روند های پذیرش هوش تجاری و بلوغ / The trend of business intelligence adoption and maturity

روند های پذیرش هوش تجاری و بلوغ The trend of business intelligence adoption and maturity

  • نوع فایل : کتاب
  • زبان : انگلیسی
  • ناشر : IEEE
  • چاپ و سال / کشور: 2018

توضیحات

رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت کسب و کار، مدیریت دانش
مجله International Islamic University Malaysia – Malaysia
دانشگاه کنفرانس بین المللی علوم و مهندسی کامپیوتر – International Conference on Computer Science and Engineering

منتشر شده در نشریه IEEE
کلمات کلیدی انگلیسی Data Processing; BI Adoption; BI Maturity; Data Mining; BI Success

Description

I. INTRODUCTION Today’s enterprises require to experience the challenge of responding to turbulent market change, meeting the escalating customer requirements and providing the quality product within a short product lifecycle [1] In recent years, market enthusiasm toward business intelligence (BI) is overwhelming [2, 3] According to [3], BI spending rose 16 percent in 2012 to hit $12.9 billion. Meanwhile, a CIO survey of 251 IT leaders revealed that more than 56 percent of organizations are considering expanding their usage of BI [4]. However, the question is raised that big companies are going ahead while the Small-medium-company are left behind and they are incapable of keeping pace with their big jaunt. This is the reality or fact that most of the companies know the benefits of using BI technologies which are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability. Nevertheless, BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmark-ing, text mining, predictive analytics and prescriptive analytics. BI with an organizational implementation of specific philosophy and methodology referred as working with information and knowledge, easy communication and technology, holistic knowledge sharing along with the effective analytic approach to business processes in organizations should be predominately associated by Decision makers as well as today’s organizations. Reviewing the existing literature on BI critically will provide a solid theoretical foundation as well as justification to the body of knowledge [5].
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