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Big Data Processing Techniques for Modern Computing Applications

Author(s) Dr. Maciej Grzenda
Country Poland
Abstract The rapid expansion of digital technologies has resulted in the generation of massive volumes of structured, semi-structured, and unstructured data across modern computing environments. Traditional data processing techniques often face limitations when dealing with the scale, velocity, diversity, and complexity of contemporary datasets. Big Data processing techniques provide advanced computational mechanisms for collecting, storing, transforming, analyzing, and extracting valuable information from large-scale data environments.
This study examines major Big Data processing techniques used in modern computing applications and develops a conceptual framework integrating data acquisition, distributed storage, preprocessing, parallel processing, analytical computation, and result interpretation. A conceptual and descriptive research methodology is adopted through the synthesis of secondary scholarly literature concerning Big Data analytics, distributed computing, cloud computing, parallel processing, stream processing, and data-intensive applications.
The analysis indicates that distributed processing, cloud-based computation, batch processing, stream processing, in-memory analytics, and scalable database technologies can significantly improve the efficiency and responsiveness of large-scale computational environments. The study further identifies challenges involving scalability, data quality, computational complexity, security, privacy, interoperability, and resource management. The proposed framework emphasizes the integration of scalable infrastructure with efficient processing methods to support modern applications. The study concludes that appropriate Big Data processing techniques can enhance computational performance, analytical capability, scalability, and real-time responsiveness across diverse technological domains.
Keywords Big Data, Data Processing, Distributed Computing, Parallel Processing, Cloud Computing, Stream Processing, Big Data Analytics, Modern Computing, Data Management.
Field Engineering
Published In Volume 1, Issue 6, November-December 2019
Published On 2019-12-30
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