scholarly journals Selecting a Business Intelligence Solution that is Fit for Business Requirements

2019 ◽  
Author(s):  
Marko Pribisalić ◽  
◽  
Igor Jugo ◽  
Sanda Martinčić-Ipšić ◽  
◽  
...  
Keyword(s):  
Business Intelligence ◽  
Business Requirements

Agile Development in Data Warehousing

2011 ◽  
Vol 2 (3) ◽  
pp. 64-77 ◽  
Author(s):  
Nayem Rahman ◽  
Dale Rutz ◽  
Shameem Akhter
Keyword(s):  
Business Intelligence ◽  
Data Warehousing ◽  
Agile Development ◽  
Successful Implementation ◽  
Design Development ◽  
Frequent Change ◽  
Development Teams ◽  
Waterfall Model ◽  
Business Requirements ◽  
The Impact

Traditional data warehouse projects follow a waterfall development model in which the project goes through distinct phases such as requirements gathering, design, development, testing, deployment, and stabilization. However, both business requirements and technology are complex in nature and the waterfall model can take six to nine months to fully implement a solution; by then business as well as technology has often changed considerably. The result is disappointed stakeholders and frustrated development teams. Agile development implements projects in an iterative fashion. Also known as the sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in the initial release, with refinements coming in a series of subsequent releases which are scheduled at regular intervals. An agile data warehousing approach greatly increases the likelihood of successful implementation on time and within budget. This article discusses agile development methodologies in data warehousing and business intelligence, implications of the agile methodology, managing changes in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates the impact of agility on the business.

Business Intelligence and Agile Methodology for Risk Management in Knowledge-Based Organizations

2012 ◽  
pp. 240-267
Author(s):  
Muhammad Mazen Almustafa ◽  
Dania Alkhaldi
Keyword(s):  
Risk Management ◽  
Business Intelligence ◽  
Agile Methodology ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
Technology Changes ◽  
Risk Management Process ◽  
Changing Economy ◽  
Business Requirements

In this highly technology - dependent, knowledge- based economy, the causes for failure of most software development projects are related to rapid technology changes, in-flux business requirements, or failure to tackle risk. Accordingly, risk management plays significant and crucial role in organizations’ response to this rapidly changing economy. Risk management process is illustrated in four main steps: identify the risk, analyze the risk, treat the risk and monitor the risk. This chapter discusses and explores the role of business intelligence and agile methodology to manage risk effectively and efficiently. It explores the risk management traditional tools that are commonly used, the role of business intelligence in risk management, and the role of agile methodology in risk management.

Agile Development in Data Warehousing

2012 ◽  
pp. 286-300 ◽  
Author(s):  
Nayem Rahman ◽  
Dale Rutz ◽  
Shameem Akhter
Keyword(s):  
Business Intelligence ◽  
Data Warehousing ◽  
Agile Development ◽  
Successful Implementation ◽  
Design Development ◽  
Frequent Change ◽  
Development Teams ◽  
Agile Approach ◽  
Waterfall Model ◽  
Business Requirements

Traditional data warehouse projects follow a waterfall development model in which the project goes through distinct phases such as requirements gathering, design, development, testing, deployment, and stabilization. However, both business requirements and technology are complex in nature and the waterfall model can take six to nine months to fully implement a solution; by then business as well as technology has often changed considerably. The result is disappointed stakeholders and frustrated development teams. Agile development implements projects in an iterative fashion. Also known as the sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in the initial release, with refinements coming in a series of subsequent releases which are scheduled at regular intervals. An agile data warehousing approach greatly increases the likelihood of successful implementation on time and within budget. This article discusses agile development methodologies in data warehousing and business intelligence, implications of the agile methodology, managing changes in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates the impact of agility on the business.

scholarly journals An IoT Knowledge Reengineering Framework for Semantic Knowledge Analytics for BI-Services

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Nilamadhab Mishra ◽  
Hsien-Tsung Chang ◽  
Chung-Chih Lin
Keyword(s):  
Knowledge Base ◽  
Business Intelligence ◽  
Cost Effective ◽  
Semantic Knowledge ◽  
Base System ◽  
Adequate Knowledge ◽  
Knowledge Base System ◽  
Rapid Changes ◽  
Data Production ◽  
Business Requirements

In a progressive business intelligence (BI) environment, IoT knowledge analytics are becoming an increasingly challenging problem because of rapid changes of knowledge context scenarios along with increasing data production scales with business requirements that ultimately transform a working knowledge base into a superseded state. Such a superseded knowledge base lacks adequate knowledge context scenarios, and the semantics, rules, frames, and ontology contents may not meet the latest requirements of contemporary BI-services. Thus, reengineering a superseded knowledge base into a renovated knowledge base system can yield greater business value and is more cost effective and feasible than standardising a new system for the same purpose. Thus, in this work, we propose an IoT knowledge reengineering framework (IKR framework) for implementation in a neurofuzzy system to build, organise, and reuse knowledge to provide BI-services to the things (man, machines, places, and processes) involved in business through the network of IoT objects. The analysis and discussion show that the IKR framework can be well suited to creating improved anticipation in IoT-driven BI-applications.

Business Intelligence and Agile Methodology for Risk Management in Knowledge-Based Organizations

2014 ◽  
pp. 1710-1735 ◽  
Author(s):  
Muhammad Mazen Almustafa ◽  
Dania Alkhaldi
Keyword(s):  
Risk Management ◽  
Business Intelligence ◽  
Agile Methodology ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
Technology Changes ◽  
Risk Management Process ◽  
Changing Economy ◽  
Business Requirements

In this highly technology - dependent, knowledge- based economy, the causes for failure of most software development projects are related to rapid technology changes, in-flux business requirements, or failure to tackle risk. Accordingly, risk management plays significant and crucial role in organizations’ response to this rapidly changing economy. Risk management process is illustrated in four main steps: identify the risk, analyze the risk, treat the risk and monitor the risk. This chapter discusses and explores the role of business intelligence and agile methodology to manage risk effectively and efficiently. It explores the risk management traditional tools that are commonly used, the role of business intelligence in risk management, and the role of agile methodology in risk management.

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

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