Healthcare Data Analytics on the Cloud

Meaningful analysis of voluminous health information has always been a challenge in most healthcare organizations. Accurate and timely information required by the management to lead a healthcare organization through the challenges found in the industry can be obtained using business intelligence (BI) or business analytics tools. However, these require large capital investments to implement and support the large volumes of data that needs to be analyzed to identify trends. They also require enormous processing power which places pressure on the business resources in addition to the dynamic changes in the digital technology. This paper evaluates the various nuances of business analytics of healthcare hosted on the cloud computing environment. The paper explores BI being offered as Software as a Service (SaaS) solution towards offering meaningful use of information for improving functions in healthcare enterprise. It also attempts to identify the challenges that healthcare enterprises face when making use of a BI SaaS solution

How Regular Business Has Becomes Mobile Business. A Mobile Agent Approach

The age of static business and slow information flow, when most decision was based on day-or week-old data, has come to an end. Now new technology helps organizations provide a more agile, flexible approach to business that was not technologically available five years ago. As a result, organizations are paying more attentions to supporting business process with the ability to adapt to the dynamic environment. This paper describes how the action of mobile agent enabled decision support in conjunction with the organizational trends, enables new practice in the field of e-Business. This is done to understand the magnitude of the e-business context problem and to suggest possible ways around the problem when building mobile agents. Therefore, a mobile agent approach is proposed in this paper to offer solution for mobile business and to manage complex business activities.mobile agent, mobile technologies, mobility, business

ICT Investment and Productivity: A Provincial Perspective

In 2008, Statistics Canada, for the first time, made available estimates of information and communication technology (ICT) investment by province. Given the importance of ICT investment for productivity growth, these data are important for the comparative analysis and understanding of productivity growth by province. The objective of this report is to present the basic data on ICT investment and ICT investment per worker in Canada and the ten provinces over the 1981-2007 period. The first part of the report reviews the literature on why ICT investment is important for productivity. The second part examines ICT investment levels and trends by province. The third part decomposes the gap in ICT investment per worker by province, relative to the national average, into three effects: that related to income levels, to the total investment/GDP share, and to the ICT investment/total investment share.Machinery and equipment investment, information and communications technology, ICT, Investment gap, Business sector, Provincial estimates

SAP HANA Data Volume Management

Today information technology is a data-driven environment. The role of data is to empower business leaders to make decisions based on facts, trends, and statistical numbers. SAP is no exception. In modern days many companies use business suites like SAP on HANA S/4 or ERP or SAP Business Warehouse and other non-SAP applications and run those on HANA databases for faster processing. While HANA is an extremely powerful in-memory database, growing business data has an impact on the overall performance and budget of the organization. This paper presents best practices to reduce the overall data footprint of HANA databases for three use cases like SAP Business Suite on HANA, SAP Business Warehouse, and Native HANA database

Implementation of a business intelligence system in a public institution

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology is capable to support companies to reach their goals by making use data to take advantages from its analysis. Concerning public institutions, it is meaningful to deliver high-quality services and products to society, and technology may lead the organizations to a more efficient service provision. The purpose of this project is the implementation of a business intelligence system in Consultoria Jurídica da União (CJU) [Consultancy Office], the institution responsible for analyzing bidding processes in Brazil. The solution proposed by this work aims to store the business data and provide an analytical tool to display information in dashboards to provide insights to stakeholders, analyzing data trends and tendencies, preventing future unnecessary events, identifying best practices, to finally improve the public tenders to a better application of public funds and provide better services to society. To reach this project main objective, the technology that surrounds the BI system to be implemented includes the development of a scalable data warehouse to store the organization data and its schema modelling, the extraction-transform-load method to populate the data warehouse tables, and create the analytical tool, named dashboard, to answer the business needs providing the institution information. This business intelligence system intends to improve the legal bidding process in public agencies by making use of technology

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.siirretty Doriast

Information Technology and the QS Practice

The paper examines how Quantity Surveying practices can improve their business performance, market share and profit levels by embracing and evolving with the latest technological developments in electronic business practices and data/information analysis and exchange in the construction industry. Firms in the new millenium will need towork smarterto gain competitive advantage and electronic commerce provides probably the greatest scope for this to be achieved. More importantly, current project procurement trends strongly indicate that firms not able to communicating electronically at all levels with project participants will find it increasingly difficult to secure work. The results of three nationwide surveys of the Australian Quantity Surveying profession spanning from 1995 to 1999 are used to identify current business practices and technology utilisation by Quantity Surveying firms and to analyse whether firms are positioning themselves to meet future industryrequirements. The paper concludes with a range of Information Technology strategies aimed at improving business opportunities and performance for Quantity Surveying firms

A critical analysis of the relationship between business information system technology and supply chain management with special reference to optimum efficiency within large enterprises in the food and drug retail sector in KwaZulu-Natal.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.The purpose of this research is to explore the relationship between supply chain management and business information system technology within the food and drug retail sector with special reference to optimum efficiency. Business information system technology leverages information and knowledge sharing throughout the supply chain which enables them to respond more effectively to an ever-changing and volatile marketplace. The relationship between supply chain management and business information system technology is multi-faceted and complex in nature, and consequently, has the ability to penetrate every element of an organisation’s functionality. Furthermore, it has the ability to penetrate the functionality of an entire chain or network of suppliers and markets irrespective of their position around the globe. Supply Chain management literature teaches that optimisation within functional areas is not as effective as cross-optimisation across functions and supply chain networks. As supply chains rely on business information technology for crossoptimisation, optimum efficiency will always be a moving target for as long as business technology and supply chain management continue to break through new ground. In this research large food and drug supply chain networks and their business information system requirements, trends, influence, effect and constraints were reviewed, with special reference to creating optimum efficiency in their supply chain networks. This research was motivated by discussions with Pick ‘n Pay’s business information system’s service provider and their desire to optimise Pick ‘n Pay’s supply chain network efficiency in a highly price-competitive environment, resulting in an in-depth case study being carried out on Pick ‘n Pay (Pty) Ltd stores in KwaZulu-Natal. The review of literature suggests that cross-optimisation is only mutually beneficial within trust relationships that exhibit seamless flows of information throughout a supply chain. Data suggests that despite Pick ‘n Pay’s use of advanced business information system technology, Pick ‘n Pay together with the food and drug retail stores in South Africa have a long way to go on this issue

Business Intelligence Technology, Applications, and Trends

Enterprises are considering substantial investment in Business Intelligence (BI) theories and technologies to maintain their competitive advantages. BI allows massive diverse data collected from virus sources to be transformed into useful information, allowing more effective and efficient production. This paper briefly and broadly explores the business intelligence technology, applications and trends while provides a few stimulating and innovate theories and practices. The authors also explore several contemporary studies related to the future of BI and surrounding fields