مقاله انگلیسی رایگان در مورد استخراج داده های دانش برای هوش تجاری – الزویر 2022

 

مشخصات مقاله
ترجمه عنوان مقاله استخراج داده های دانش برای هوش تجاری: یک رویکرد تحقیقاتی طراحی
عنوان انگلیسی مقاله Knowledge data extraction for business intelligence A design science research approach
نشریه الزویر
انتشار مقاله سال 2022
تعداد صفحات مقاله انگلیسی 9 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
2.267 در سال 2020
شاخص H_index 92 در سال 2022
شاخص SJR 0.569 در سال 2020
شناسه ISSN 1877-0509
فرضیه ندارد
مدل مفهومی دارد، بخش 4 صفحه 6
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت دانش – مدیریت کسب و کار – مدیریت بازرگانی
نوع ارائه مقاله
ژورنال و کنفرانس
مجله  پروسیدیای علوم کامپیوتر – Procedia Computer Science
دانشگاه Universidade Lusófona do Porto, Portugal
کلمات کلیدی هوش تجاری – کلان داده ها – انبار داده – داده کاوی – کشف داده های دانش – علوم طراحی
کلمات کلیدی انگلیسی Business Intelligence, Big Data, Data Wharehouse, Data Mining, Knowledge Data Discovery, Design Science
شناسه دیجیتال – doi
https://doi.org/10.1016/j.procs.2022.08.016
لینک سایت مرجع https://www.sciencedirect.com/science/article/pii/S1877050922007542
کد محصول e17363
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
1 Introduction
2 Literature Review
3 Literature Review
4 Business Intelligence Conceptual Model
5 Discussion and Conclusion
References

بخشی از متن مقاله:

Abstract

     The application of Business Intelligence systems can be seen as a business strategy and development, which integrates a comprehensive set of services to provide relevant corporate information in strategic and operational decision-making, and to increase the corporation’s competitiveness. For the successful implementation of a Business Intelligence System in an organization, it is necessary to use well-defined processes and business rules. The purpose of this article is to present and explore a set of tools and practices for extracting and exploiting Big Data sources. The result of this research approach aims to define a set of indicators and dashboards to improve the organization’s business management and intelligence.

Introduction

     rtually available to everyone, anytime and from anywhere. Thus, with globalization contributing to increased competitiveness, organizations are forced to constantly change, to manage a large amount of data generated daily and which are essential to support decision-making. There is also a need to consider the competitiveness between organizations, where the awareness that data represent an essential source for the production of necessary information is becoming ever greater [19][6][7]. Computer applications have allowed

     Computer applications have allowed organizations to have quality control over data, generate relevant indicators to be provided to managers about the organizations business, preparing them to design forecast scenarios more effectively and efficiently. Consequently, organizations are becoming increasingly dependent on the use of Business Intelligence (BI) applications to extract, process and organize the necessary data.

Discussion and Conclusion

     After characterizing the various phases of the work, some conclusions and results can be considered. The first coincides with the importance of knowledge of data for organizations. Data stored in different sources must be extracted and explored for a platform such as Data Warehouses and associated with BI systems, to suit users and the organization, to improve the quality of information, and obtain the knowledge necessary for decision making.

     In this sense, the importance of reviewing the literature must be recognized, allowing the study and characterization of platforms, applications and systems, for the process of extracting and exploring data knowledge for BI.

     The research methodology phase contextualizes the development structure of the aligned work, with the objective to be achieved, through the creation of the artifact, from the extraction and exploration of relevant data that serve the BI system. The DSR methodology allows finding an acceptable solution to the problem. After analysing the problem and in accordance with this methodology, the solution found was the creation of a cataloguing typology, which makes it possible to identify how and which data extraction and exploration tools are best suited to the users’ requirements.

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