Data Mining and the Project Management Environment

2010 ◽  
pp. 337-357
Author(s):  
Emanuel Camilleri
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Data Warehouse ◽  
Business Strategy ◽  
Organizational Issues ◽  
Management Concepts ◽  
Public Sector Organizations ◽  
Private And Public ◽  
Four Levels ◽  
Corporate Business

The chapter illustrates how data mining and knowledge management concepts may be applied in a project oriented environment for both the private and public sectors. It identifies the project environment success roadmap that consists of four levels leading to project corporate success. Processes that control the dataflow for generating the projects data warehouse are identified and the projects data warehouse contents are defined. The rest of the chapter shows how data mining may be utilised at each project success level to increase the chances of delivering profitable projects that will have the intended impact on the corporate business strategy. The general conclusion is that there is a need to structure and prioritise information for specific end-user problems and to address a number of organizational issues that may facilitate the application of data mining and knowledge management in a project oriented environment. Finally, the chapter concludes by identifying the issues that need to be addressed by private and public sector organizations so that data mining may be utilised successfully in their decision making process.

An Envisioned Approach for Modeling and Supporting User-Centric Query Activities on Data Warehouses

2013 ◽  
Vol 9 (2) ◽  
pp. 89-109 ◽  
Author(s):  
Marie-Aude Aufaure ◽  
Alfredo Cuzzocrea ◽  
Cécile Favre ◽  
Patrick Marcel ◽  
Rokia Missaoui
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Information Retrieval ◽  
Query Processing ◽  
Data Warehouse ◽  
Multidimensional Data ◽  
Data Warehouses ◽  
Cooperative Query Answering ◽  
User Centric ◽  
Use Of Knowledge

In this vision paper, the authors discuss models and techniques for integrating, processing and querying data, information and knowledge within data warehouses in a user-centric manner. The user-centric emphasis allows us to achieve a number of clear advantages with respect to classical data warehouse architectures, whose most relevant ones are the following: (i) a unified and meaningful representation of multidimensional data and knowledge patterns throughout the data warehouse layers (i.e., loading, storage, metadata, etc); (ii) advanced query mechanisms and guidance that are capable of extracting targeted information and knowledge by means of innovative information retrieval and data mining techniques. Following this main framework, the authors first outline the importance of knowledge representation and management in data warehouses, where knowledge is expressed by existing ontology or patterns discovered from data. Then, the authors propose a user-centric architecture for OLAP query processing, which is the typical applicative interface to data warehouse systems. Finally, the authors propose insights towards cooperative query answering that make use of knowledge management principles and exploit the peculiarities of data warehouses (e.g., multidimensionality, multi-resolution, and so forth).

Implementing process‐oriented knowledge management strategies

2003 ◽  
Vol 7 (4) ◽  
pp. 62-74 ◽  
Author(s):  
Ronald Maier ◽  
Ulrich Remus
Keyword(s):  
Knowledge Management ◽  
Business Strategy ◽  
Management Strategies ◽  
Management Approach ◽  
Km Strategy ◽  
Current State ◽  
State Of Practice ◽  
Process Oriented ◽  
Four Levels ◽  
Strategic Perspective

Despite growing interest about a strategic perspective on knowledge management (KM), there is still a lack of a procedure and methods to guide the implementation of KM strategies. In this paper, we review the current state of practice of KM initiatives and identify four scenarios for potentially successful KM initiatives. The majority of organizations can be described as being a knowledge management starter. In order to improve these KM initiatives and link them to business strategy, we suggest a process‐oriented knowledge management approach as a step to bridge the gap between human‐ and technology‐oriented KM. This approach is outlined with the help of the four levels of intervention: (1) strategy, (2) KM organization and processes, (3) topics/content, and (4) instruments/systems. The definition and implementation of a process‐oriented KM strategy in a large transaction bank will serve as an example to illustrate the application of our approach.

Implementation of data mining as a support of business application strategy

2018 ◽  
Vol 5 (1) ◽  
pp. 47-55
Author(s):  
Florensia Unggul Damayanti
Keyword(s):  
Data Mining ◽  
Random Forest ◽  
Business Strategy ◽  
Input Parameter ◽  
Data Mining Algorithm ◽  
Complex Data ◽  
Business Decision ◽  
Marketing Department ◽  
Business Application ◽  
Complex Data Sets

Data mining help industries create intelligent decision on complex problems. Data mining algorithm can be applied to the data in order to forecasting, identity pattern, make rules and recommendations, analyze the sequence in complex data sets and retrieve fresh insights. Yet, increasing of technology and various techniques among data mining availability data give opportunity to industries to explore and gain valuable information from their data and use the information to support business decision making. This paper implement classification data mining in order to retrieve knowledge in customer databases to support marketing department while planning strategy for predict plan premium. The dataset decompose into conceptual analytic to identify characteristic data that can be used as input parameter of data mining model. Business decision and application is characterized by processing step, processing characteristic and processing outcome (Seng, J.L., Chen T.C. 2010). This paper set up experimental of data mining based on J48 and Random Forest classifiers and put a light on performance evaluation between J48 and random forest in the context of dataset in insurance industries. The experiment result are about classification accuracy and efficiency of J48 and Random Forest , also find out the most attribute that can be used to predict plan premium in context of strategic planning to support business strategy.

Investigating the Personality Variable (LOC) & Impression Management Relationship: Exploring the Role of Demographic Variables & Sectoral Difference of Managers

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Poornima Madan ◽  
Shalini Srivastava
Keyword(s):  
Locus Of Control ◽  
Impression Management ◽  
Demographic Variables ◽  
Personality Variable ◽  
Public Sector Organizations ◽  
Private And Public ◽  
The Difference ◽  
The Relationship ◽  
Test Correlation

The purpose of the study is to investigate the relationship between locus of control and impression management. The study also examines the variation in locus of control dimensions namely, internality, externality (others) and externality (chance). It further investigates the difference on perception of demographic variables (gender and marital status) and sectoral difference on impression management. The study was administered on 125 Managers who were representatives of different private and public sector organizations in Delhi/NCR. Variables in the study were assessed using validated instruments. Descriptive Statistics, t-test, Correlation and Regression were used for data analysis. Organizations will be better prepared to dig into the arena of one of the personality variable, i.e. locus of control and its relationship with impression management. The current research is imperative in providing insights into role of personality variable (locus of control) and impression management, which will be one of the pioneer researches available till date. Moreover, the research will highlight the significance of locus of control dimensions and impression management.

scholarly journals The Effect of Strategic Human Resource and Knowledge Management on Sustainable Competitive Advantages at Jordanian Universities: The Mediating Role of Organizational Innovation

2021 ◽  
Vol 13 (15) ◽  
pp. 8445
Author(s):  
Fieras Alfawaire ◽  
Tarik Atan
Keyword(s):  
Knowledge Management ◽  
Human Resource ◽  
Organizational Innovation ◽  
Strategic Human Resource Management ◽  
Education Sector ◽  
Competitive Advantages ◽  
Convenience Sample ◽  
Mediating Role ◽  
Private And Public ◽  
Sustainable Competitive Advantages

The higher education sector faces considerable competition around the world. Accordingly, universities need to make more efforts to increase their competitive advantages. This study aimed to empirically investigate the effect of organizational innovation (OI), knowledge management (KM), and strategic human resource management (SHRM), with a dependent variable of sustainable competitive advantages (SCAs), at Jordanian Universities. For this aim, a specially designed questionnaire has been distributed to study a convenience sample of 400 academic and administrative staff at Jordanian private and public universities, to obtain the required quantitative data. The study’s hypotheses were verified by Baron and Kenny’s mediation regression approach using the software Statistical Package for the Social Sciences (SPSS). The results of the study demonstrate that there is a significant positive relationship between the following pairs of variables: KM and SCA; SHRM and SCA; SHRM and OI; KM and OI; and OI and SCA, whereas OI was found to have a partial and indirect significant mediation impact on the direct relationship between KM and SHRM and universities (organizations) gaining SCAs. Finally, it was concluded that more attention needs to be paid to the OI aspect in organizations and to integrate it with KM and SHRM in a way that promotes SCAs. In addition, we propose that similar studies should be conducted in industries other than education or the education sector in different countries in a way that obtains generalized and representative results.

Stairways to heaven: implementing social media in organizations

2013 ◽  
Vol 17 (5) ◽  
pp. 741-754 ◽  
Author(s):  
Moria Levy
Keyword(s):  
Social Media ◽  
Knowledge Management ◽  
Empirical Study ◽  
Design Methodology ◽  
Applied Research ◽  
Service Marketing ◽  
Content Type ◽  
Four Levels ◽  
Functional Components ◽  
Practical Implications

Purpose – This paper is aimed at both researchers and organizations. For researchers, it seeks to provide a means for better analyzing the phenomenon of social media implementation in organizations as a knowledge management (KM) enabler. For organizations, it seeks to suggest a step-by-step architecture for practically implementing social media and benefiting from it in terms of KM. Design/methodology/approach – The research is an empirical study. A hypothesis was set; empirical evidence was collected (from 34 organizations). The data were analyzed both quantitatively and qualitatively, thereby forming the basis for the proposed architecture. Findings – Implementing social media in organizations is more than a yes/no question; findings show various levels of implementation in organizations: some implementing at all levels, while others implement only tools, functional components, or even only visibility. Research limitations/implications – Two main themes should be further tested: whether the suggested architecture actually yields faster/eased KM implementation compared to other techniques; and whether it can serve needs beyond the original scope (KM, Israel) as tested in this study (i.e. also for other regions and other needs – service, marketing and sales, etc.). Practical implications – Organizations can use the suggested four levels architecture as a guideline for implementing social media as part of their KM efforts. Originality/value – This paper is original and innovative. Previous studies describe the implementation of social media in terms of yes/no; this research explores the issue as a graded one, where organizations can and do implement social media step-by-step. The paper's value is twofold: it can serve as a foundational study for future researches, which can base their analysis on the suggested architecture of four levels of implementation. It also serves as applied research that will help organizations searching for social media implementation KM enablers.

Study and application of data mining and data warehouse in CIMS

2003 ◽  
Author(s):  
Lijuan Zhou ◽  
Chi Liu ◽  
Daxin Liu
Keyword(s):  
Data Mining ◽  
Data Warehouse
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