Data Warehouse Performance

2011 ◽  
pp. 580-585 ◽  
Author(s):  
Beixin ("Betsy") Lin ◽  
Yu Hong ◽  
Zu-Hsu Lee
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Performance Tuning ◽  
Data Warehouses ◽  
User Query ◽  
Data Volume ◽  
Predictive Data Mining ◽  
Support Decision Making ◽  
Over Time

A data warehouse is a large electronic repository of information that is generated and updated in a structured manner by an enterprise over time to aid business intelligence and to support decision making. Data stored in a data warehouse is non-volatile and time variant and is organized by subjects in a manner to support decision making (Inmon et al., 2001). Data warehousing has been increasingly adopted by enterprises as the backbone technology for business intelligence reporting and query performance has become the key to the successful implementation of data warehouses. According to a survey of 358 businesses on reporting and end-user query tools, conducted by Appfluent Technology, data warehouse performance significantly affects the Return on Investment (ROI) on Business Intelligence (BI) systems and directly impacts the bottom line of the systems (Appfluent Technology, 2002). Even though in some circumstances it is very difficult to measure the benefits of BI projects in terms of ROI or dollar figures, management teams are still eager to have a “single version of the truth,” better information for strategic and tactical decision making, and more efficient business processes by using BI solutions (Eckerson, 2003). Dramatic increases in data volumes over time and the mixed quality of data can adversely affect the performance of a data warehouse. Some data may become outdated over time and can be mixed with data that are still valid for decision making. In addition, data are often collected to meet potential requirements, but may never be used. Data warehouses also contain external data (e.g. demographic, psychographic, etc.) to support a variety of predictive data mining activities. All these factors contribute to the massive growth of data volume. As a result, even a simple query may become burdensome to process and cause overflowing system indices (Inmon et al., 1998). Thus, exploring the techniques of performance tuning becomes an important subject in data warehouse management.

Data Warehouse Performance

2011 ◽  
pp. 318-322
Author(s):  
Beixin (Betsy) Lin ◽  
Yu Hong ◽  
Zu-Hsu Lee
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Business Processes ◽  
Successful Implementation ◽  
End User ◽  
Bottom Line ◽  
User Query ◽  
Tactical Decision ◽  
Support Decision Making

A data warehouse is a large electronic repository of information that is generated and updated in a structured manner by an enterprise over time to aid business intelligence and to support decision making. Data stored in a data warehouse is non-volatile and time variant and is organized by subjects in a manner to support decision making (Inmon, Rudin, Buss, & Sousa, 1998). Data warehousing has been increasingly adopted by enterprises as the backbone technology for business intelligence reporting and query performance has become the key to the successful implementation of data warehouses. According to a survey of 358 businesses on reporting and end-user query tools, conducted by Appfluent Technology, data warehouse performance significantly affects the Return on Investment (ROI) on Business Intelligence (BI) systems and directly impacts the bottom line of the systems (Appfluent Technology, 2002). Even though in some circumstances it is very difficult to measure the benefits of BI projects in terms of ROI or dollar figures, management teams are still eager to have a “single version of the truth,” better information for strategic and tactical decision making, and more efficient business processes by using BI solutions (Eckerson, 2003).

scholarly journals Construction and functioning for the data warehouse in the enterprise in the context of the effective decision making

Equilibrium ◽  
2009 ◽  
Vol 2 (1) ◽  
pp. 171-180
Author(s):  
Michał Kukliński
Keyword(s):  
Decision Making ◽  
Data Processing ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Data Warehouses ◽  
Economic Decisions ◽  
Business Intelligence Systems ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Answering Questions

In the twenty-four hours of computerised enterprises, recruiting huge amounts of data, processing them in the traditional way would be highly ineffective and it will not deliver to us so much interesting information, forecasts and the relation, as Business Intelligence systems, of which Data Warehouses are a basis. The publication is answering questions: what the data warehouse is what is serving for and what are examples of applying. Stages of the build of the Data Warehouse and factors assuring achieving success in taking economic decisions will be introduced.

Enhancing Security in Banking Environment Using Business Intelligence

2020 ◽  
Vol 10 (4) ◽  
pp. 21-34
Author(s):  
Sonali Mathur ◽  
Shankar Lal Gupta ◽  
Payal Pahwa
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Encryption Scheme ◽  
Data Warehouses ◽  
Unauthorized Access ◽  
Security Issues ◽  
Security Algorithm ◽  
Different Sources

Data warehouses are the most valuable assets of an organization and are basically used for critical business and decision-making purposes. Data from different sources is integrated into the data warehouse. Thus, security issues arise as data is moved from one place to another. Data warehouse security addresses the methodologies that can be used to secure the data warehouse by protecting information from being accessed by unauthorized users for maintaining the reliability of the data warehouse. A data warehouse invariably contains information which needs to be considered extremely sensitive and confidential. Protecting this information is invariably very important as data in the data warehouse is accessed by users at various levels in the organization. The authors propose a method to protect information based on an encryption scheme which secures the data in the data warehouse. This article presents the most feasible security algorithm that can be used for securing the data stored in the operational database so as to prevent unauthorized access.

Data Warehouse Support for Policy Enforcement Rule Formulation

2019 ◽  
pp. 255-273
Author(s):  
Deepika Prakash
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Conversion Process ◽  
Tool Support ◽  
Policy Enforcement ◽  
Decision Making Problem ◽  
Operational Decision Making ◽  
Early Information ◽  
Support Decision Making ◽  
Policy Violation

It is believed that a data warehouse is for operational decision making. Recently, a proposal was made to support decision making for formulating policy enforcement rules that enforce policies. These rules are expressed in the WHEN-IF-THEN form. Guidelines are proposed to elicit two types of actions, triggering actions that cause the policy violation and the corresponding correcting actions. The decision-making problem is that of selecting the most appropriate correcting action in the event of a policy violation. This selection requires information. The elicited information is unstructured and is “early.” This work is extended by proposing a method to directly convert early information into its multi-dimensional form. For this, an early information mode is proposed. The proposed conversion process is a fully automated one. Further, the tool support is extended to accommodate the conversion process. The authors also apply the method to a health domain.

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.

Analysis of Business Intelligence Solutions in the SME Sectors

2015 ◽  
Vol 795 ◽  
pp. 123-128
Author(s):  
Leszek Kiełtyka ◽  
Klaudia Smoląg
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Complex Analysis ◽  
Small And Medium Enterprises ◽  
Decision Makers ◽  
Current Events ◽  
Decision Making Processes ◽  
Barriers To Implementation ◽  
Medium Enterprises ◽  
Support Decision Making

Business intelligence (BI) solutions are aimed to help managers make decisions in enterprises. Through complex analysis, decision-makers are supported in building strategies of operation. Managers in small and medium-sized enterprises (SME) are also becoming more aware of the fact that conventional methodology of analysis of current events is insufficient. Therefore, the need arises for using the solutions that support the processes of data analysis, finding relationships between each other or pointing to important tendencies and anomalies. These systems were primarily oriented at larger enterprises. However, BI solutions are more and more often adjusted to SME enterprises, offering a complex tool to support decision-making processes. This paper presents key stages in evolution of BI systems and characterizes selected BI systems dedicated to small and medium enterprises (SMEs). Substantial barriers to implementation of BI systems in SMEs were also indicated.

scholarly journals A Predictive Analytics Model for E-commerce Sales Transactions to Support Decision Making: A Case Study

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Shereen Morsi
Keyword(s):  
Decision Making ◽  
Predictive Analytics ◽  
Strategic Decisions ◽  
Business Decision ◽  
Innovative Capabilities ◽  
Data Volume ◽  
Precautionary Measures ◽  
Support Decision Making

Given the significant growth in electronic commerce, firms are seeking technological innovations and innovative capabilities to deal concurrently with the data’ volume generated and gaining insights from it for better decisions. Although recent studies identify predictive analytics as becoming the keystone of all business decision making and a crucial aspect in firms by it is a possible means for driving strategic decisions. Significant inroads into the interrelationships between capabilities and the execution of a pathway to an analytical capability to many Egyptian e-commerce businesses have yet to be made. Therefore, this paper aims to shed light on the importance and the role of using predictive analytics models in the Egyptian e-commerce firms where these tools became dominant resources for gaining valuable knowledge for better decision making by precautionary measures from prediction rates and different applications that have been applied by global e-commerce firms. The aim of the paper was achieved by building a predictive analytics model for sales forecasting by tackling to one of the e-commerce company in Egypt, and the online transaction dataset has been analyzed. The result obtained from the model has been displayed, and some insights extracted from the prediction model have been explained.

scholarly journals Building a Diabetes Data Warehouse to Support Decision making in healthcare industry

2014 ◽  
Vol 16 (2) ◽  
pp. 138-143 ◽  
Author(s):  
Abubakar Ado ◽  
◽  
Ahmed Aliyu ◽  
Saifullahi Aminu Bello ◽  
Abdulra’uf Garba Sharifai ◽  
...  
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Healthcare Industry ◽  
Support Decision Making

Web Page Extension of Data Warehouses

2011 ◽  
pp. 2090-2095
Author(s):  
Anthony Scime
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Decision Maker ◽  
Search Engine ◽  
External Information ◽  
Data Warehouses ◽  
Strategic Decisions ◽  
Web Searches ◽  
To Come ◽  
The Web

Data warehouses are constructed to provide valuable and current information for decision-making. Typically this information is derived from the organization’s functional databases. The data warehouse is then providing a consolidated, convenient source of data for the decision-maker. However, the available organizational information may not be sufficient to come to a decision. Information external to the organization is also often necessary for management to arrive at strategic decisions. Such external information may be available on the World Wide Web; and when added to the data warehouse extends decision-making power. The Web can be considered as a large repository of data. This data is on the whole unstructured and must be gathered and extracted to be made into something valuable for the organizational decision maker. To gather this data and place it into the organization’s data warehouse requires an understanding of the data warehouse metadata and the use of Web mining techniques (Laware, 2005). Typically when conducting a search on the Web, a user initiates the search by using a search engine to find documents that refer to the desired subject. This requires the user to define the domain of interest as a keyword or a collection of keywords that can be processed by the search engine. The searcher may not know how to break the domain down, thus limiting the search to the domain name. However, even given the ability to break down the domain and conduct a search, the search results have two significant problems. One, Web searches return information about a very large number of documents. Two, much of the returned information may be marginally relevant or completely irrelevant to the domain. The decision maker may not have time to sift through results to find the meaningful information. A data warehouse that has already found domain relevant Web pages can relieve the decision maker from having to decide on search keywords and having to determine the relevant documents from those found in a search. Such a data warehouse requires previously conducted searches to add Web information.

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