Amplifying Big Data Utilization in Healthcare Analytics Through Cloud and Snowflake Migration (Published)
Amplifying the utilization of big data in healthcare analytics through cloud and Snowflake migration presents a significant opportunity to enhance data-driven insights and decision-making in the healthcare sector. This migration makes it easier to move large amounts of healthcare data to the cloud. Applications deployed in could are scalable for in-depth analysis in Health Care industry. The cloud is becoming more popular for storing data and running applications because it can easily grow with your needs, requires little to no management, improves security, and offers budget flexibility. The benefits of the cloud are obvious — once you get there. Moving to the cloud requires planning, strategy, and the right tools for data migration. [1] By using Snowflake’s advanced data warehousing tools, healthcare organizations can smoothly handle and analyze their complex and varied data. This helps them quickly uncover important insights and make better decisions. The shift to cloud technology and Snowflake has the potential to significantly enhance real-time analytics, personalized patient care, and evidence-based decision-making in healthcare. When healthcare organizations leverage big data in a cloud-based setting, they can discover valuable insights from their data, ultimately improving clinical outcomes, operational efficiency, and healthcare delivery. This study explores how the adoption of cloud and Snowflake in healthcare analytics can bring about transformative change and create new possibilities for leveraging data and generating insights in the healthcare sector.
Keywords: Big Data, Cloud Migration, Data Insights, Decision Making, Healthcare Analytics, Real-time Analytics, Snowflake, data security, scalability
Application of Software-Defined Networking (Published)
Software-Defined Networking (SDN) is an architecture purporting to be dynamic, manageable cost-effective, and adaptable, seeking to be suitable for the high bandwidth, dynamic nature of today’s applications. SDN architectures decouple network control and forwarding functions enabling the network control to become directly programmable and the underlying infrastructure to be abstract from application and network services. In this paper, the advantages and challenges of Software-Defined Networking (SDN) are discussed.However, the Software Defined Networking application (SDN App) and the application of SDN are also discussed in detail.
Uzoma I., Sunday and Samuel D., Akhibi(2022) Application of Software-Defined Networking, European Journal of Computer Science and Information Technology, Vol.10, No.2, pp.27-48
Keywords: Networking, Software, controller, packet, scalability
Query Processing in the Cloud for Big Data Applications Benefits and Risks (Published)
The advent of cloud computing has transformed the landscape of big data processing, offering numerous benefits and presenting certain risks. This paper explores the domain of query processing in the cloud for big data applications, elucidating the advantages and challenges associated with this paradigm shift. Benefits: Scalability: Cloud platforms provide elastic resources, allowing big data applications to scale up or down based on demand. This scalability enables organizations to process vast amounts of data without significant upfront investments in hardware. Accessibility: Cloud-based query processing offers accessibility from anywhere, promoting remote work and collaboration, and facilitating data sharing and analysis among global teams. Risks: Data Security and Privacy: Storing and processing sensitive data in the cloud can pose security and privacy risks if not properly managed. Data breaches and unauthorized access are potential concerns. Data Transfer Costs: Transferring large volumes of data to and from the cloud can result in significant costs, particularly when dealing with extensive datasets. Vendor Lock-In: Adopting cloud services can lead to vendor lock-in, making it challenging to migrate to another provider or back to on-premises infrastructure. This paper delves into these benefits and risks in detail, providing insights into strategies for mitigating the associated challenges and making informed decisions when considering query processing in the cloud for big data applications. The balance between reaping the benefits of cloud scalability and managing the associated risks is crucial in the ever-evolving landscape of big data processing.
Keywords: Accessibility, Big Data, Cloud Computing, Cost Efficiency, Managed Services, Query processing, scalability