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Publications (5)
The data engineering landscape is rapidly transforming to meet the growing demands of AI and machine learning (ML). Traditional monolithic data architectures are being replaced by modular, cloud-nativ...
In today’s data-centric world, the seamless transfer of data between systems is crucial, especially when handling big data. Sqoop (SQL-to-Hadoop) is a popular tool used to transfer large datasets betw...
In the age of data democratization and shared analytics, visualizing sensitive data without violating individual privacy has become a pressing challenge. This article introduces two novel frameworks:...
As data volume, velocity, and variety continue to expand exponentially, do the risks associated with securing sensitive information within big data ecosystems. Cybersecurity is no longer just a networ...
Data engineering is a critical field that supports the efficient handling, processing, and retrieval of largescale datasets. This paper explores two key aspects of data engineering: data compression t...
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