Nayem Rahman

Competitive Strategies in the Computer Industry

A firms competitive behavior is very important for its survival. Relevant stakeholders in an industry are interested in a firms operational as well as financial performance. In order to gain competitive advantage, a firm must remain steadfast during changes it goes through over time. This is true for the computer industry as well. The computer industry has been advancing very fast and firms in the industry are experiencing fierce competition for many reasons. This study examines the computer industry in terms of Michael Porters framework for analyzing the profitability. The authors conduct a critical analysis of the threat of new entrants into the computer industry segment, the bargaining power of suppliers in the industry, the bargaining power of buyers in the industry, the threat of substitute products or services, and rivalry among competitors in the industry. This study has implications for incumbent firms and new entrants into the computer manufacturing industry that evaluate competitive strategies in the industry.

An Empirical Study of Data Warehouse Implementation Effectiveness

Abstract A data warehouse implementation involves a huge financial undertaking on the part of a business organization. Business organizations maintain an enterprise data warehouse to get access to the most accurate and up-to-date information concerning their business. That information needs to be available at the right time to enable organizations to make strategic business decisions. This article discusses the findings of an empirical study of data warehouse implementation effectiveness. The motivation behind conducting this study was to identify the variables that are influential. In this study eight variables were taken as predictive variables and four as response variables. The findings of the study show that certain variables have a significant influence on the response variables for data warehousing success. IT professionals, academicians and researchers might find these findings beneficial.

Building a Customer Inquiry Database System

Organizations invest in customer database software to keep customer data safe and secured. That also allows them to increase operational efficiency of business. In this article, the authors will discuss development of a customer inquiry database system for use by small businesses. The proposed database system is destined to store customer information, inquiries, and company product information. The authors have designed and developed user interfaces UI using the state of the art software development technology and developed business intelligence BI capability using this system. This article provides a holistic view of building a customer inquiry database system. Existing literature or database system books talk about these topics partially as opposed to our approach of an integrated view of customer inquiry system.

Big Data Business Intelligence in Bank Risk Analysis

This paper provides an overview of big data technologies and best practices from the standpoint of business intelligence BI applications in the banking industry. The authors discussed current challenges in banking industry that could be addressed by using big data technologies. Based on their research, they provided a list of big data tools and technologies in terms of an ecosystem that are suitable for real-time data processing and capable in bank fraud detection and prevention, and other bank risk analysis. They highlighted how business intelligence could be leveraged with the help of emerging big data technologies.

A Simulation Model for Application Development in Data Warehouses

Software development projects have been blamed for being behind schedule, cost overruns, and the delivery of poor quality product. This paper presents a simulation model of a data warehouse to evaluate the feasibility of different software development controls and measures to better manage a software development lifecycle, and improve the performance of the launched software. This paper attempts to address the practical issue of code defects in each stage of data warehouse application development. The author has compared the defect removal rate of their previous project to the newly proposed enhanced project development life cycle that uses code inspection and code scorecard along with other phases of software development life cycle. Simulation results show that the code inspection and code score-carding have achieved a significant code defect reduction. This has also significantly improved the software development process and allowed for a flawless production execution. The author proposes this simulation model to a data warehouse application development process to enable developers to improve their current process.

Can Agile, Lean and ITIL Coexist?

Information Technology Infrastructure Library (ITIL) is frequently perceived as overly wordy and bureaucratic while Agile and Lean methodologies are often positioned as a rejection of heavy handed process and governance. But IT Service Management, Agile, and Lean are all focused on the same thing: How to get valuable work done quickly and efficiently in the complex world of IT in order to enable a businesss competitive edge. Delivering IT solutions at the speed-of-business while maintaining quality, performance and availability of the Live Environment is a constant balancing act among simultaneous constraints. ITIL, Agile and Lean all contain best-practices to define and manage these constraints and the contexts in which they exist. The authors will compare and contrast the core of these methodologies to show how they align with the goal of providing a roadmap for successful implementation and coexistence.

A System Dynamics Model for a Sustainable Fish Population

To visualize or address complex real world problems, eliciting and mapping of a mental model is reasonable approach but it is far from sufficient by itself. In this article we present a system dynamics model. The purpose of the model is to develop a sustainable model for fish population, growth, and harvesting. The model was run through several important tests to determine its sensitivity to changing in key parameters and initial values with different scenarios and boundary conditions. Model results show that fish birth, growth, stocks and catch can be controlled quickly in different real-world changing conditions to maintain a sustainable fish population.