research-article

The research of Data Integration and Business Intelligent based on drilling big data

Authors:

Gao Xiang,

Wang FangAuthors Info & Claims

ICIME 2017: Proceedings of the 9th International Conference on Information Management and Engineering

Pages 64 - 68

https://doi.org/10.1145/3149572.3149603

Published: 09 October 2017 Publication History

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Abstract

With the development of information technology, ChangQing drilling engineering company has accumulated a large number of data about drilling, and the research foundation of drilling big data technology had been formed. But now, huge volumes of data are distributed in different heterogeneous data sources due to the long-term decentralized construction, which is hard to realize the comprehensive analysis of related data. In this paper, aiming at the practical problems, a data integration and business intelligent- project based on drilling big data has been put forward. Referencing to the knowledge of this field, the system applies kettle which is a data integration tool to realize the integration of ETL heterogeneous data resource, establishes the data warehouse based on theme, and uses fine report which is a business intelligence tools to organize the views of drilling big data according to different user's requires, shows flexibly in multi-perspective view, thus provides powerful data support for user's drilling decision.

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Cited By

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Çelik C(2024)SMALL TO MEDIUM‐SIZED ENTERPRISES DATA PERCEPTION AND APPLICATIONSYönetim ve Ekonomi Araştırmaları Dergisi10.11611/yead.141077022:1(154-170)Online publication date: 28-Mar-2024
https://doi.org/10.11611/yead.1410770
Waqar A(2024)Intelligent decision support systems in construction engineering: An artificial intelligence and machine learning approachesExpert Systems with Applications10.1016/j.eswa.2024.123503249(123503)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123503
Rado JRodriguez C(2021)Business Intelligence Tools Implementing in the Field of Electrical Industry2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)10.1109/CICN51697.2021.9574665(50-55)Online publication date: 22-Sep-2021
https://doi.org/10.1109/CICN51697.2021.9574665

Index Terms

The research of Data Integration and Business Intelligent based on drilling big data
1. Information systems
  1. Data management systems
    1. Information integration
      1. Data cleaning

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Published In

ICIME 2017: Proceedings of the 9th International Conference on Information Management and Engineering

October 2017

233 pages

ISBN:9781450353373

DOI:10.1145/3149572

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Salford: University of Salford

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Association for Computing Machinery

New York, NY, United States

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Published: 09 October 2017

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ICIME 2017

ICIME 2017: 2017 9th International Conference on Information Management and Engineering

October 9 - 11, 2017

Barcelona, Spain

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Çelik C(2024)SMALL TO MEDIUM‐SIZED ENTERPRISES DATA PERCEPTION AND APPLICATIONSYönetim ve Ekonomi Araştırmaları Dergisi10.11611/yead.141077022:1(154-170)Online publication date: 28-Mar-2024
https://doi.org/10.11611/yead.1410770
Waqar A(2024)Intelligent decision support systems in construction engineering: An artificial intelligence and machine learning approachesExpert Systems with Applications10.1016/j.eswa.2024.123503249(123503)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123503
Rado JRodriguez C(2021)Business Intelligence Tools Implementing in the Field of Electrical Industry2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)10.1109/CICN51697.2021.9574665(50-55)Online publication date: 22-Sep-2021
https://doi.org/10.1109/CICN51697.2021.9574665

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Recommendations

Investigating Business Intelligence in the era of Big Data: concepts, benefits and challenges

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Data Integration, Cleaning, and Deduplication: Research Versus Industrial Projects