Earticle

초록

영어

Data modeling in data warehousing is a multifaceted process crucial for effective data management and analysis. Through techniques like conceptual, logical, and physical modeling, data architects organize complex data structures. The iterative nature of modeling allows adaptation to evolving business needs. The analysis shows that most organizations used the hybrid approach to create the data modeling in the data warehouse because this approach helps to create a good and efficient model of data in the data warehouse. But on the other hand, when we talk about the anomalies, researchers used an isolation forest and an LSTM algorithm based on net earnings by month. This is the way that helps to remove maximum anomalies from the data warehouse during storing data from sources. In this era, mostly people use Big data concept for data model for data warehousing but this technique is much complex for storing data and retrieval of data in this technique just single thing is missed for the data modeling named as reusability in future working of big data if we majorly emphasize on reusability of data the this tech can be most efficient as compare to present.

목차

Abstract
I. INTRODUCTION
II. LITERATURE REVIEW
III. METHODOLOGY
IV. RESULTS AND DISCUSSION
REFERENCES

키워드

저자

• Muhammad Ibrar [ Department of Computer & Mathematical Sciences New Mexico Highlands University, Las Vegas, USA ]
• Khalid Hamid [ Department of Computer Science, Superior University, Lahore. Pakistan ]
• Muhammad Waseem Iqbal [ Department of Software Engineering, Superior University, Lahore. Pakistan ]
• Muhammad Waleed Iqbal [ Department of Computer Science, COMSATS University Islamabad, Sahiwal Campus; Sahiwal, Pakistan ]
• Abeer Moazzam [ School of Computing, Horizon University College, Ajman, UAE ]
• Muhammad Adnan Khan [ School of Computing, Horizon University College, Ajman, UAE ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004