دانلود مقاله استخراج داده های دانش برای هوش کسب و کار
خلاصه
1. معرفی
2. بررسی ادبیات
3. بررسی ادبیات
4. مدل مفهومی هوش تجاری
5. بحث و نتیجه گیری
منابع
Abstract
1. Introduction
2. Literature Review
3. Literature Review
4. Business Intelligence Conceptual Model
5. Discussion and Conclusion
References
چکیده
کاربرد سیستم های هوش تجاری را می توان به عنوان یک استراتژی تجاری و توسعه دید که مجموعه ای جامع از خدمات را برای ارائه اطلاعات مربوط به شرکت در تصمیم گیری های استراتژیک و عملیاتی و افزایش رقابت پذیری شرکت ادغام می کند. برای پیاده سازی موفقیت آمیز یک سیستم هوش تجاری در یک سازمان، استفاده از فرآیندها و قوانین تجاری کاملاً تعریف شده ضروری است. هدف از این مقاله ارائه و بررسی مجموعه‌ای از ابزارها و روش‌ها برای استخراج و بهره‌برداری از منابع کلان داده است. نتیجه این رویکرد پژوهشی با هدف تعریف مجموعه‌ای از شاخص‌ها و داشبوردها برای بهبود مدیریت و هوش تجاری سازمان است.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
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.