Implementation Of Data Warehouse Research Articles

Design and analysis on data warehouse of personnel administration system using time series algorithm

The purpose of this study was to design and analysis on data warehouse of personnel administration system using time series. The success of the company in performing its business activities is definitely supported by reliable system administration job. Abundant data within the company; employee information, attendance data, leave the data, the increase in the classroom, increase salaries and allowances requires good management in the order. To assist in the management of personnel data in the study, analysis and design on data warehouse is done in the administration section personnel to facilitate the collection of employee data, monthly and annual reports. The method used in the data warehouse design, data retrieval is done form related sources through extraction, transforming, and loading (ETL) process. After the data warehouse is formed, then conducted data analysis of the presence of the employee with a period of time, either the monthly attendance data analysis as well as using the annual time series algorithm. Process analysis is used to look at trend data is the presence of any employee that can be used to analyze the performance of each employee. This process then continues with the creation of reports on performance of employees which can be used for strategic decisions at the management level. The results obtained from this study showed that the application of data warehouse in staffing information systems conducted to obtain information that can support strategic decisions at the management level. Thus, the design and implementation of data warehouse in power system can help collect data, analyze data, create a report and present the data in a form of employment that can be used to aid strategic decisions at the management level.

Transition Strategies of Change Management For the Succesful Implementation of Data Warehouse of Higher Education in Indonesia

Data Warehouse of Higher Education offers enormous advantages in efficiency, productivity, cost reduction and information integration system. This paper conducted to support success transition of implementation of Data Warehouse of Higher Education in Indonesia (that is called ‘Sistem Pangkalan Data Pendidikan Tinggi or PD-DIKTI in Indonesian) that had been implemented since 2013 ago. However, Data Warehouse of Higher Education implementations are complex, with many encountering difficulty and even failure. Transition of Data Warehouse implementation has been identified as critical success factor. A model that is used to manage the transition of Data Warehouse of Higher Education is Bridge’s Model, where this model is included to top ten leading transition for managing change in the world. The paper is going to summerize the results of a selected relevant articles both of the success implementation new IT technology and how to handle resistance to make transition hoped. In addition, we need to look at the transition models. The paper is hopefully able in changing the better equipped management to get satisfactory decision for all involved in implementing new IT system. This paper also conducted with Action research to get the information trusted.

Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer.

Background:Electronic health record (EHR) based research in oncology can be limited by missing data and a lack of structured data elements. Clinical research data warehouses for specific cancer types can enable the creation of more robust research cohorts.Methods:We linked data from the Stanford University EHR with the Stanford Cancer Institute Research Database (SCIRDB) and the California Cancer Registry (CCR) to create a research data warehouse for prostate cancer. The database was supplemented with information from clinical trials, natural language processing of clinical notes and surveys on patient-reported outcomes.Results:11,898 unique prostate cancer patients were identified in the Stanford EHR, of which 3,936 were matched to the Stanford cancer registry and 6153 in the CCR. 7158 patients with EHR data and at least one of SCIRDB and CCR data were initially included in the warehouse.Conclusions:A disease-specific clinical research data warehouse combining multiple data sources can facilitate secondary data use and enhance observational research in oncology.

An automatic transition from the design to the implementation of a spatial data warehouse

Existing approaches for the design and implementation of spatial data warehouses have not considered spatial and non-spatial decision maker's requirements. In this paper, we propose an approach based on the model driven architecture to transit automatically from the design of the spatial data warehouse to its implementation. The implementation takes into account spatial and non-spatial requirements. We use the formalism of the platform independent model to design the spatial data warehouse and the platform specific model for the implementation. An experimentation of the different steps of our approach is presented. The case study is about five users in urban governance field. The experimentation allowed to generate a personalised spatial data warehouse for a group of users sharing similar spatial requirements. The experimentation is evaluated by the use of the diffusion theory.

An automatic transition from the design to the implementation of a spatial data warehouse

An automatic transition from the design to the implementation of a spatial data warehouse

Data warehouse Implementation on Denpasar City Online Community Complaints System

Department of Communications and Informatics, appointed as Executor of Handling Complaint Society in Denpasar City. Over time and more complex data complaints that come in so complicate the data analysis, to overcome the data it is necessary implementation of data warehouse. The method used is Snowflake Schema, this method is chosen because this method is the development of star schema where each dimension table can have sub-table dimension. It aims to minimize data overload. From the results of the implementation in get the conclusion that by implementing data warehouse can facilitate the user in view report in accordance with the desired from summary to detail.

Using Health Information Technology and Data to Improve Chronic Disease Outcomes in Federally Qualified Health Centers in Maryland.

Federally Qualified Health Centers provide health care services to underserved communities and vulnerable populations. In Maryland, the burden of chronic disease is high among Federally Qualified Health Center patients. Electronic health records (EHRs) are becoming more widely used, and effective use of EHR data may improve chronic disease outcomes. This article describes the process of developing a data aggregation and analytics platform to support health centers in using population health data based on standardized clinical quality measures. This data warehouse, capable of aggregating EHR data across multiple health centers, provides opportunities for benchmarking and elicits a discussion of quality improvement, including identifying and sharing clinical best practices. Phase 1 of the project involved the strategic engagement of health center leadership and staff to get buy-in and to assess readiness. Phase 2 established the technological infrastructure and processes to support data warehouse implementation and began the process of information sharing and collaboration among 4 early adopters. Phase 3 will expand the project to additional health centers and continue quality improvement efforts. The health information technology marketplace is rapidly changing, and staying current will be a priority so that the data warehouse remains a useful quality improvement tool that continues to meet the demands of Maryland health centers. Ongoing efforts will also focus on ways to further add value to the system, such as incorporating new metrics to better inform health center decision making and allocation of resources. The data warehouse can inform and transform the quality of health care delivered to Maryland’s most vulnerable populations, and future research should focus on the ability of health centers to translate this potential into actual improvements.

An empirical study of data warehouse implementation effectiveness

A data warehouse implementation involves a huge financial undertaking on the part of a business organization. Business organizations maintain an enterprise data warehouse to get access to the most accurate and up-to-date information concerning their business. That information needs to be available at the right time to enable organizations to make strategic business decisions. This article discusses the findings of an empirical study of data warehouse implementation effectiveness. The motivation behind conducting this study was to identify the variables that are influential. In this study eight variables were taken as predictive variables and four as response variables. The findings of the study show that certain variables have a significant influence on the response variables for data warehousing success. IT professionals, academicians and researchers might find these findings beneficial.

Automatic Transformation of Data Warehouse Schema to NoSQL Data Base: Comparative Study

Driven by the ever-growing of data from social network (SN), data warehouse (DW) approaches must be adapted. Generally the star, snowflake or constellation models are used as logical ones. All these models are inadequate when dealing with social data which need scalable and flexible systems. As an alternative, NoSQL systems begin to grow.In the absence of a clear approach which allows the implementation of data warehouse under NoSQL model, we propose in this paper, new rules for transforming a multidimensional conceptual model into two NoSQL ones: column-oriented and documentoriented models. For each model, we distinguish two types of transformation: simple and hierarchical. To validate our transformation rules, we implemented four data warehouses using Cassandra as a column-oriented NoSQL system and MongoDB as document-oriented NoSQL system. These systems were implemented using java routines in Talend Data Integration tool and evaluated in terms of “Write Request Latency” and “Read request Latency” using TPC-DS benchmark.

Application of Data Warehouse in Real Life: State-of-the-art Survey from User Preferences’ Perspective

In recent years, due to increase in data complexity and manageability issues, data warehousing has attracted a great deal of interest in real life applications especially in business, finance, healthcare and industries. As the importance of retrieving the information from knowledge-base cannot be denied, data warehousing is all about making the information available for decision making. Data warehouse is accepted as the heart of the latest decision support systems. Due to the eagerness of data warehouse in real life, the need for the design and implementation of data warehouse in different applications is becoming crucial. Information from operational data sources are integrated by data warehousing into a central repository to start the process of analysis and mining of integrated information and primarily used in strategic decision making by means of online analytical processing techniques (OLAP). Despite the applications of data warehousing techniques in number of areas, there is no comprehensive literature review for it. This survey paper is an effort to present the applications of data warehouse in real life. It focuses to help the scholars knowing the analysis of data warehouse applications in number of domains. This survey provides applications, case studies and analysis of data warehouse used in various domains based on user preferences.

Factors Affecting The Successful Implementation Of Data Warehouse

Factors Affecting The Successful Implementation Of Data Warehouse

Challenges in the Successful Implementation of Data Warehouse

Data warehouse refers to a database that gathers and stores data from various remote and heterogeneous sources of information. It is an Information System (IS) that extracts knowledge from the operational data stores of the business. It also provides information concerning suppliers, customers, markets and financial outcome. The present study provides an overview of data warehouse, a description of general data warehouse development process and highlights data warehouse challenges. The study also presents data warehouse success.

User Requirement Analysis in Data Warehouse Design: A Review

Abstract User requirement analysis is crucial in data warehouse design. It effects almost every decision throughout implementation of data warehouse or business intelligence system. Currently, there are no standardization of user requirement analysis approaches had been outlined and this leads to complexity in data warehouse design. Various requirement analysis approaches have been proposed. However, data warehouse designer unable to choose which approach most suitable to be adapted in their project. This paper review various user requirement analysis approaches that been classified into four categories; data-driven approach, user driven approach, goal driven approach and mixed driven approach. It also outlines their strengths and weaknesses within different contexts. The review enables readers to identify appropriate user requirement analysis approach suitable for their projects.

“The Need for World Class Documentation, Data and Record Centres in Universities”

The primary purpose of this paper is - To discuss the current state of Data Management in Universities & To Suggest the ways in which Universities can manage their Data in a more effective & Efficient way rather than the conventional methods. This paper deals with the Concepts of Record Centre, Data Centre, Data Warehouse, Data warehouse in University setup & Steps in the Implementation of Data warehouse in universities. This paper also deals with the Challenges faced by Universities especially, Indian Universities in handling Data & Records & Suggests ways to deal with the problems of not only present but in the future too.This paper further deals with the Methods of Digitization of Documents and Records in the university setup.

CA3-04: Repurposing the Virtual Data Warehouse as a Reporting Tool

Background/Aims The creation and implementation of a research Virtual Data Warehouse (VDW) has shown demonstrable benefits for healthcare researchers. However, the VDW’s potential may be diminished to the extent its accessibility is limited outside of the research sphere. The most obvious limitation is in cases where VDW data can only be accessed via statistical software packages (such as SAS) or the use of Structured Query Language (SQL). This may inhibit access to data by interested, authorized parties who lack training in those computer languages. The potential exists for a research site to leverage the VDW into a more open and accessible reporting system, provided that its implementation meets the following criteria: its data is hosted on a relational database management system (RDBMS); its design schema reasonably well adheres to the principles of data normalization; the site implementing the VDW has access to a standardized library of medical terminology that can be used to validate data and display it in a hierarchical manner. The aim is to leverage the existing VDW data model to produce a flexible and easily accessible reporting system.

Desain Data Warehouse pada Sistem Informasi Sumber Daya Manusia Sub-Sistem Rekrutmen

Employees as a resource management are essential to improve the effectiveness of company’s performance and process efficiency. This paper discusses the implementation of data warehouse and its role in assisting the decision making related to recruitment activities undertaken by Human Resources Department. In this research built a data warehouse design to store large amounts of data and to gain potentially a new perspective of data distribution as well as to provide reports and solutions for users the ad hoc question and to analyze the transactional data. This study aims to design a data warehouse to support accurate decision making related to human resource management in order to create high performance productivity. The method used in this paper consists of: (1) data collection using interview and literature study related to employee recruitment and (2) data warehouse design derived from Teh Ying Wah et al. This research results in a data warehouse design and its implementation to analyze transactional data from the related activities of recruitment and employee management to support decision making.

The Design and Implementation of Monitoring Data Warehouse of Ambient Air Quality

This paper provides the schemata and arithmetic of the city ambient air quality monitoring data warehouse. And describes the Modeling Theory and Method for Constructing Fact Table of Data Warehouse,;At last The implementation of the CAQMADW prototype validates the feasibility of domain data model

Configuring and executing etl tasks on grid environments - requirements and specificities

Data Warehouses store integrated and consistent data in a subject-oriented data repository dedicated especially to support business intelligence processes. Nevertheless, in order to maintain a data warehouse up-to-date, data intensive tasks retrieve regularly specialized information from specific preselected information sources, transforming and conforming it accordingly to some specific business requirements provided by decision-makers. Such tasks, commonly named as Extract-Transform-Load (ETL) processes, have a limited time frame window to be executed over an ever increasing amount of data with extremely complex operations. The common approach to deal with the need of more computational power is the acquisition of new and more powerful hardware. This expensive approach disregards the unused computational resources available in desktop computers already present at most enterprises’ computational environments. This paper intends to define a different approach to deal with ETL processes, taking advantage of parallel processing over a GRID environment using XML data as an effective support to data storage and communication, demonstrating that GRID environments could be a real alternative for the implementation of low cost data warehouses.

An ETL Metadata Model for Data Warehousing

Metadata is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A metadata model is important to the implementation of a data warehouse, the lack of a metadata model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent metadata. This article proposes adoption of an ETL (extracttransform-load) metadata model for the data warehouse that makes subject area refreshes metadata-driven, loads observation timestamps and other useful parameters, and minimizes consumption of database systems resources. The ETL metadata model provides developers with a set of ETL development tools and delivers a user-friendly batch cycle refresh monitoring tool for the production support team.

A practical application of our MDD approach for modeling secure XML data warehouses

Data warehouses are systems that provide useful information to support the decision making process, thus improving organizations' business processes. These systems integrate heterogeneous sources which are not only limited to their internal business data but also include data from the Web, the latter of which have become increasingly more important in the decision making process in recent years. This has motivated the extensive use of XML in the implementation of data warehouses, in a manner which facilitates data and metadata interchange among the heterogeneous data sources from the Web and the data warehouse. However, the business information that data warehouses manage is crucial and highly sensitive, and must be carefully protected. Security is thus a key issue in the design of data warehouses, regardless of the implementation technology used. It is important to note that the data available on the Web requires particular security considerations which have been specifically tailored to these systems in order to permit their particularities to be captured correctly. Unfortunately, although security issues have been considered in the development of traditional data warehouses, current research lacks approaches with which to consider security when the target platform is based on XML technology.In order to deal with this situation, in this paper we propose a methodological approach for the model driven development of secure XML data warehouses. We also specify a set of transformation rules that are able to automatically generate not only the corresponding XML structure of the data warehouse from secure conceptual data warehouse models, but also the security rules specified within the data warehouse XML structure, thus allowing both aspects to be implemented simultaneously. We additionally introduce our secure XML DW development approach, in which the secure conceptual DW data model, the PIM, is transformed into a secure XML DW, as a PSM, by applying a set of transformation rules. Our proposal is validated through the practical application of our model driven development approach for Modeling Secure XML Data Warehouses to a case study, which is based on a central Airport DW. We first describe the transformation rules defined, then use a step by step illustration to show how they will be applied to the secure conceptual model of the case study to obtain the Secure XML Data Warehouse, thus demonstrating the benefits of our proposal, and finally we analyze how to achieve the secure implementation into commercial database management systems, providing details of the secure implementation in Oracle XML DB 11g.