompasses certain practices, methodologies, and implementation techniques necessary for seamless IT service orchestration at various levels. Such tasks will increasingly require human oversight to maintain safety and effectiveness as automation becomes more prevalent. Gary Sidhu, Senior Vice President of Product Engineering at GTT, emphasizes that a successful collaboration between human data engineers and artificial intelligence (AI) is essential. He advocates for the integration of human expertise with advanced technology, noting that while technology alone can enhance performance, the involvement of skilled professionals is crucial. Sidhu references his extensive experience in telecommunications and at GTT, known for its Envision orchestration platform that connects people, data, and machinery. To streamline data practices and enhance efficiency, companies are advised to create a centralized information management hub. Such a hub helps eliminate redundancies and ensures stakeholders have access to accurate and current information. However, achieving this level of integration requires organizational discipline. Companies need a clear data strategy, encompassing the commitment of all employees to adhere to data management best practices, facilitating the success of data engineering initiatives. As data is integral to business operations, securing data transmission is vital, bringing additional complexity to IT security teams. According to research from Omdia, enterprises are focusing more on security functions in the evolving landscape of virtualization, emphasizing the need for secure access and security applications. Looking forward, the collaboration between human data engineers and AI is expected to deepen, allowing for more robust governance frameworks to be established, ensuring data accuracy and compliance in real-time monitoring. By prioritizing these efforts, organizations can effectively address challenges related to data management, leading towards more precision-engineered benefits in the future.