Middleware-based Database Replication: The Gaps between Theory and Practice

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200

ERP implementation for an administrative agency as a corporative frontend and an e-commerce smartphone app

This document contains all the descriptions, arguments and demonstrations of the researches, analysis, reasoning, designs and tasks performed to achieve the requirement to technologically evolve an managing agency in a way that, through a solution that requires a reduced investment, makes possible to arrange a business management tool with e-commerce and also a mobile application that allows access and consultation of mentioned tool. The first part of the document describes the scenario in order to contextualize the project and introduces ERP (Enterprise Resources Planning). In the second part, a deep research of ERP market products is carried out, identifying the strengths and weaknesses of each one of the products in order to finish with the choice of the most suitable product for the scenario proposed in the project. A third part of the document describes the installation process of the selected product carried out based on the use of Dockers, as well as the configurations and customizations that they make on the selected ERP. A description of the installation and configuration of additional modules is also made, necessary to achieve the agreed scope of the project. In a fourth part of the thesis, the process of creating an iOS and Android App that connects to the selected ERP database is described. The process begins with the design of the App. Once designed, it is explained the process of study and documentation of technologies to choose the technology stack that allows making an application robust and contemporary without use of licensing. After choosing the technologies to use there are explained the dependencies and needs to install runtime enviornments prior to the start of coding. Later, it describes how the code of the App has been raised and developed. The compilation and verification mechanisms are indicated in continuation. And finally, it is showed the result of the development of the App once distributed. Finally, a chapter for the conclusions analyzes the difficulties encountered during the project and the achievements, analyzing what has been learned during the development of this project

Comparative Study Of Implementing The On-Premises and Cloud Business Intelligence On Business Problems In a Multi-National Software Development Company

Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceNowadays every enterprise wants to be competitive. In the last decade, the data volumes are increased dramatically. As each year data in the market increases, the ability to extract, analyze and manage the data become the backbone condition for the organization to be competitive. In this condition, organizations need to adapt their technologies to the new business reality in order to be competitive and provide new solutions that meet new requests. Business Intelligence by the main definition is the ability to extract analyze and manage the data through which an organization gain a competitive advantage. Before using this approach, it’s important to decide on which computing system it will base on, considering the volume of data, business context of the organization and technologies requirements of the market. In the last 10 years, the popularity of cloud computing increased and divided the computing Systems into On-Premises and cloud. The cloud benefits are based on providing scalability, availability and fewer costs. On another hand, traditional On-Premises provides independence of software configuration, control over data and high security. The final decision as to which computing paradigm to follow in the organization it’s not an easy task as well as depends on the business context of the organization, and the characteristics of the performance of the current On-Premises systems in business processes. In this case, Business Intelligence functions and requires in-depth analysis in order to understand if cloud computing technologies could better perform in those processes than traditional systems. The objective of this internship is to conduct a comparative study between 2 computing systems in Business Intelligence routine functions. The study will compare the On-Premises Business Intelligence Based on Oracle Architecture with Cloud Business Intelligence based on Google Cloud Services. A comparative study will be conducted through participation in activities and projects in the Business Intelligence department, of a company that develops software digital solutions to serve the telecommunications market for 12 months, as an internship student in the 2nd year of a master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence at Nova Information Management School (NOVA IMS)

Pure Base Training Centre Management Information System With Semantic Web

This paper involved with the development of web based Management Information System which applies to Pure Base Training Centre management system by using Java technology with Semantic Web approach. The objective of this research is to develop Management Information System application integrates with Semantic Web technology. It is to enable proper data and information management and to provide quick data access. This will be a tool for system managers to work in offices and physical workspace. Application areas include J2EE application as applied to view, report, record, and access appropriate data using information technology which involving transfer of digital data between authorized members and management. This proposed technology hopefully will be useful as well as initial step towards changes in a new alternative technology in the future

Grifon: a graphical interface to an object oriented database

The aim of the research outlined in this thesis is to establish what type of interface would be most suitable for object oriented databases. In particular it examines how graphical interface technologies might be used to present the database in a clearer form. In support of the research, a prototype interface system has also been developed to a commercial database to illustrate the practicality of the development of such an interface, and the increased effectiveness of the resultant system. The thesis outlines the features provided by the interface, the benefits accrued from such a system, and the problems associated with its development. Finally, it examines how such a system fits into the current work being carried out in the area of user interaction with databases

Predicting Post-Procedural Complications Using Neural Networks on MIMIC-III Data

The primary focus of this paper is the creation of a Machine Learning based algorithm for the analysis of large health based data sets. Our input was extracted from MIMIC-III, a large Health Record database of more than 40,000 patients. The main question was to predict if a patient will have complications during certain specified procedures performed in the hospital. These events are denoted by the icd9 code 996 in the individuals\u27 health record. The output of our predictive model is a binary variable which outputs the value 1 if the patient is diagnosed with the specific complication or 0 if the patient is not. Our prediction algorithm is based on a Neural Network architecture, with a 90%-10% training-testing ratio. Our preliminary analysis yielded a prediction accuracy above 80%, outperforming various multi-linear models. A comparative analysis of various optimizers as well as time based performance measures is also included