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Merchant acquirer is a business of acquiring debit card, credit card, and prepaid card transactions using EDC (electronic payment terminals) in merchants. It is included in one of the top business priority areas in PT. XYZ. It is in the area of retail payments and deposits. It increases fees based incomes, cheap funds, and high yield loans. In order to improve its business performance, PT. XYZ needs...
Online Analytics Processing (OLAP) is utilised to develop multidimensional operations enabling queries and visualisation for Business Intelligence (BI). Most of the OLAP systems come with a tightly integrated user interface for querying and visualisation of data without the core OLAP operations exposed as an API. Advanced BI applications can be developed and composed to create complex workflows if...
Big-data middle layer architecture is defined to perform the query analysis and the evaluation of the Big Data. This scheme is implemented on dynamic generated data section. The concept of Big Data concerns with a bulk of data presented in large volume with complicated architecture and with increasing data set. The data for such system can be taken from multiple sources and sometimes from independent...
Teradata data warehouse technology has been widely used in China, but few studies it. In order to clearly understand the Teradata and its internal mechanisms, the paper studies the basic structure of Teradata data warehouse through analyzing the parallelism characteristic and scalability characteristic of Teradata MPP System. The paper also discusses the solution about construction of the Teradata...
This paper describes the author's concept for universal enterprise platform that allows to benefit from modern approaches to data analysis based on Business Intelligence and Big Data technologies. This idea is based on SOA architecture that enables workflow to coordinate the business processes and communicate domain applications with bespoke Business Intelligence and Big Data Solutions. Whole platform...
Petrology, petrography and ordinary geologic data compose an ever increasing collection of information for post-processing analysis. Geoscientists at Universidad Autónoma de Chihuahua, are consistently working with these data collections for research purposes. Scientists record this information, as well as that obtained in bibliography references, in order to study it and lead to important research...
With the appearance of computer network, could computing, the internet of things, big data more and more get the attention of people. Understanding and Application big data, and make a scientific decision, become the most necessary and urgent problem. Big data, not only let the database have always been known for efficient and secure storage embarrassed, but also allow the data warehouse that provide...
The Small&Medium steel enterprises is relatively weak on information technology, and the information management personnel lack the urgent need for information integration. According to the actual needs of the Small&Medium steel enterprises information management, three-tier architecture of information integration systems is proposed in this paper. By using SQL Server to implement database...
Inspired by the emerging Big Data challenge, in this paper we provide the description of OLAP*, a Cloud based framework for supporting effective and efficient OLAP in Big Data environments. OLAP* combines data warehouse partitioning techniques with Cloud Computing paradigms, and provides a suitable implementation on top of the well-known ROLAP server Mondrian where the main task consists in applying...
This paper will give an overview on the approach to provide an integrated system for consumable yield analysis at GLOBALFOUNDIRES to support rapid new product ramp, technology development and yield excursion analysis. The business drivers for such a system will be reviewed, and insight will be given into the integration components, software architecture, challenges, and the implemented and proposed...
Daniel E. O'Leary examines the notion of the Big Data Lake and contrasts it with decision support-based data warehouses. In addition, some of the risks of the emerging Lake concept that ultimately require data governance are analyzed. O'Leary investigates using different AI and crowdsourcing (human intelligence) applications in that lake in order to integrate disparate data sources, facilitate master...
In a Dimensional Model of Data Warehouse, process of designing conceptual schema based on user requirements face some challenges due to data sources may lack some important elements. One way to improve schema is by utilizing alternative sources of knowledge that act as DW additional data sources. Since past few years, there are several researchers who present the use of Ontology to improve several...
Healthcare environment is growing to include not only the traditional information systems, but also a business intelligence platform. For executive leaders, consultants, and analysts, there is no longer a need to spend hours in design and develop of typical reports or charts, the entire solution can be completed through using Business Intelligence “BI” software. This paper discusses current state-of-the-art...
Extract, Transform and Load (ETL) is a fundamental process used to populate a data warehouse and an important step towards data integration which is a key step for data preprocessing for many data mining projects. The objective of this project is to create a simple web based ETL tool which can be accessed by anyone with internet access. This ETL tool is also supported by a brief on-line tutorial on...
This study explores the architecture of Decision Support System for Tariff and Trade that not only facilitates data analysis and trade forecast by providing an integration of report generation tools, but also enhances the retrieval of information and support decision-making by providing economic quantitative analysis tools and system modeling tools. Based on multi-dimensional modeling techniques of...
Extraction-Transformation-Loading (ETL) plays an important role in data warehouse. Typically, performance is considered the main factor in ETL projects. Actually, faulttolerance and many other aspects influence the results of ETL greatly especially when the time period of projects are long and transformation rules cannot be determined from beginning, such as the situation of changing business logic...
Organizations use the techniques of data warehouse and knowledge discovery in databases to generate useful information to support their strategic decisions. These techniques, if properly combined, can offer a broad knowledge of business domain treaty. This paper proposes the use of ontology to organize and categorize the relevant data from the field of social vulnerability. With the exploration of...
Traditional Chinese Medicine (TCM) has been widely used to treat various diseases like infectious diseases. Treatment Based on Syndrome Differentiation (TBSD) is the main principle in TCM clinical practice. So exploring the relationships between diagnoses and treatments from successful cases is important and valuable for better treating hepatitis diseases, which is a decision support problem based...
To analyze large quantity of information in medication with scientific technique and to provide decision supports for doctors, we set up the research on Adverse Drug Reactions (ADRs) by constructing a multidimensional data warehouse. Adopted SQL Server 2005 business intelligence tools, we extracted, transformed and loaded the data from spontaneous reporting system (SRSs) of ADRs to the data warehouse,...
Although much progress has been made to plan and execute Software Development projects in an agile manner, Data Warehouse or Business Intelligence projects seem to still execute in a more traditional manner. Data Warehouse projects are quite different than Software Development projects and need a set of Agile practices that are distinctly their own. This paper is an account of Data Warehouse redevelopment...
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