Enterprise Business Intelligence Research Articles

Enterprise Mashup Systems as Platform for Situational Applications

Currently, several Enterprise 2.0 platforms are beginning to emerge. This paper introduces Enterprise Mashup technology as a means to improve IT alignment of individual work processes and changing business needs. Enterprise Mashups enable users to create customized applications to easily find and transform business information and functionalities, as well as collaboratively share pre-built Mashup applications. Therefore, the concept of Enterprise Mashups integrates Web 2.0 technologies and principles with well-established paradigms such as Enterprise Information Integration, Business Intelligence, and Business Process Management. Involved organizational key drivers, technical challenges and inhibitors are discussed to assess the potential business value and explain the emerging expansion of Mashup platforms in companies.

Trends & Controversies

Business Intelligence (BI), a term coined in 1989, has gained much traction in the IT practitioner community and academia over the past two decades. According to Wikipedia, BI refers to the "skills, technologies, applications, and practices used to support decision making" (http://en.wikipedia.org/wiki/Business_intelligence). On the basis of a survey of 1,400 CEOs, the Gartner Group projected BI revenue to reach US$3 billion in 2009. Through BI initiatives, businesses are gaining insights from the growing volumes of transaction, product, inventory, customer, competitor, and industry data generated by enterprise-wide applications such as enterprise resource planning (ERP), customer relationship management (CRM), supply-chain management (SCM), knowledge management, collaborative computing, Web analytics, and so on. The same Gartner survey also showed that BI surpassed security as the top business IT priority in 2006.

The Development of Business Intelligence in Romanian Enterprises: A Possible Cultural Approach

Business Intelligence (in the present material we will use only the short form – BI) and intercultural management are considered, but also framed in the category „of the last arrived” ( in February 1994 the BI was formally defined in France) management science sub domains (it is used the singular form of the term, because in this context it is mentioned the fundamental sub domain and not the variety of approaches whom it can be assimilated to management – case in which it will be used the plural form: the term of the „management sciences”), resultant of some generalizing tries to propose solutions of success of organizations. Although still fulfills a resumative function regarding the organization of ideas, of its theoretical enunciations and not only, BI represents a discipline in continuous development (mostly because of its intentional and practical elements). These anticipative research will try to propose solutions (which can present interest in the enterprises daily practice, but also in the science) for the difficulties encountered in the enrolling of the BI’s activities and practices in the Romanian enterprises, keeping in mind the employees and the managers position towards the BI occurred fallowing an deduced behavior by the Romanian cultural peculiarity.

MAD skills

As massive data acquisition and storage becomes increasingly affordable, a wide variety of enterprises are employing statisticians to engage in sophisticated data analysis. In this paper we highlight the emerging practice of Magnetic, Agile, Deep (MAD) data analysis as a radical departure from traditional Enterprise Data Warehouses and Business Intelligence. We present our design philosophy, techniques and experience providing MAD analytics for one of the world's largest advertising networks at Fox Audience Network, using the Greenplum parallel database system. We describe database design methodologies that support the agile working style of analysts in these settings. We present dataparallel algorithms for sophisticated statistical techniques, with a focus on density methods. Finally, we reflect on database system features that enable agile design and flexible algorithm development using both SQL and MapReduce interfaces over a variety of storage mechanisms.

Facilitating change management with configurative reference modelling

Change management describes a structured approach to transitions from the present state to a desired state. Reference models can assist this process since they provide a solution schema for specific problems by adapting best or common-practice approaches. The configuration of reference models has been a field of research in the past. However, the integrative configuration of different reference models or respective reference models serving multiple purposes lacks applicable methods. In practice this is a common problem, as the simultaneous implementation and/or maintenance of business processes in an Enterprise Resource Planning (ERP) system and business intelligence system shows. We propose a methodology that allows the integrated configuration of conceptual models for transaction processing and decision support by integrating meta models for respective modelling languages. Additionally, its application is exemplified by extending an existing reference model in a business case.

The starting block: enterprise (business) intelligence – evolving towards knowledge valuation

PurposeThis paper proposes a logical starting point to valuing knowledge within the context of the business enterprise.Design/methodology/approachThe methodology or approach to knowledge valuation is derived from empirical research based on a framework of intangible valuation areas (FIVA). The key valuation components of FIVA are used as the basis for the evolution of an enterprise knowledge valuation system (KVS).FindingsThe findings of the paper are that, fundamental to implementing a KVS is the leveraging of the current enterprise environment, to uncover the intelligence that currently exists so as to make decisions and act on those decisions. This paper presents the first layer of a conceptual model that supports the development of a KVS that leverages the current enterprise environment and integrates existing systems development methods and techniques in its approach to KVS creation and implementation.Originality/valueThe conceptual model – KVS Building Blocks – integrates fundamental types of models with each other to provide a holistic approach to implementing knowledge valuation in an enterprise environment. The first block in the KVS Building Blocks establishes a journey to identifying the data and information enterprise stakeholders need represented in a language they understand, to build a foundation that supports the capability of enterprise stakeholders to value knowledge within their enterprise.

Business intelligence: the management information system next step

Currently, information technology assumes a major role in business, because of it pivotal role in building business intelligence in enterprises. Here we discuss the premises those business intelligence results from the sophistication of a management information system towards the combination of the concept of intelligence and the concept of competitiveness, as organizational tools to give market leadership to enterprises. To do this, we propose and discuss a model to elaborate on business intelligence extended concept. It involves internal and external information to be incorporated as innovation platforms helping enterprises find unique solutions. Competitive intelligence, as gathering, processing and distributing key information to key people, can evolve to business intelligence as an extended concept of business systems effectiveness and strategy. This extended concept comprehends also knowledge management that aligns organizational competencies, building on cognitive bases, to position businesses strategically in the market.