Data Management in the Cloud: Strategies for Storage and Analysis

EasyChair Preprint no. 12181

Abstract

In recent years, the adoption of cloud computing has revolutionized data management practices for organizations across various industries. This paper explores the strategies employed by enterprises for storing and analyzing data in the cloud. It delves into the advantages and challenges associated with cloud-based data management, including scalability, cost-effectiveness, security, and compliance. The paper discusses various storage options available in the cloud, such as object storage, file storage, and database services, highlighting their respective features and use cases. It also examines techniques for optimizing data storage to enhance performance and minimize costs, including data tiering, compression, and deduplication. Furthermore, the paper addresses the complexities of analyzing large volumes of data in the cloud. It explores the use of distributed computing frameworks like Apache Hadoop and Spark for processing big data efficiently. Additionally, it discusses the role of cloud-based analytics services and machine learning platforms in deriving valuable insights from data.

Keyphrases: Cloud Computing, data management, storage strategies

@Booklet{EasyChair:12181,
  author = {Taimur Hassan and Jane Elsa},
  title = {Data Management in the Cloud: Strategies for Storage and Analysis},
  howpublished = {EasyChair Preprint no. 12181},

  year = {EasyChair, 2024}}