Big Data Management and Analytics as a Cloud Service


  • Shahad Alghamdi Prince Mohammad Bin Fahd University, Al-Khobar, Saudi Arabia
  • Sarah Alghamdi
  • Yasmeen Almansour
  • Alfia Badiwalla



Big data, Data Analytics, Data Processing, IoT


Traditional database management systems are inadequate for handling uncertain data due to design limitations. Various methods address database uncertainty, often oversimplifying and restricting representable uncertainties. Rapid data growth from technologies like IoT, multimedia, and social media has led to massive diverse data, known as big data, categorized into structured, semi-structured, and unstructured types. Coping with big data's challenges is encapsulated in the "Vs Model" with volume, velocity, and variety dimensions. It aims to gather variable information for causal understanding and informed decisions. Big data offers competitive advantages: smart decisions (69%), operational control (54%), customer insights (52%), and cost cuts (47%). This research studies big data management and cloud computing, where data and apps are accessed via the internet, saving resources globally. Cloud's simplicity and power facilitate tasks and storage. Risks include bankruptcy or breaches, yet cloud remains valuable for preserving big data. Vital factors in big data's value creation involve converting IT costs to assets and connecting big data outcomes to performance. This abstract summarizes exploration of traditional limitations, big data's essence, cloud's potential, and value creation nuances.




How to Cite

Shahad Alghamdi, Alghamdi, S. ., Almansour, Y. ., & Badiwalla, A. . (2023). Big Data Management and Analytics as a Cloud Service. International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence, 2(1).



Review Article