Implementing data-driven decision support system based on independent educational data mart

Decision makers in the educational field always seek new technologies and tools, which provide solid, fast answers that can support decision-making process. They need a platform that utilize the students’ academic data and turn them into knowledge to make the right strategic decisions. In this paper, a roadmap for implementing a data driven decision support system (DSS) is presented based on an educational data mart. The independent data mart is implemented on the students’ degrees in 8 subjects in a private school (Al-Iskandaria Primary School in Basrah province, Iraq). The DSS implementation roadmap is started from pre-processing paper-based data source and ended with providing three categories of online analytical processing (OLAP) queries (multidimensional OLAP, desktop OLAP and web OLAP). Key performance indicator (KPI) is implemented as an essential part of educational DSS to measure school performance. The static evaluation method shows that the proposed DSS follows the privacy, security and performance aspects with no errors after inspecting the DSS knowledge base. The evaluation shows that the data driven DSS based on independent data mart with KPI, OLAP is one of the best platforms to support short-to-long term academic decisions

Yığın Kişiselleştirme Yaklaşımı Ve Örnek Uygulama Mass Customization And Sample Application

Tahmin edilemeyen talep, heterojen müşteri istekleri, kısa ürün yaşam çevrimleri, kaliteli ve kişiselleştirilmiş ürün ve hizmetlere olan talebin artması ve tüm bunları mümkün kılan teknolojik ve inovatif buluşlar işletmeler arası rekabeti üst noktalara taşımıştır. Rekabetin odağında yer alan müşterilerin istek ve ihtiyaçlarının yeterli ve etkin bir biçimde tanımlanarak karşılanabilmesinde yığın kişiselleştirme üretim sistemi 1980’ ler den itibaren hız kazanmıştır. Yığın kişiselleştirme kişilerin istek ve ihtiyaçlarına uygun ürünlerin yığın üretim maliyetlerinde üretilerek sunulmasıdır. Üretim değer zincirinin farklı noktalarında müşteri katılımını öngören yığın kişiselleştirme üretim sistemi farklı seviyelerde ürünün kişiselleştirilebilmesine olanak sağlamaktadır. Dizayn- üretim- montaj ve dağıtım aşamalarının tümüyle müşteriye sunulacak ürünün spesifikasyonlarına göre belirlendiği mutfak üretim sektöründe, yığın kişiselleştirilmiş ürünler maliyet avantajı sağlamaktadır. Bu çalışmanın amacı kişiye özel mutfak üretimi yapan B İşletmesi ile yığın kişiselleştirme üretim yaklaşımı ile modüler mutfak üretimi yapan A İşletmesinin maliyetlerini karşılaştırarak maliyet avantajını ortaya koyabilmektir. Bu doğrultuda iki işletmenin maliyet verileri analiz edilmiş ve yığın kişiselleştirme üretim sistemini kullanan işletmenin ölçek ve kapsam ekonomilerini etkin bir biçimde kullanarak maliyet avantajı elde ettiği görülmüştür. Unpredictable demand, heterogeneous customer requests, short product life cycles, increase in the demand for customized and quality product and services and technological and innovative discoveries that enable all these have boosted the rivalry between enterprises. The role of mass customization system in defining and meeting the requests and necessities of the customers who are the focal point of this rivalry in an efficient and adequate manner has increased since 1980’s. Mass customization means offering products that meet the requirements and the necessities of the customers at mass production costs. Mass customization system which provides for the customer participation at different points of product value chain provides the opportunity to customize products in different levels. In the kitchen production industry where design-production-assembly and distribution stages of the production are completely determined according to the specifications of the product which is going to be presented to the customer, mass customized products provide cost advantages. Aim of this study is to be able to present the cost advantage by comparing the costs of Enterprise B which custom produces kitchens and Enterprise A which produces modular kitchens with mass customization approach. To that end, cost data of the two enterprises analyzed and ıt was seen that the enterprise which uses mass customization production system gains cost advantage by using scale and scope economies efficiently

Requirement modeling for data warehouse using goal-UML approach: the case of health care

Decision makers use Data Warehouse (DW) for performing analysis on business information. DW development is a long term process with high risk of failure and it is difficult to estimate the future requirements for the decision-making. Further, the current DW design does not consider the early and late requirements analysis during its development, especially by using Unified Modeling Language (UML) approach. Due to this problem, it is crucial that current DW modeling approaches covered both early and late requirements analysis in the DW design. A case study was conducted on Malaysia Rural Health Care (MRH) to gather the requirements for DW design. The goal-oriented approach has been used to analyze the early requirements and later was mapped to UML approach to produce a new DW modeling called Goal-UML (G-UML). The proposed approach highlighted the mapping process of DW conceptual schema to a class diagram to produce a complete MRH-DW design. The correctness of the DW design was evaluated using expert reviews. The G-UML method can contribute to the development of DW and be a guideline to the DW developers to produce an improved DW design that meets all the user requirement

Research on conceptual modeling: Themes, topics, and introduction to the special issue

Conceptual modeling continues to evolve as researchers and practitioners reflect on the challenges of modeling and implementing data-intensive problems that appear in business and in science. These challenges of data modeling and representation are well-recognized in contemporary applications of big data, ontologies, and semantics, along with traditional efforts associated with methodologies, tools, and theory development. This introduction contains a review of some current research in conceptual modeling and identifies emerging themes. It also introduces the articles that comprise this special issue of papers from the 32nd International Conference on Conceptual Modeling (ER 2013).This article was supported, in part, by the J. Mack Robinson College of Business at the Georgia State University, the Marriott School of Management at Brigham Young University (EB-201313), and by the GEODAS-BI (TIN2012-37493-C03-03) project from the Spanish Ministry of Education and Competitivity

Design of a Data Warehouse Model for a University Decision Support System

Data Warehouse (DW) can be a valuable asset in providing a stress-free access to data for reporting and analysis. Regrettably, building and preserving an active DW is usually associated with numerous hitches ranging from design to maintenance.  Research in the field of data warehousing has led to the emergence of vital contemporary technologies to aid design, management, and use of information systems that is capable of conveying a Decision Support System (DSS) to organizations. Nevertheless, in the face of persistent achievement and evolution of the field, abundant research is still left unturned across many diverse areas of the data warehousing. The objective of the paper therefore, is to design a DW database model for a University DSS using a dimensional modeling and techniques. A proposed DW database model with specific focus on modeling and design has been realized in this study.  The researchers have demonstrated on how a DW database model can be realized using the dimensional modeling and technique. Keywords: Data Warehouse, Modeling, Decision Support System, Decision Making

Data warehouse schema for monitoring key performance indicators (KPIs) for university teaching and learning using goal oriented approach

The growth and development of universities, just as other organisations, depend on their abilities to strategically plan and implement development blueprints which are in line with their vision and mission statements. The actualizations of these statements –which are often abstracted into goals and sub-goals and linked to their respective actors –are better measured by defined key performance indicators (KPIs). And in universities that handle modestly large and heterogeneous data, development of data warehouse is important. Specifically, Universiti Utara Malaysia (UUM) is yet to have a data warehouse for monitoring its organisational KPIs. This study therefore proposes a data warehouse schema for university’s KPIs for teaching and learning KPIs using a Requirement Goal Analysis for Data Warehouse KPI(ReGADaK)approach which is an extension of goal-oriented requirement analysis and design (GRAnD). The proposed schema highlights the facts, dimensions, attributes and measures of UUM’s teaching and learning unit. The measures from the goal analysis of this unit serve as basis of developing the related university’s KPIs. The proposed data warehouse schema is evaluated through expert review, prototyping and usability evaluation. The findings from the evaluation processes suggest that the proposed data warehouse schema is suitable for university’s KPIs for teaching and learning KPIs monitoring and practicable

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches