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About 3,081 papers for “data warehouse development”

Data Warehouse Development Methodology

Apress eBooks · 2008

Some people believe they do not need to define the business requirements when building a data warehouse because a data warehouse is built to suit the nature of the data in the organization, not to suit the people. I believe that all IT systems of any kind need to be built to suit the users. A system must be usable. If the system is not used, there is no point in building it. This usability concept is fundamental to this chapter, so keep that in mind.

Cited by 0

Data warehouse development with EPC

Māris Klimavičius · 2006

Abstract:. The Author introduces the approach to address data warehousing issues at the enterprise level. The approach covers data warehouse requirements specification and initial design stages. Author proposes to extend business process model, to cover the main issues connected with development of data warehouses. In this paper Event-Driven Process Chain diagram is extended, a business process modeling language, which has been developed within the framework of ARIS. The Author considers that the use of business process models is necessary, as they reflect both enterprise information systems and business functions, which are important for data analysis. Proposed approach divides development into three steps with different detailed elaboration of models. ARIS framework is used for development of all models. The Described approach gives possibility to gather requirements and display them to business users in easy manner. As examples to demonstrate the approach business processes of the Treasury of the Republic of the Latvia are used within the paper.

Cited by 1

Agile modeling data warehouse development

Couceiro, Frederico da Silva · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2012

Most of the traditional software and database development approaches tend to be serial, not evolutionary and certainly not agile, especially on data-oriented aspects. Most of the more commonly used methodologies are strict, meaning they’re composed by several stages each with very specific associated tasks. A clear example is the Rational Unified Process (RUP), divided into Business Modeling, Requirements, Analysis & Design, Implementation, Testing and Deployment. But what happens when the needs of a well design and structured plan, meet the reality of a small starting company that aims to build an entire user experience solution. Here resource control and time productivity is vital, requirements are in constant change, and so is the product itself. In order to succeed in this environment a highly collaborative and evolutionary development approach is mandatory. The implications of constant changing requirements imply an iterative development process. Project focus is on Data Warehouse development and business modeling. This area is usually a tricky one. Business knowledge is part of the enterprise, how they work, their goals, what is relevant for analyses are internal business processes. Throughout this document it will be explained why Agile Modeling development was chosen. How an iterative and evolutionary methodology, allowed for reasonable planning and documentation while permitting development flexibility, from idea to product. More importantly how it was applied on the development of a Retail Focused Data Warehouse. A productized Data Warehouse built on the knowledge of not one but several client needs. One that aims not just to store usual business areas but create an innovative sets of business metrics by joining them with store environment analysis, converting Business Intelligence into Actionable Business Intelligence.

Cited by 0Open access

Development of Data Warehouse Conceptual Models

Laila Niedrite, Darja Solodovnikova, Liga Grundmane · IGI Global eBooks · 2011

There are many methods in the area of data warehousing to define requirements for the development of the most appropriate conceptual model of a data warehouse. There is no universal consensus about the best method, nor are there accepted standards for the conceptual modeling of data warehouses. Only few conceptual models have formally described methods how to get these models. Therefore, problems arise when in a particular data warehousing project, an appropriate development approach, and a corresponding method for the requirements elicitation, should be chosen and applied. Sometimes it is also necessary not only to use the existing methods, but also to provide new methods that are usable in particular development situations. It is necessary to represent these new methods formally, to ensure the appropriate usage of these methods in similar situations in the future. It is also necessary to define the contingency factors, which describe the situation where the method is usable.This chapter represents the usage of method engineering approach for the development of conceptual models of data warehouses. A set of contingency factors that determine the choice between the usage of an existing method and the necessity to develop a new one is defined. Three case studies are presented. Three new methods: userdriven, data-driven, and goal-driven are developed according to the situation in the particular projects and using the method engineering approach.Request access from your librarian to read this chapter's full text.

Cited by 0

Ensuring Quality In Data Warehouse Development

Jaspreeti Singh · 2008

Abstract- Data warehouses are complex systems that have to deliver highly-aggregated data from heterogeneous sources to decision makers. It is essential that we can assure the quality data warehouse in terms of data as well as the services provided by it. But the requirements and the environment of data warehouse systems is dynamic in nature. To handle these changes efficiently, data warehouses depend largely on the meta databases. In this paper, the proposal is to extend the Goal-Decision-Information approach to model the quality of the data warehouse. In order to fulfill the specific quality goals, dependencies among the various quality factors is exploited in this model.

Cited by 0

Development of Data Warehouse Conceptual Models

Laila Niedrite, Darja Solodovnikova, Liga Grundmane · IGI Global eBooks · 2011

There are many methods in the area of data warehousing to define requirements for the development of the most appropriate conceptual model of a data warehouse. There is no universal consensus about the best method, nor are there accepted standards for the conceptual modeling of data warehouses. Only few conceptual models have formally described methods how to get these models. Therefore, problems arise when in a particular data warehousing project, an appropriate development approach, and a corresponding method for the requirements elicitation, should be chosen and applied. Sometimes it is also necessary not only to use the existing methods, but also to provide new methods that are usable in particular development situations. It is necessary to represent these new methods formally, to ensure the appropriate usage of these methods in similar situations in the future. It is also necessary to define the contingency factors, which describe the situation where the method is usable.This chapter represents the usage of method engineering approach for the development of conceptual models of data warehouses. A set of contingency factors that determine the choice between the usage of an existing method and the necessity to develop a new one is defined. Three case studies are presented. Three new methods: userdriven, data-driven, and goal-driven are developed according to the situation in the particular projects and using the method engineering approach.

Cited by 3

Towards Data Quality into the Data Warehouse Development

Munawar Munawar, Naomie Salim, Roliana Ibrahim · 2011

Commonly, DW development methodologies, paying little attention to the problem of data quality and completeness. One of the common mistakes made during the planning of a data warehousing project is to assume that data quality will be addressed during testing. In addition to the data warehouse development methodologies, we will introduce in this paper a new approach to data warehouse development. This proposal will be based on integration data quality into the whole data warehouse development phase, denoted by: integrated requirement analysis for designing data warehouse (IRADAH). This paper shows that data quality is not only an integrated part of data warehouse project, but will remain a sustained and ongoing activity.

Cited by 18

Contours of a Drug Development Data Warehouse

Paul Vervuren Organon Oss, Frank Dietvorst · 2015

Organon is conducting a data warehouse project that aims to make drug development data more easily and widely available across the R&D organization. Main goal is to enable study data exploration across compounds. Initially, the project will be limited to disclosing clinical data. This paper presents our considerations and solutions for the various warehouse and toolset components, including the data warehouse architecture and software/hardware design. In addition, it discusses the role of CDISC and the possibilities of aligning the data warehouse with the clinical data process

Cited by 0

Development of a data warehouse process model

Osianlis., Anastasios · Monash University · 2021

This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.

Cited by 0Open access

Development of a data warehouse process model

Osianlis., Anastasios · Figshare · 2021

This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.

Cited by 0Open access

Development of a medical informatics data warehouse.

Cai Wu · PubMed · 2006

This project built a medical informatics data warehouse (MedInfo DDW) in an Oracle database to analyze medical information which has been collected through Baylor Family Medicine Clinic (FCM) Logician application. The MedInfo DDW used Star Schema with dimensional model, FCM database as operational data store (ODS); the data from on-line transaction processing (OLTP) were extracted and transferred to a knowledge based data warehouse through SQLLoad, and the patient information was analyzed by using on-line analytic processing (OLAP) in Crystal Report.

Cited by 5Open access

Core Methodologies in Data Warehouse Design and Development

James Yao, John Wang, Qiyang Chen et al. · International Journal of Robotics Applications and Technologies · 2013

Data warehouse is a system which can integrate heterogeneous data sources to support the decision making process. Data warehouse design is a lengthy, time-consuming, and costly process. There has been a high failure in data warehouse development projects. Thus how to design and develop a data warehouse have become important issues for information systems designers and developers. This paper reviews and discusses some of the core data warehouse design and development methodologies in information system development. The paper presents in particular the most recent and much heated hybrid approach which is a combination of data-driven and requirement-driven approaches.

Cited by 0

Early Development of an Enterprise Health Data Warehouse

Mowafa Househ, Majid M. Altuwaijri · Studies in health technology and informatics · 2011

The purpose of this study is to describe early development challenges of an enterprise data warehouse within a Saudi Arabian academic healthcare facility. An action case research method was selected for this paper. The study took place between December 2009 and February 2010. Data collection included interviews, meeting observations, and meeting minutes. Early development challenges centered on the development of clear contracts with vendors; development of a clear project plan; a need to fast-track bureaucracy; and educate clinicians and staff about the project; and lack of data standardization.

Cited by 5

The Development of Data Warehouse for Contractor System

Wimora Sarwindo, Abba Suganda Girsang · International Journal of Engineering and Advanced Technology · 2019

In the middle of the crowded infrastructure of facility and infrastructure while the data of project budget has been increasing every day, PT XYZ requires new technology of data warehouse in order to respond the needs of recording and extracting project budget data quickly and accurately because Ms Excel, recent software used by managing-data staff to store data manually, is fairly time-consuming to record and extract daily realization of project budget. Therefore, in order to help the company to learn the result of the project budgets that have already been spent for the various needs of project construction, the technology of data warehouse should be present in order to extract and record data more consistently and time-saving. Data warehouse technology to support the development of Data Warehouse is Pentaho because Pentaho is database application that is supported with database MYSQL and OLAP feature as a means to analyze and process data contained in multidimensional tables once the process of ETL is executed. ETL means the process of selecting and extracting data from one source into the designated source in order to produce better-quality data result. OLAP is developed by using pivot 4j view integrated by pentaho server to map the structure of fact and dimension table properly so that, the tables can get a proper connection to display desired information in term of graphs for the need of dashboard display. The dashboard that is coded through mdx queries in CDE Dashboard shows the final result of either monthly or yearly project budget obviously and reliably so that the company can learn the report and make decision that needs to be taken to control the budget costs and maintain the company profit. Both CDE Dashboard and pivot 4j view are integrated with pentaho server. Finally, report is presented by using pentaho report designer as a means to extract needed data more rapidly and consistently because data are called through id stored in different table, but the same field.

Cited by 0Open access

A business-oriented approach to data warehouse development

Ania Cravero Leal, José-Norberto Mazón, Juan Trujillo · Ingeniería e Investigación · 2013

Several surveys have indicated that many data warehouses fail to meet business objectives or are outright failures. One reason for this is that requirement engineering is typically overlooked in real projects. This paper addresses data warehouse design from a business perspective by highlighting business strategy analysis, alignment between data warehouse objectives and a firm's strategy, goal-oriented information requirements' modelling and how an underlying multidimensional data warehouse model may be derived. A set of guidelines is provided allowing developers to design a data warehouse aligned with a prevailing business strategy. A classic case study is presented.

Cited by 22Open access