دانلود مقاله ISI انگلیسی شماره 83094
ترجمه فارسی عنوان مقاله

مشخصات و مشتق شاخص های عملکرد کلیدی برای تجزیه و تحلیل کسب و کار: رویکرد معنایی

عنوان انگلیسی
Specification and derivation of key performance indicators for business analytics: A semantic approach
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
83094 2017 31 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Data & Knowledge Engineering, Volume 108, March 2017, Pages 30-49

ترجمه کلمات کلیدی
هوش تجاری، مدل های انبار داده های مفهومی، شاخص های اصلی عملکرد، مدل های استراتژیک، تجزیه و تحلیل کسب و کار،
کلمات کلیدی انگلیسی
Business intelligence; Conceptual data warehouse models; Key performance indicators; Strategic models; Business analytics;
پیش نمایش مقاله
پیش نمایش مقاله  مشخصات و مشتق شاخص های عملکرد کلیدی برای تجزیه و تحلیل کسب و کار: رویکرد معنایی

چکیده انگلیسی

Key Performance Indicators (KPI) measure the performance of an enterprise relative to its objectives thereby enabling corrective action where there are deviations. In current practice, KPIs are manually integrated within dashboards and scorecards used by decision makers. This practice entails various shortcomings. First, KPIs are not related to their business objectives and strategy. Consequently, decision makers often obtain a scattered view of the business status and business concerns. Second, while KPIs are defined by decision makers, their implementation is performed by IT specialists. This often results in discrepancies that are difficult to identify. In this paper, we propose an approach that provides decision makers with an integrated view of strategic business objectives and conceptual data warehouse KPIs. The main benefit of our proposal is that it links strategic business models to the data for monitoring and assessing them. In our proposal, KPIs are defined using a modeling language where decision makers specify KPIs using business terminology, but can also perform quick modifications and even navigate data while maintaining a strategic view. This enables monitoring and what-if analysis, thereby helping analysts to compare expectations with reported results.