In the modern era, digital data processing with a huge volume of data from the repository is
challenging due to various data formats and the extraction techniques available. The …

Hadoop is the most economical and cheap software framework that allows distributed
storage and parallel processing of more extensive data sets. Hadoop distributed file system …

The amount of digital data produced worldwide is exponentially growing. While the source of
this data, collectively known as Big Data, varies from among mobile services to cyber …

Big data analytics (BDA) is important to reduce healthcare costs. However, there are many
challenges of data aggregation, maintenance, integration, translation, analysis, and …

Serverless computing has revolutionized application deployment, obviating traditional
infrastructure management and dynamically allocating resources on demand. A significant …

As the data-driven paradigm for intelligent systems design is gaining prominence,
performance requirements have become very stringent, leading to numerous fine-tuned …

This survey article reviews the challenges associated with deploying and optimizing big data
applications and machine learning algorithms in cloud data centers and networks. The …

Hadoop has been regarded as the de-facto standard for handling data-intensive distributed
applications with its popular storage and processing engine called as the Hadoop …

Abstract Big Data Analytics is an innovative approach for extracting the data from a huge
volume of data warehouse systems. It reveals the method to compress the high volume of …

Processing Big Data in cloud is on the increase. An important issue for efficient execution of
Big Data processing jobs on a cloud platform is selecting the best fitting virtual machine (VM) …