Enterprise Data Engineering: Architecting Modern Data Warehouses for Business Success

This article provides a comprehensive overview of Enterprise Data Engineering with a focus on Data Warehouse Architecture, exploring its critical role in modern organizations' data strategies. It delves into the complexities of integrating diverse data sources, including point-of-sale systems, online databases, and CRM platforms. It examines the nuances of ETL/ELT processes essential for data integration. The article discusses various data warehouse architectures, compares cloud-based and on-premises solutions, and elaborates on dimensional modeling techniques crucial for effective data organization. It also covers creating and managing data marts, highlighting their importance in departmental analytics. The article emphasizes the significant benefits of enterprise data warehousing, including a unified data view, improved scalability, and enhanced decision-making capabilities. Furthermore, it addresses the critical aspects of data governance and quality. It explores advanced concepts such as data visualization, real-time processing, and AI and machine learning integration in data warehousing. This comprehensive exploration provides valuable insights for organizations seeking to leverage data as a strategic asset in the digital age.

Authors

Institutions

Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-02-23
DOI
https://doi.org/10.32628/cseit251112348
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enterprise Data Engineering: Architecting Modern Data Warehouses for Business Success

Dheeraj Kumar Bansal
1 citations
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
2.28
article

Enterprise Data Engineering: Architecting Modern Data Warehouses for Business Success

Dheeraj Kumar Bansal
article en
1 citations

Abstract

This article provides a comprehensive overview of Enterprise Data Engineering with a focus on Data Warehouse Architecture, exploring its critical role in modern organizations' data strategies. It delves into the complexities of integrating diverse data sources, including point-of-sale systems, online databases, and CRM platforms. It examines the nuances of ETL/ELT processes essential for data integration. The article discusses various data warehouse architectures, compares cloud-based and on-premises solutions, and elaborates on dimensional modeling techniques crucial for effective data organization. It also covers creating and managing data marts, highlighting their importance in departmental analytics. The article emphasizes the significant benefits of enterprise data warehousing, including a unified data view, improved scalability, and enhanced decision-making capabilities. Furthermore, it addresses the critical aspects of data governance and quality. It explores advanced concepts such as data visualization, real-time processing, and AI and machine learning integration in data warehousing. This comprehensive exploration provides valuable insights for organizations seeking to leverage data as a strategic asset in the digital age.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(1)
Birla Institute of Technology and Science, Pilani (IN)
Openalex Percentile: Top 14%
Big Data and Business Intelligence
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enterprise Data Engineering: Architecting Modern Data Warehouses for Business Success — Dheeraj Kumar Bansal · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS