Big Data Management Prototype Development for Analysis Various of Data

The phenomenon of big data is currently agrowing topic in the world of information technology. From someof the literature mentioned that manage big data can createsignificant value for the world economy, improving productivityand competitiveness of enterprises and the public sector as wellas creating a large economic surplus for consumers. However,from some of the information obtained, big data is still not widelyapplied in the company or organization. This study aimed toexplore more information about the big data and proceed withmaking an application prototype big data management. Toexperiment with big data storage that is database, this researchuse NoSQL database technology that can map the needs of bothstructured and unstructured. And this research will be carriedout migration of Relational Database (RDBMS) into the databaseMongoDB. Prototype will be create with the object of study isstructured and unstructured data. The expected result of thisresearch is a model or prototype of big data management thatcan help organizations and companies (especially education) tomake decisions based on various types of data

Big Data Analysis with MongoDB for Decision Support System

The big data is currently a growing topic in the world of information technology. Based on the literature mentioned that manage of big data can create significant value for the world economy, improving productivity and competitiveness of enterprises and the public sector as well as creating a large economic surplus for consumers. However, based on the information obtained, the big data is still not widely applied in the company or organization. This study aimed to explore more information about the big data and proceed with making an application prototype big data management. This experiment established with the big data storage that is database, this research use NoSQL database technology that can map the needs of both structured and unstructured. And this research will be carried out migration of Relational Database (RDBMS) into the database MongoDB.   Prototype will be create with the object of study is structured and unstructured data. The expected result of this research is a model or prototype of big data management that can help organizations and companies (especially education) to make decisions based on various types of data

A systems thinking approach to business intelligence solutions based on cloud computing

Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 73-74).Business intelligence is the set of tools, processes, practices and people that are used to take advantage of information to support decision making in the organizations. Cloud computing is a new paradigm for offering computing resources that work on demand, are scalable and are charged by the time they are used. Organizations can save large amounts of money and effort using this approach. This document identifies the main challenges companies encounter while working on business intelligence applications in the cloud, such as security, availability, performance, integration, regulatory issues, and constraints on network bandwidth. All these challenges are addressed with a systems thinking approach, and several solutions are offered that can be applied according to the organization's needs. An evaluations of the main vendors of cloud computing technology is presented, so that business intelligence developers identify the available tools and companies they can depend on to migrate or build applications in the cloud. It is demonstrated how business intelligence applications can increase their availability with a cloud computing approach, by decreasing the mean time to recovery (handled by the cloud service provider) and increasing the mean time to failure (achieved by the introduction of more redundancy on the hardware). Innovative mechanisms are discussed in order to improve cloud applications, such as private, public and hybrid clouds, column-oriented databases, in-memory databases and the Data Warehouse 2.0 architecture. Finally, it is shown how the project management for a business intelligence application can be facilitated with a cloud computing approach. Design structure matrices are dramatically simplified by avoiding unnecessary iterations while sizing, validating, and testing hardware and software resources.by Eumir P. Reyes.S.M.in System Design and Managemen

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Exploring the potential of big data on the health care delivery value chain (CDVC): a preliminary literature and research agenda

Big data analytics (BDA) is emerging as a game changer in healthcare. While the practitioner literature has been speculating on the high potential of BDA in transforming the healthcare sector, few rigorous empirical studies have been conducted by scholars to assess the real potential of BDA. Drawing on the health care delivery value chain (CDVC) and an extensive literature review, this exploratory study aims to discuss current peer-reviewed articles dealing with BDA across the CDVC and discuss future research directions

Big Data

Η εργασία στοχεύει στην ανάλυση της αγοράς των μεγάλων δεδομένων, Περιλαμβάνονται οι πάροχοι μαζί με κάποιες ενδιαφέρουσες περιπτώσεις χρήσης.Nowadays, term big data, draws a lot of attention, both for Business and person perspective. For decades, companies have been making business decisions through its Business Intelligence department, based on transactional data which were basically stored in relational databases. However, regulatory compliance, increased competition, and other pressures have created an insatiable need for companies to accumulate and analyze large, fast-growing quantities of data that was beyond the critical data

Towards the Implementation of an Intelligent ERP System: Guidelines for Building Intelligent ERP Systems

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe digital age has forced companies to change the way they operate their businesses and adapt quickly to the digital transformation driven by increased global competitiveness in recent years. To remain competitive, organizations must implement management solutions that allow them to efficiently control all business areas through an Enterprise Resource Planning (ERP) system. Management systems have had to evolve to keep up with technological advancements by incorporating intelligent tools. As a result, ERP companies have created new systems known as intelligent ERP (i-ERP). Given the variety of improvement opportunities, it has become necessary to develop a series of guidelines for i-ERP manufacturing as well as for companies that want to implement intelligent solutions in their different business areas, in order to assist technical and non-technical people selecting the best existing option. A design science research (DSR) methodology was used to accomplish the study's goal. It was mandatory to start by defining what an i-ERP system is. Furthermore, their seven capabilities have been clarified, such as intelligent behaviour, learning management, advanced analytics, process automation, intelligent interfaces, dark analytics, and simplification of customization. These capabilities are based on technologies such as artificial intelligence, machine learning, big data, and cloud computing. The guidelines were based on these seven capabilities and were applied to the four major modules of an ERP, which are financial, purchasing, sales, and human resources. As a result, it was possible to create a table with recommendations in general by i-ERP capabilities, followed by guidelines focusing on the financial, purchasing, sales, and human resources areas, and an assessment tool that allowed creating measures to evaluate an ERP system, considering its level of intelligence based on the recommendations created. Finally, the evaluation system was used to rate the latest system developed by SAP SE, SAP S4/HANA, demonstrating its usefulness, followed by expert interviews to validate the recommendations for the four areas identified in terms of their use and acceptance. The relevant literature review and my personal work experience were used as the basis for this master's thesis. It is expected that this study will contribute to the scientific community's understanding of intelligent information systems as well as arouse curiosity in future studies.A era digital forçou as empresas a mudarem a forma como operam os seus negócios e a adaptarem-se rapidamente à transformação digital impulsionada pelo aumento da competitividade global nos últimos anos. Para se manterem competitivas, as organizações devem implementar soluções de gestão que lhes permitam controlar eficazmente todas as áreas de negócio através de um sistema de planeamento de recursos corporativos (ERP). Os sistemas de gestão tiveram de evoluir para acompanhar os avanços tecnológicos, incorporando ferramentas inteligentes. Como resultado, as empresas de sistemas ERP criaram produtos conhecidos como ERP inteligentes (i-ERP). Dada a variedade de oportunidades de melhoria, tornou-se necessário desenvolver uma série de orientações para fabricantes de i-ERP bem como para empresas que pretendam implementar soluções inteligentes nas diversas áreas de negócio, a fim de ajudar as pessoas técnicas e não técnicas na seleção da melhor opção existente. Uma metodologia de desenho de investigação científica (DSR) foi utilizada para atingir o objetivo do estudo. Foi obrigatório começar por definir o que é um sistema i-ERP bem como as suas sete capacidades identificadas, como ter um comportamento inteligente, gestão da aprendizagem, análise avançada, automatização de processos, interfaces inteligentes, análise escura, e simplificação da personalização, que têm como base tecnologias como inteligência artificial, aprendizagem de máquinas, grandes dados e armazenamento em nuvem. As orientações utilizaram como base estas sete capacidades e foram aplicadas aos quatro principais módulos de um ERP, que são o financeiro, compras, logística e recursos humanos. Como resultado foi possível criar uma tabela de recomendações gerais por capacidades de um i-ERP, seguida de recomendações com foco na área financeira, compras, logística e recursos humanos e por último uma ferramenta de avaliação que permitiu criar medidas para avaliar um sistema ERP, considerando o seu nível de inteligência com base nas recomendações criadas. Por último, o sistema de avaliação foi utilizado para classificar o mais recente sistema desenvolvido pela SAP SE, o SAP S4/HANA, demonstrando a sua utilidade, seguido de entrevistas a especialistas para validar as recomendações para as quatro áreas identificadas em termos de respetiva utilização e aceitação. Uma relevante revisão bibliográfica e a minha experiência profissional foram utilizadas como base para esta tese de mestrado. Espera-se que este estudo contribua para a compreensão dos sistemas de informação inteligentes pela comunidade científica, assim como despertar curiosidade em estudos futuros

Analyzing and Developing Technique for Mining Very Large Databases to Support Knowledge Exploration

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