DataWarehouse Modernization Using Document-Oriented ETL Framework for Real Time Analytics
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Rathore, V.S., Sharma, S.C., Tavares, J.M.R., Moreira, C., Surendiran, B. (eds) Rising Threats in Expert Applications and Solutions. Lecture Notes in Networks and Systems, vol 434. Springer, Singapor
Abstract
For past several years Relational Databases performing and providing
services to many applications. As data is growing, the necessity for a new kind of
databasewhich can handle such a huge amount of data in semistructured and unstructured
form has also increased. NoSQL databases are able to manage complexity of
data structure aswell as they can handle such a huge amount of data. Analysis is again
a challenging process of such semi-structured and unstructured data. Traditional data
warehouses are incapable of analyzing such schema-less data for decision making
as relational databases need to know schema in advance. ETL (Extract-Transform-
Load) is the process used to collect data from source, process and transform them and
storing into a data warehouse for further analysis. The paper presents a framework
for an ETL process for document-oriented data warehouse which provides real-time
analytics using classification approach at the data warehouse stage. The proposed
framework is designed and verified to enhance execution time for real-time analytics.
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Patel, M., Patel, D.B. (2022). Data Warehouse Modernization Using Document-Oriented ETL Framework for Real Time Analytics. In: Rathore, V.S., Sharma, S.C., Tavares, J.M.R., Moreira, C., Surendiran, B. (eds) Rising Threats in Expert Applications and Solutions. Lecture Notes in Networks and Systems, vol 434. Springer, Singapore. https://doi.org/10.1007/978-981-19-1122-4_5