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@article{179677,
        author = {JAYAPRIYADHARISINI J},
        title = {Cloud Based Data Warehousing for Big Data Analytics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7387-7388},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179677},
        abstract = {With the recent advancements in computer 
technologies, the amount of data available is increasing 
day by day. However, excessive amounts of data create 
great 
challenges for users. Meanwhile, cloud 
computing services provide a powerful environment to 
store large volumes of data. To the best of our 
knowledge, this is a first systematic review of its kind, 
that reviews academic documents published in peer
reviewed venues from 2011 to 2019, based on a four
step selection process of identification, screening, 
eligibility, and inclusion for the selection process. They 
eliminate various requirements, such as dedicated 
space and maintenance of expensive computer 
hardware and software. Handling big data is a time
consuming task that requires large computational 
clusters to ensure successful data storage and 
processing. In this work, the definition, 
classification, 
and characteristics of big data are discussed, along 
with various cloud services, such as Microsoft Azure, 
Google Cloud, Amazon Web Services, International 
Business Machine cloud, Hortonworks, and Map R. A 
comparative analysis of various cloud-based big data 
frameworks is also performed. Various research 
challenges are defined in terms of distributed database 
storage, data security, heterogeneity, and data 
visualization.},
        keywords = {big data; data analysis; cloud  computing; Hadoop},
        month = {May},
        }