Data Engineering: The powerhouse of Artificial Intelligence
NVIDIA founder and CEO Jensen Huang stated during an on-stage conversation with Databricks cofounder and CEO Ali Ghodsi at the Databricks Data + AI Summit 2024 on Wednesday that accelerated computing is revolutionizing data processing and analytics for businesses. “Every company’s business data is their gold mine,” Huang stated, adding that although each organization has vast volumes of data, it has been difficult to glean insights and knowledge from it.
Data Engineers are experts who help convert various forms of raw data into intelligence. Data Engineering is a crucial topic that serves as the foundation of any data-driven company, while being often overlooked. Data engineering is the practice of designing, creating, and maintaining infrastructure to facilitate the gathering, storage, and analysis of massive volumes of data. It guarantees that data flows seamlessly from many sources to where it is needed and is translated into a format that data scientists, analysts, and business leaders can easily access and use.
The value of data engineering cannot be emphasized. In an era when data is generated at unprecedented rates and volumes, organizations rely on strong data engineering to convert the deluge into useful insights. Without well-designed data pipelines, scalable storage options, and dependable data processing frameworks, even the best analytical tools and advanced algorithms would be ineffective.
“Artificial intelligence is only as good as the data that powers it,” says Frank Maddux, MD, Global Chief Medical Officer and Member of the Management Board, Fresenius Medical Care. “Dialysis care generates a large amount of data that can be used for secondary purposes, but multinational datasets are scarce due to the fundamental need for adherence to varying complex data protection regulations around the world, as well as the challenges in harmonization of data from different clinical systems,” said Len Usvyat, PhD, Head of Clinical Advanced Analytics for Fresenius Medical Care. “This important data tool increases the speed and robustness of the company’s analytical capabilities and provides greater consistency in generating data-driven clinical insights. The knowledge gained from these efforts has the potential to improve not just the practice of medicine, but more importantly the quality of life for people with kidney disease.
As we navigate the complexities of big data, let us remember that the true value of data is unlocked not just through its collection, but through the meticulous engineering that supports its lifecycle.
About the author: Bitthal Khaitan is a seasoned professional in cloud data engineering. With over 35,000 followers on LinkedIn and a vast audience reaching millions through his annual technical content views, Khaitan has established himself as a top tier thought leader. LinkedIn, a renowned professional networking platform with over 1 billion registered members worldwide, has recognized Mr. Khaitan as a Community Top Voice. His expertise in Data Engineering has led to invitations to contribute articles on various topics related to the field. His articles on LinkedIn have garnered recognition and engagement from the community, as evidenced by the Community Top Voice badge awarded to him.
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