Big Data Engineering on Cloud Platforms

With the rapid proliferation of data within the digital landscape, a significant amount of dossier is available, ushering in “Big Data” concepts, embracing massive volume, velocity, and variety of information generated daily. The Phenomenon of Big Data presents significant challenges and opportunities for individuals, business organizations, and all entities that can use the concept to achieve strategic advantages. Extensive data engineering is a critical discipline focusing on designing, developing, and managing systems and architectures that enable effective data handling and analysis. The paper's objective is to explore Big Data evolution and the role of Big Data in informed decision-making in the real world. By integrating enhanced technologies such as Apache, Hadoop, and Spark, cloud computing platforms have changed the data processing landscape, allowing individuals, organizations, and entities to extract meaningful data for decision-making. The paper has examined the current trends in big data, including machine learning and artificial intelligence, and the increasing concerns about data security, privacy and availability, and the rising edge of computing. Additionally, the journal discusses challenges such as managing diverse data sources, ensuring data quality, and addressing the skills gap in the workforce. From such a multilevel lens, the paper offers a nuanced understanding of Big Data Engineering, OOP, and Cloud Platforms and their significant impact on organizational strategic decisions and performance. The paper reveals that integrating Big Data concepts supports an organization's innovation, enhances decision-making processes, and gains a competitive edge, ultimately reshaping the future of data management and analysis. Accordingly, the study's findings underscore notable significant data engineering investment, unlocking capabilities for valuable data as an asset in an increasingly complex world.