Knowledge Management und Business Intelligence

In the modern business day, enterprises have extensive data that has stimulated data variety in many information silos. These activities for extracting valued data from the sources apply Knowledge Management (KM) and Business Intelligence (BI) technologies and applications. The BI frameworks can effectively empower companies to share, analyse also access knowledge and data. Apart from that, KM fundamentally promotes the usage of knowledge and data that is available in the company. In that case, it might be assumed that KM and BI plays a fundamental role in the development of quantitative and qualitative data value which is essential for decision-making. These concepts can benefit from each other and it can be considered that BI plays a fundamental role in KM projects. For instance, BI techniques are applicable in KM for carrying and creating knowledge. The core rationale of this research is to evaluate the interactions, connections and differences between KM and BI. In this analysis, the essential information was taken and collected from different case studies and various literature sources. This procedure is used to compose this research which helps to access accurate data which is essential to mention enterprise management in the modern age. In general, effective agreement results has been witnessed in other scholastic research which states the clear connection of the two concepts and their interaction with each other.

Download Full-text

A Critical Review of Organizing Knowledge Management for Innovation

THE INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND BUSINESS ADMINISTRATION ◽

10.18775/ijmsba.1849-5664-5419.2014.82.1001 ◽

2022 ◽

Vol 8 (2) ◽

pp. 7-15

Author(s):

Asa Romeo Asa ◽

Harold Campbell ◽

Johanna Pangeiko Nautwima

Keyword(s):

Knowledge Management ◽

Competitive Advantage ◽

Diffusion Of Innovation ◽

Business Intelligence ◽

Network Dynamics ◽

Knowledge Networks ◽

External Knowledge ◽

Knowledge Processes ◽

Wide Range ◽

Integrated Knowledge

This study critically reviews the literature that demonstrates the relevance of knowledge management process and business intelligence, as well as the challenges arising when it comes to organising for innovation in today’s business organisations. Hence, the to attain desired innovation it is important to integrate business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Hence, importance of integrating business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Organisations’ innovation dynamics and knowledge processes that lead competitive advantage of organisations are examined. Literature points that many organisations rely on individual employees’ knowledge and skills. As a result, information systems that enable knowledge management (KM) as a critical tool for gaining a competitive advantage (Campbell, 2012). The seminal argument in this study is that knowledge diffusion and knowledge externalities are the main drive of increase in economy. As a result, this is expected to be a win-win value proposition for such organisations integrating business intelligence and knowledge management. However, owing to changing business conditions and the rapidity of technological development, as well as the rising expenses involved with carrying out R&D operations in many of these organisations, maintaining competitive advantage through internal R&D alone is becoming increasingly challenging. The importance of innovation processes and network dynamics in the context of Integrated Knowledge Networks is explored, which provide feasible possibilities for utilising innovation as an interactive process as well as knowledge processes for creating business intelligence in organisations. Due to the challenges of organising for innovation, the organisations figured to rely on “Open innovation” approach to intentionally seek out unique knowledge and information outside of their organisational bounds. This study also discusses the challenges that organisations hurdle on in managing inter-organizational cooperation because of external knowledge sourcing techniques (Campbell, 2009). This is due, in part, to the fact that they span a wide range of organisations, people, and resources, as well as the interactions that exist between them. The creative processes and network dynamics are facilitated by an architecture that blends organisational and technical aspects in Integrated Knowledge Networks. Hence, the study focuses on twofold to sourcing external knowledge in particular: learning from international business environments and corporate venturing strategy for corporate incubators.

Download Full-text

The Role of Data Mining for Business Intelligence in Knowledge Management

Advances in Business Strategy and Competitive Advantage - Integration of Data Mining in Business Intelligence Systems ◽

10.4018/978-1-4666-6477-7.ch002 ◽

2015 ◽

pp. 12-33 ◽

Cited By ~ 65

Author(s):

Kijpokin Kasemsap

Keyword(s):

Data Mining ◽

Knowledge Management ◽

Human Resources ◽

Organizational Performance ◽

Business Intelligence ◽

Statistical Significance ◽

Practical Applications ◽

Business Goals ◽

Emerging Trends

This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining the concept of KM, BI, and DM; the relationships among KM, BI, and DM; the practical applications of KM, BI, and DM; and the emerging trends toward practical results in KM, BI, and DM. In order to solve existing BI problems, this chapter also describes practical applications of KM, BI, and DM (in the fields of marketing, business, manufacturing, and human resources) and the emerging trends in KM, BI, and DM (in terms of larger databases, high dimensionality, over-fitting, evaluation of statistical significance, change of data and knowledge, missing data, relationships among DM fields, understandability of patterns, integration of other DM systems, and users' knowledge and interaction). Applying DM for BI in the KM environments will enhance organizational performance and achieve business goals in the digital age.

Download Full-text

Knowledge Management and Business Analytics

Big Data and Knowledge Sharing in Virtual Organizations - Advances in Knowledge Acquisition, Transfer, and Management ◽

10.4018/978-1-5225-7519-1.ch001 ◽

2019 ◽

pp. 1-42

Author(s):

Nirali Nikhilkumar Honest ◽

Atul Patel

Keyword(s):

Big Data ◽

Knowledge Management ◽

Business Intelligence ◽

Business Performance ◽

Virtual Organization ◽

Data Driven ◽

Business Analytics ◽

Broad Category ◽

Business Operations

Knowledge management (KM) is a systematic way of managing the organization's assets for creating valuable knowledge that can be used across the organization to achieve the organization's success. A broad category of technologies that allows for gathering, storing, accessing, and analyzing data to help business users make better decisions, business intelligence (BI) allows analyzing business performance through data-driven insight. Business analytics applies different methods to gain insight about the business operations and make better fact-based decisions. Big data is data with a huge size. In the chapter, the authors have tried to emphasize the significance of knowledge management, business intelligence, business analytics, and big data to justify the role of them in the existence and development of an organization and handling big data for a virtual organization.

Download Full-text

Big Data, Knowledge, and Business Intelligence

Encyclopedia of Information Science and Technology, Fourth Edition ◽

10.4018/978-1-5225-2255-3.ch081 ◽

2018 ◽

pp. 943-950

Author(s):

G. Scott Erickson ◽

Helen N. Rothberg

Keyword(s):

Big Data ◽

Knowledge Management ◽

Competitive Advantage ◽

Intellectual Capital ◽

Business Intelligence ◽

Competitive Intelligence ◽

Business Analytics ◽

The Past ◽

The People ◽

Tools And Techniques

Knowledge management (KM), intellectual capital (IC), and competitive intelligence are distinct yet related fields that have endured and grown over the past two decades. KM and IC have always differentiated between the terms and concepts of data, information, knowledge, and wisdom/intelligence, suggesting value only comes from the more developed end of the range (knowledge and intelligence). But the advent of big data/business analytics has created new interest in the potential of data and information, by themselves, to create competitive advantage. This new attention provides opportunities for some exchange with more established theory. Big data gives direction for reinvigorating the more mature fields, providing new sources of inputs and new potential for analysis and use. Alternatively, big data/business analytics applications will undoubtedly run into common questions from KM/IC on appropriate tools and techniques for different environments, the best methods for handling the people issues of system adoption and use, and data/intelligence security.

Download Full-text

Knowledge Management to Promote Organizational Change in India

Knowledge Management in Emerging Economies ◽

10.4018/978-1-61692-886-5.ch019 ◽

2010 ◽

pp. 308-324

Author(s):

Juha Kettunen ◽

Manodip Ray Chaudhuri

Keyword(s):

Organizational Change ◽

Knowledge Management ◽

Environmental Change ◽

Change Management ◽

Competitive Advantage ◽

Conceptual Framework ◽

Business Intelligence ◽

General Framework ◽

Strategy Process ◽

Successful Change

This chapter contributes to the literature of knowledge management by providing a conceptual framework to promote organizational change. The chapter demonstrates that knowledge management can be used as a general framework which integrates the approaches of strategic and change management. A business company is an organization that must continually respond to environmental change and adjust to fluctuations to gain competitive advantage. Business intelligence produces tacit and explicit information about the markets that are used in the strategy process. The tools of change management provided in this chapter can be used in different kinds of organisations to increase competitiveness for the future. In addition, this chapter presents cases of successful change management. This chapter is useful for those who want to enhance change to increase competitive advantage of companies and other organisations.

Download Full-text