Some Issues in Design of Data Warehousing Systems

2001 ◽  
pp. 125-172 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Kamalakar Karlapalem ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Data Warehousing ◽  
Complex Data ◽  
Time Varying ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
On Line ◽  
Analytical Processing ◽  
Warehousing Systems

Information is one of the most valuable assets of an organization, and when used properly can assist intelligent decision-making that can significantly improve the functioning of an organization. Data warehousing is a recent technology that allows information to be easily and efficiently accessed for decision-making activities. On-line analytical processing (OLAP) tools are well studied for complex data analysis. A data warehouse is a set of subject-oriented, integrated, time varying and non-volatile databases used to support the decision-making activities (Inmon, 1992).

Some Issues in Design of Data Warehousing Systems

2011 ◽  
pp. 22-76
Author(s):  
Ladjel Bellatreche ◽  
Kamalakar Karlapalem ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Data Warehousing ◽  
Complex Data ◽  
Time Varying ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
On Line ◽  
Analytical Processing ◽  
Warehousing Systems

Information is one of the most valuable assets of an organization, and when used properly can assist intelligent decision-making that can significantly improve the functioning of an organization. Data warehousing is a recent technology that allows information to be easily and efficiently accessed for decision-making activities. On-line analytical processing (OLAP) tools are well studied for complex data analysis. A data warehouse is a set of subject-oriented, integrated, time varying and non-volatile databases used to support the decision-making activities (Inmon, 1992).

Using OLAP Tools for e-HRM

2011 ◽  
pp. 252-265
Author(s):  
Alysson Bolognesi Prado ◽  
Carmen Freitas ◽  
Thiago Ricardo Sbrici
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Data Warehouse ◽  
End Users ◽  
Web Portal ◽  
Business Information ◽  
On Line ◽  
Analytical Processing ◽  
Resource Data ◽  
Support Decision Making

In the growing challenge of managing people, Human Resources need effective artifacts to support decision making. On Line Analytical Processing is intended to make business information available for managers, and HR departments can now encompass this technology. This paper describes a project in which the authors built a Data Warehouse containing actual Human Resource data. This paper provides data models and shows their use through OLAP software and their presentation to end-users using a web portal. The authors also discuss the progress, and some obstacles of the project, from the IT staff’s viewpoint.

scholarly journals Data Warehouse Schemas using Multidimensional Data Model for Retail

2017 ◽  
Vol 2 (1) ◽  
pp. 84
Author(s):  
Kheri Arionadi Shobirin ◽  
Adi Panca Saputra Iskandar ◽  
Ida Bagus Alit Swamardika
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Data Warehouse ◽  
Data Model ◽  
Transaction Processing ◽  
Multidimensional Data ◽  
Complex Query ◽  
On Line ◽  
Analytical Processing ◽  
Operational Data

A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2011 ◽  
pp. 141-156
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

scholarly journals Biomedical Data Warehouses

2008 ◽  
pp. 149-156 ◽  
Author(s):  
Jérôme Darmont ◽  
Emerson Olivier
Keyword(s):  
Data Warehouse ◽  
Data Warehousing ◽  
Large Data ◽  
Complex Data ◽  
Biomedical Data ◽  
Future Trends ◽  
Data Warehouses ◽  
On Line ◽  
Line Analysis ◽  
Existing Data

In this context, the warehouse measures, though not necessarily numerical, remain the indicators for analysis, and analysis is still performed following different perspectives represented by dimensions. Large data volumes and their dating are other arguments in favor of this approach (Darmont et al., 2003). Data warehousing can also support various types of analysis, such as statistical reporting, on-line analysis (OLAP) and data mining. The aim of this article is to present an overview of the existing data warehouses for biomedical data and to discuss the issues and future trends in biomedical data warehousing. We illustrate this topic by presenting the design of an innovative, complex data warehouse for personal, anticipative medicine.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2008 ◽  
pp. 2964-2977
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

XML Warehousing and OLAP

2011 ◽  
pp. 2109-2116 ◽  
Author(s):  
Hadj Mahboubi
Keyword(s):  
Data Warehouse ◽  
Data Warehousing ◽  
Markup Language ◽  
Future Trends ◽  
Xml Data ◽  
Easy Task ◽  
Extensible Markup ◽  
On Line ◽  
Analytical Processing ◽  
Business Data

With the eXtensible Markup Language (XML) becoming a standard for representing business data (Beyer et al., 2005), a new trend toward XML data warehousing has been emerging for a couple of years, as well as efforts for extending the XQuery language with near On-Line Analytical Processing (OLAP) capabilities (grouping, aggregation, etc.). Though this is not an easy task, these new approaches, techniques and architectures aim at taking specificities of XML into account (e.g., heterogeneous number and order of dimensions or complex measures in facts, ragged dimension hierarchies…) that would be intricate to handle in a relational environment. The aim of this article is to present an overview of the major XML warehousing approaches from the literature, as well as the existing approaches for performing OLAP analyses over XML data (which is termed XML-OLAP or XOLAP; Wang et al., 2005). We also discuss the issues and future trends in this area and illustrate this topic by presenting the design of a unified, XML data warehouse architecture and a set of XOLAP operators expressed in an XML algebra.

Using OLAP Tools for e-HRM

2010 ◽  
Vol 6 (4) ◽  
pp. 49-62 ◽  
Author(s):  
Alysson Bolognesi Prado ◽  
Carmen Freitas ◽  
Thiago Ricardo Sbrici
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Data Warehouse ◽  
Human Resource ◽  
Web Portal ◽  
Business Information ◽  
On Line ◽  
Analytical Processing ◽  
Resource Data ◽  
Support Decision Making

In the growing challenge of managing people, Human Resources need effective artifacts to support decision making. On Line Analytical Processing is intended to make business information available for managers, and HR departments can now encompass this technology. This paper describes a project in which the authors built a Data Warehouse containing actual Human Resource data. This paper provides data models and shows their use through OLAP software and their presentation to end-users using a web portal. The authors also discuss the progress, and some obstacles of the project, from the IT staff’s viewpoint.

scholarly journals IMPLEMENTASI OLAP (ON-LINE ANALYTICAL PROCESSING) UNTUK PENGOLAHAN TRANSAKSI PENJUALAN BERBASIS WEB (STUDI KASUS: LILOLA BOUTIQUE)

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Ni Putu Manik Ardiyanti ◽  
Aniek Suryanti Kusuma ◽  
I Kadek Budi Sandika
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Black Box ◽  
Web Based ◽  
Processing Application ◽  
Sales Data ◽  
Black Box Testing ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

ABSTRACT<br />Information on sales data required by the owner at Lilola Boutique as a basis for decision making and strategy . On the other hand, the large amount of transactional sales data that occurs at any time causes problems in these analyze process. To solve these problem, an OLAP (On-Line Analytical Processing) application was built. OLAP application is designed using the CodeIgniter framework which produces a fast and reliable web-based application and data warehouse as its database. To produce a good data warehouse, the Nine Step Kimball method were used. Stages of this method produced a snowflake scheme as a storage place for data warehouse. The implementation of the system design could produced the OLAP report required by Lilola Boutique. Testing the system using black box testing method that showed the performance of applications that run well. From the results of this study can be concluded that OLAP application made the process of sales transaction data analysis to produce reports as the basis of the decision-making process.<br />Keywords: Sales, OLAP, Data Warehouse, Nine Step Kimball<br />ABSTRAK<br />Informasi mengenai data penjualan dibutuhkan oleh owner pada Lilola Boutique sebagai dasar untuk pengambilan keputusan dan penentuan strategi perusahaan. Di sisi lain, banyaknya data transaksi penjualan yang terjadi setiap harinya menyebabkan kesulitan dalam proses analisa dan pengambilan keputusan. Untuk mengatasi permasalahan tersebut, dibangun sebuah aplikasi OLAP (On-Line Analytical Processing). Perancangan aplikasi OLAP dirancang menggunakan framework CodeIgniter yang menghasilkan aplikasi berbasis web yang handal dan cepat dan data warehouse sebagai basis datanya. Untuk menghasilkan data warehouse yang baik, digunakan metode perancangan Nine Step Kimball. Tahapan metode ini menghasilkan rancangan snowflake schema sebagai tempat penampungan data warehouse. Implementasi rancangan sistem dapat menghasilkan laporan OLAP yang dibutuhkan oleh pihak Lilola Boutique. Pengujian sistem menggunakan metode black box testing yang menghasilkan unjuk kerja aplikasi yang berjalan dengan baik. Dari hasil penelitian ini dapat disimpulkan bahwa sistem aplikasi OLAP dapat membantu proses pengolahan data transaksi penjualan untuk menghasilkan laporan yang berkualitas sebagai dasar dalam pengambilan keputusan.<br />Kata Kunci: Penjualan, OLAP, Data Warehouse, Nine Step Kimball

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