A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

The Role of Maintenance and Facility Management in Logistics: A Literature Review

Purpose - The purpose of this paper is to provide a literature review on the different ways of carrying out Facility Management and related topics in order to uncover that there is limited research regarding the impact of Facility Management on the logistics and operational performance of warehouses. Design/methodology/approach - Four different focus areas have been identified and for each one different methodologies and streams of research have been studied. Findings - The study underlines the importance of Facility Management for the logistics operations; therefore it supports the notion that investments aiming at preserving the status of the building and service components of warehouses are crucial. Originality/value - This paper aims to suggest to Facility Management managers that they can contribute to enhance business performance by designing effective Facility Management strategie

Supply chain management implementation in the Spanish grocery sector: An exploratory study

This paper explores the integration process that firms follow to implement Supply Chain Management (SCM) and the main barriers and benefits related to this strategy. This study has been inspired in the SCM literature, especially in the logistics integration model by Stevens [1]. Due to the exploratory nature of this paper and the need to obtain an in depth knowledge of the SCM development in the Spanish grocery sector, we used the case study methodology. A multiple case study analysis based on interviews with leading manufacturers and retailers was conducted. The results of this analysis suggest that firms seem to follow the integration process proposed by Stevens, integrating internally first, and then, extending this integration to other supply chain members. The cases also show that Spanish manufacturers, in general, seem to have a higher level of SCM development than Spanish retailers. Regarding the benefits that SCM can bring, most of the companies identify the general objectives of cost and stock reductions and service improvements. However, with respect to the barriers found in its implementation, retailers and manufacturers are not coincident: manufacturers seem to see more barriers with respect to aspects related to the other party, such as distrust and a lack of culture of sharing information, while retailers find as main barriers the need of a “know-how”, the company culture and the history and habits.Supply chain management, grocery sector, logistics integration process

Evaluation Real-Time Data Warehousing Challenges From A Theoretical And Practical Perspective

The concept of real-time data warehousing has grown in popularity in recent years as organizations demand access to critical pieces of data in real-time to produce analytics and make business decisions to gain competitive advantage. Real-time data warehousing systems differ substantially from traditional data warehousing systems, thus, presenting a unique set of organizational and operational challenges. The basis for the research was to investigate whether adequate information is available regarding the organizational and operational challenges of real-time data warehousing and whether that information is available to the database community. This exploration was done by gathering primary research, conducting a case study research design, and comparing, analyzing, and drawing conclusions from the two different types of research. The information for the primary research was gathered from scholarly, peer reviewed articles, and books on Google Scholar and ACM, computer science and database journals, various textbooks, and the Internet. The case study was conducted on an organization utilizing a real-time data warehousing system

The necessities for building a model to evaluate Business Intelligence projects- Literature Review

In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, ReadinessComment: International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.2, April 201

Data Warehouse Design and Management: Theory and Practice

The need to store data and information permanently, for their reuse in later stages, is a very relevant problem in the modern world and now affects a large number of people and economic agents. The storage and subsequent use of data can indeed be a valuable source for decision making or to increase commercial activity. The next step to data storage is the efficient and effective use of information, particularly through the Business Intelligence, at whose base is just the implementation of a Data Warehouse. In the present paper we will analyze Data Warehouses with their theoretical models, and illustrate a practical implementation in a specific case study on a pharmaceutical distribution companyData warehouse, database, data model.

Data warehouse automation trick or treat?

Data warehousing systems have been around for 25 years playing a crucial role in collecting data and transforming that data into value, allowing users to make decisions based on informed business facts. It is widely accepted that a data warehouse is a critical component to a data-driven enterprise, and it becomes part of the organisation’s information systems strategy, with a significant impact on the business. However, after 25 years, building a Data Warehouse is still painful, they are too time-consuming, too expensive and too difficult to change after deployment. Data Warehouse Automation appears with the promise to address the limitations of traditional approaches, turning the data warehouse development from a prolonged effort into an agile one, with gains in efficiency and effectiveness in data warehousing processes. So, is Data Warehouse Automation a Trick or Treat? To answer this question, a case study of a data warehousing architecture using a data warehouse automation tool, called WhereScape, was developed. Also, a survey was made to organisations that are using data warehouse automation tools, in order to understand their motivation in the adoption of this kind of tools in their data warehousing systems. Based on the results of the survey and on the case study, automation in the data warehouses building process is necessary to deliver data warehouse systems faster, and a solution to consider when modernize data warehouse architectures as a way to achieve results faster, keeping costs controlled and reduce risk. Data Warehouse Automation definitely may be a Treat.Os sistemas de armazenamento de dados existem há 25 anos, desempenhando um papel crucial na recolha de dados e na transformação desses dados em valor, permitindo que os utilizadores tomem decisões com base em fatos. É amplamente aceite, que um data warehouse é um componente crítico para uma empresa orientada a dados e se torna parte da estratégia de sistemas de informação da organização, com um impacto significativo nos negócios. No entanto, após 25 anos, a construção de um Data Warehouse ainda é uma tarefa penosa, demora muito tempo, é cara e difícil de mudar após a sua conclusão. A automação de Data Warehouse aparece com a promessa de endereçar as limitações das abordagens tradicionais, transformando o desenvolvimento da data warehouse de um esforço prolongado em um esforço ágil, com ganhos de eficiência e eficácia. Será, a automação de Data Warehouse uma doçura ou travessura? Foi desenvolvido um estudo de caso de uma arquitetura de data warehousing usando uma ferramenta de automação, designada WhereScape. Foi também conduzido um questionário a organizações que utilizam ferramentas de automação de data warehouse, para entender sua motivação na adoção deste tipo de ferramentas. Com base nos resultados da pesquisa e no estudo de caso, a automação no processo de construção de data warehouses, é necessária para uma maior agilidade destes sistemas e uma solução a considerar na modernização destas arquiteturas, pois permitem obter resultados mais rapidamente, mantendo os custos controlados e reduzindo o risco. A automação de data warehouse pode bem vir a ser uma “doçura”

Farm SMEs sustainability assessment based on Bellagio Principles. The case of Messinian Region, Greece

Purpose: Sufficient support of the sustainability of farm products embedded in a region (such as Products of Designated Origin / PDOs) to overcome significant obstacles to access domestic and remote markets. Main research question is how to overcome such inherent difficulties and transform them into challenges and opportunities to the new market environment. Design/methodology /approach: Combination of simplicity with the complicated issue of sustainability for awareness of small farmers SMEs and their collective representatives. Improve the understanding of the Sustainable Supply Chain Management (SSCM), to facilitate sustainability through use of the ‘Bellagio Principles’ for assessing sustainability of local farm products and facilitating further enhancement. Use of certain PDOs farm products of the Messinian region of Greece, such as local Sfela Feta cheese, olive oil, olives and raisins, to assess sustainability and improvement. Formation of a conceptual constructive action R&D framework of broader use in building-up and performing implementation of holistic supply chain strategy. Expected Findings: Providing better understanding of the SSCM. Insights on how SMEs co-operatives can collectively apply holistic strategies concerning local farm PDOs to fulfil competitiveness and sustainability requirements, under variant product and market conditions. Originality / Value : Improving the know-how, focusing on the sustainability of regional, traditional products and its effects upon supply chain performance and market access. Practical implications for regional-based farm SMEs in the design of holistic value creation strategies to produce sustainable competitive advantage. Interactive cause and effect dynamic implications of sustainable development on social, economic and physical environment