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5. A reflective researcher with skills in:
(b) Conducting research

Dissertation Abstracts

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# Author Year Category Research Type Theme
1 Carte, Traci Ann 1999 Data Warehousing Practice Qualitative Impact of organizational environment on implementation.
2 Chen, Shiuhlon 1997 Data Warehousing Practice Qualitative/Action research? Decision support from data mining.
3 Chiou, Shao-Fong 1999 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
4 Gramme, Steven Joseph 1996 Data Warehousing Practice Qualitative/Action research? Query optimization
5 Haley, Barbara Jean 1997 Data Warehousing Practice Qualitative EIS framework
6 Hanson, Joseph H. 1996 Data Warehousing Theory Quantitative Organizational factors in implementation success.
7 Harinarayan, Venkatesh 1997 Data Warehousing Theory Quantitative Change management
8 He, Jianhui 1999 Data Warehousing Practice Action research Query optimization
9 Hirji, Karim Khan 1996 Data Warehousing Theory & Practice Qualitative Data warehouse implementation
10 Huyn, Nam Quan 1997 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
11 John, George Harrison 1997 Data Warehousing Theory Qualitative? Data warehouse implementation.
12 Kawaguchi, Akira 1998 Data Warehousing Theory Qualitative/Quantitative? Query optimization and change management
13 Kim, Hyeoncheol 1998 Data Warehousing Theory Quantitative Data mining research
14 Kuno, Harumi Anne 1996 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? Change management
15 Little, Robert Grover Jr 1998 Data Warehousing Practice Qualitative Data warehouse implementation
16 McGee, Kimberlee Roi 1997 Data Warehousing Practice Qualitative Data warehouse implementation
17 Park, Yong-Tae 1999 Data Warehousing Practice Qualitative Impact of data warehousing on decision support
18 Patterson, James Elder 1996 Data Warehousing Theory Qualitative Workflow theory, problems of data warehouse setup and maintenance
19 Quass, Dallan Wendell 1997 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? View maintenance optimization
20 Rallapalli, Prasad Venkataramana 1997 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? View-Less Value Based Security
21 Shaposhnikov, Artyom 1998 Data Warehousing Theory This is neither quantitative nor qualitative research - it is discovery and invention. What is that called? Efficient locking strategies for large mainly read transaction operations
22 Shim, Junho 1998 Data Warehousing Theory Qualitative Intelligent query cache management for serving data warehouse results over the web
23 Sriram, Cadambi 1997 Data Warehousing Theory Qualitative Using efficient materialized views in data warehouses
24 Stefanovic, Nebojsa 1997 Data Warehousing Theory Qualitative plus discovery Design and implementation of OLAP spatial data
25 Tam, Yin Jenny 1998 Data Warehousing Theory Quantitative Datacube designs that support efficient OLAP mining
26 Velayas, James Michael 1992 Decision Support Practice Quantitative/Qualitative  Applying Data Envelopment Analysis and Entropy in providing strategic direction
27 Wang, Rihui 1997 Data Warehousing Practice Qualitative  Principles, architecture, and implementation of data warehouses
28 White, Gary Leon 1996 Data Warehousing Practice Qualitative Using data mining as a technique for integrating data from multiple sources into a single data warehouse
29 Zhuge, Y. U. E. 1999 Data Warehousing Theory Qualitative and discovery Maintenance of warehouse views as data sources change
 
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1 Author Carte, Traci Ann
Year 1999
Title The Impact Of "Publicness" On Executive Information Systems Development (Organizational Theory, Systems Development)
Keywords business administration, management, political science, public administration, information science
Abstract Executive Information Systems (EIS) are experiencing a resurgence in popularity. Jazzy new concepts like enterprise resource planning, data warehousing, and data mining are giving rise to a renewed need to provide executives with meaningful views of corporate information (Desormeaux, 1998; Eshelman and Skatoff, 1998; Stedman, 1998; Stein, Sweat, and Carillo, 1998). With this resurgence comes a renewed need for researchers to provide insight into the complex EIS development environment. This study is a first step in developing an understanding of how differences in an organization's external environment impact EIS development. Research hypotheses were generated regarding the impact of sector membership on the critical success factors of EIS development. These hypotheses were empirically tested using a survey method. A self-administered questionnaire was mailed to 189 organizations. Responses were obtained from 54 percent. The results suggest that environmental differences do influence EIS development. Sector differences acted as a moderator in the relationship between organizational characteristics and EIS development environment characteristics. Further, these development environment characteristics were found to have a direct relationship to project success. These results are used to offer modified prescription to practitioners and advice to future researchers.
Search String "data warehousing"
Search Date 25-Aug-00
Search Num of
Thesis Type Ph.D.
University University Of Georgia
Category Data Warehousing Practice
Research Questions How differences in an organization's external environment impact EIS development.
Research Type Qualitative
Theme Impact of organizational environment on implementation.
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2 Author Chen, Shiuhlon
Year 1997
Title D4 an Integrated Architecture of Data Mining, a Data Warehouse, Distributed Databases and Distributed Computation (Decision Support Systems, MIS, Internet, Data Acquisition, Knowledge Deployment)
Keywords business administration, general; computer science
Abstract The study and application of Decision Support Systems (DSS) has become one of the major topics of MIS. An underlying component of a DSS is the decision model. Data mining is a useful technique to discover the hidden pattern or relationship among data. Thus, a decision model can be built upon the findings. However, unlike machine learning, a comprehensive data mining process covers from data collection to the use of discovered knowledge. How to gather the data from different resources becomes the first problem. To some industries, which are mainly consisted of small-scale business organizations, data resources are widely separated within each organization, even though the data logically belong to one data scheme. In this case the distributed databases exist but the distributed database management system does not. The data warehousing approach is introduced to overcome the problem of data acquisition. The other difficulty of data mining is the demand upon computing resources, and it can be computation intensive. This dissertation casts the above difficulties to a global network environment, namely the Internet. The goal is to integral a data warehouse, data mining, distributed databases and distributed computation into a single framework under the Internet infrastructure. This work fully develops this framework and implement a prototype system referred to as D4 that covers data acquisition, data mining and knowledge deployment.
Search String "data warehouse"; "data warehousing" AND "decision support"
Search Date 30-Jan-00
Search Num 26 of 80
Thesis Type Ph.D.
University The University Of Mississippi
Category Data Warehousing Practice
Research Questions How can data mining be used to discover patterns or relationships that provide useful support to decision making?
Research Type Qualitative/Action research?

Theme

Decision support from data mining.

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3 Author Chiou, Shao-Fong
Year 1999
Title The Impact of Early Grouping and User-Defined Functions On Query Optimization
Keywords computer science
Abstract On-line Analytical Processing (or OLAP) is a new class of query processing for large-scaled database systems. It provides a quick, responsive way for the users of Decision Support System (DSS) to navigate through the large amount of data in big organizations. To achieve the required performance, the frequently requested aggregate queries are precomputed (or materialized) and stored in a centralized repository, called Data Warehouse. Due to the large amount of data, the query optimizers must devise optimal plans for the computation of these materialized views to meet the user requirements. Traditional two-phase optimization approach for aggregate queries, i.e., optimizing the query without considering the GROUP BY and aggregation, and appending the aggregation on the resulting plan in the former process, is not guaranteed to produce optimal plans. A new technique that evaluates the GROUP BY operators early in query optimization provides more opportunities for the optimizers to find the optimal plans. However, pushing down the GROUP BY operator also increase the search space dramatically. The first part of the thesis is to derive heuristics that will reduce the search space in a cost-based optimization. The second part of the thesis extends the optimizer's ability to generate plans for queries with holistic aggregate functions, using the early grouping technique. One difficulty is that the evaluation of holistic functions cannot be started until all data are collected, which is not compatible with the early grouping technique. In the early grouping approach, data are evaluated by partitions and the results of the partitions are merged in the final stage. The thesis provides a method to start the evaluation by partially aggregating the input data even not all data are completely collected. The third part of the thesis enhances the database system to allow users define their own grouping attributes. This contribution allows users to generate new information from the existing data. The new ability, however, increases the burden to the optimizer to find an optimal plan when the attributes involved are derived from some other attributes. The thesis provides a new evaluation method and a thorough cost analysis of the new model. It offers the optimizers new opportunities to generate more cost efficient plans.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 1 of 80
Thesis Type D.Sc.
University University Of Lowell
Category Data Warehousing Theory
Research Questions To develop query optimization heuristics to improve OLAP query performance.
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
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4 Author Gramme, Steven Joseph
Year 1996
Title An Intelligent EIS With a Data Warehouse Facility
Keywords business administration, management; information science
Abstract In this thesis, I propose a system that integrates executive information system (EIS), intelligent agent, mathematical modeling, and data warehouse technologies. This intelligent EIS system will use data stored in an organization's data warehouse to answer pertinent executive questions. Unlike current EIS systems, this system is not limited to individual departmental questions; this intelligent EIS will answer executive questions company wide. This EIS will interact with a data warehouse via a user interface and coordinator and use intelligent agents and mathematical models in the EIS to manipulate data in the data warehouse into meaningful executive solutions. The intelligent agents and mathematical models include a rule-based reasoning mechanism, a case-based reasoning mechanism, a simulation modeling mechanism, a statistical modeling mechanism, and an optimization modeling mechanism. This thesis first discusses the framework of the proposed Intelligent EIS with a Data Warehouse Facility (IEISDW), then a case example that determines the best internet service provider for an organization will be presented which utilizes the tools in the system.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 38 of 80
Thesis Type M.B.A.
University California State University, Long Beach
Category Data Warehousing Practice
Research Questions How should an EIS be framed using a data warehouse? What ISP would provide the best use of these tools?
Research Type Qualitative/Action research?
Theme Query optimization
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5 Author Haley, Barbara Jean
Year 1997
Title Implementing the Decision Support Infrastructure: Key Success Factors in Data Warehousing (Information Technology)
Keywords business administration, management; information science
Abstract Today many organizations possess IT infrastructures that provide limited data management, integration, and access. These organizations would be better served by IT infrastructures that offer appropriate data and tools to support decision makers. Data warehousing provides a unique opportunity to improve the IT infrastructure. It is the process of implementing, maintaining, and using data that have been specially prepared to support decision making. Data warehousing addresses data management, integration. and access issues by creating a repository of quality data that can be manipulated to meet changing business needs. This study examined the effects of three groups of implementation factors on the success of data warehousing implementation. Two survey instruments were developed to measure implementation factors and success factors from an organization's data warehousing manager and data warehousing users, respectively. Ultimately, 241 survey packets were mailed to participating organizations, and 104 responded with usable surveys for a response rate of 43 percent. Structural equation modeling was performed on the responses from the mail survey to test the research model. Findings showed that organizational, project, and infrastructure factors are associated with the expected organizational, project, and infrastructure outcomes, respectively. Further, project and organizational outcomes are related to success factors. One hypothesis was not supported. Infrastructure outcomes are not associated with data warehousing implementation success.
Search String "data warehouse"; "data warehousing" AND "decision support"
Search Date 30-Jan-00
Search Num 16 of 80
Thesis Type Ph.D.
University University Of Georgia
Category Data Warehousing Practice
Research Questions Are organizational, project, and infrastructure factors associated with the success of data warehousing implementation?
Research Type Qualitative
Theme EIS framework
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6 Author Hanson, Joseph H.
Year 1996
Title An Alternative Data Warehouse Structure For Performing Updates (Database, SDB)
Keywords computer science
Abstract One key area involved in implementing the data warehouse is the transfer of information from the SDBs into the data warehouse and making it available to the user. Once the information is made available to the data warehouse, it must be incorporated into the overall data warehouse scheme. The difficulty is that the SDBs, being local in nature, are changing at a very rapid rate. In looking at the overall intent of the data warehouse as a repository for vast amounts of diverse information, these changes, made to the SDBs, can be critical to the correctness of the query responses provided by the warehouse. The problem could be solved by extracting all of the pertinent information and changes from the SDBs and immediately incorporating it into the warehouse. The pitfall to this type of solution is that the data warehouse will have very large amounts of information stored in its tables, possibly up to terabytes, and the incorporation and re-calculation of the views for this size database would be extremely expensive in terms of both time and computing power. This thesis presents an alterative to the state of the art data warehouse environment by providing an auxiliary structure to accept these updates and store them until the data warehouse has available cycle time to incorporate the new data and update the necessary views. By performing simulations against both the state of the art and alternative structures, this work proves that there is a significant performance improvement in user query response time by incorporating the auxiliary structure.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 31 of 80
Thesis Type D.C.S.
University Colorado Technical University
Category Data Warehousing Theory
Research Questions How to keep a very large data warehouse in synch with the rapid changes that occur in the production database.
Research Type Quantitative
Theme Organizational factors in implementation success.
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7 Author Harinarayan, Venkatesh
Year 1997
Title Query Processing In Data-Warehousing Environments (Olap, Precomputation, Aggregation, Decision Support)
Keywords computer science
Abstract Decision support, also known as On-Line Analytical Processing (OLAP) is a rapidly growing application of databases. OLAP systems involve processing complex aggregate queries on very large databases commonly called "data warehouses." Query response times can thus be very large for OLAP queries. However, since OLAP is an interactive process, small query response times are required. Query processing and optimization are thus critical to the success of OLAP systems, and in this thesis we develop efficient query processing and optimization techniques for OLAP. Precomputing frequently-used aggregates is the most commonly used approach to improving query performance. Since the available resources are usually limited, it is important to precompute the right set of aggregates. In this thesis, we give greedy algorithms that select the set of aggregates to precompute based on the available resources. We show that the benefit given by these greedy algorithms is close to that given by the optimal choice. Further, it has recently been shown that no polynomial-time algorithm can hope to do better than the greedy algorithm for this problem. OLAP queries make heavy use of aggregations, and so to derive algorithms for OLAP query processing, we need to reason about aggregation. In this thesis, we present an intuitive framework that treats aggregation as an extension of the classical duplicate-elimination operator. Our framework enables us to derive rules to move aggregates around in a query tree. These move-around rules form the basis for query optimization of OLAP queries. We then use these rules as building blocks in deriving algorithms for more complex problems. In particular, we provide a powerful solution to the problem of aggregate-navigation: how to use an aggregate view to answer an aggregate query, a very important problem in OLAP.
Search String "data warehousing"
Search Date 25-Aug-00
Search Num of
Thesis Type Ph.D.
University Stanford University
Category Data Warehousing Theory
Research Questions How to develop efficient query processing and optimization techniques for OLAP.
Research Type Quantitative
Theme Change management
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8 Author He, Jianhui
Year 1999
Title A Case Study On an Implementation of Marketing Data Analysis System
Keywords computer science; business administration, marketing; information science
Abstract This report documents the implementation of a data warehousing initiative for the purpose of marketing data analysis. Implementation of this project was divided into two phases. The objective of phase one is to produce a concept-proof prototype. Phase two, of which I took major responsibility, is to generate an actual production system. Major tasks I performed in phase two covered many aspects of the data warehousing life cycle: revised and fine-tuned the conceptual, logical and physical data model; performed database redesign and database sizing; built and rebuilt the database to improve performance; improved data extraction, transformation and loading process; performed database and SQL performance tuning; planned and implemented information presentation with off the shell data access tools. The first part of the report reviews the data warehousing literature by examining its evolution, conceptual model, major architectural components and some critical issues involved. In the second part of the report, the implementation of a marketing data warehouse is examined in details. A system overview is provided along with the logical data model. It then describes the mainframe component, UNIX components, presentation/end user component and the interaction among them. The Appendix provides further technical details of the project.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 2 of 80
Thesis Type M.Comp.Sc.
University Concordia University (Canada)
Category Data Warehousing Practice
Research Questions This report documents the implementation of a data warehousing initiative for the purpose of marketing data analysis.
Research Type Action research
Theme Query optimization
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9 Author Hirji, Karim Khan
Year 1996
Title Information Processing, Enabling Technology and Coordination Modeling in Complex Systems: the Case of Data Warehousing
Keywords operations research; computer science; information science
Abstract A data warehouse is a repository of selected information, drawn from remote databases or other information sources, that can be accessed directly by the end-user community. The primary impetus for data warehousing comes from the inadequacies of existing systems to meet the demands of a fast-changing business environment. The purpose of this thesis is to understand how organizational information requirements have changed, and the nature, definition, and specification of the resulting architected environment that supports enterprise-wide information processing. Specific emphasis is placed on the coordination issues that arise when data warehousing technology is introduced into existing traditional operational system environments to form an architected environment for enterprise-wide information processing. Literature on client/server systems, decision-support systems, data warehousing, systems theory and cybernetics, organization theory, and coordination theory is reviewed and provides the basis for a general proposition. A case study of a data warehousing project in a financial services company provides qualitative data for testing a specific instance of the proposition. In addition, important insights from the case study development experience, together with the reviewed literature, provide the foundation for a framework for modeling coordination in the design of a complex system. The contribution of this research both to theory and to practitioners is discussed.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 30 of 80
Thesis Type M.A.Sc.
University University Of Waterloo (Canada)
Category Data Warehousing Theory & Practice
Research Questions To understand how organizational information requirements have changed, and the nature, definition, and specification of the resulting architected environment that supports enterprise-wide information processing.
Research Type Qualitative
Theme Data warehouse implementation
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10 Author Huyn, Nam Quan
Year 1997
Title Maintaining Data Warehouses Under Limited Source Access (View Maintenance)
Keywords computer science
Abstract A data warehouse stores views derived from data that may not reside at the warehouse. Using these materialized views, user queries can be answered quickly because querying the external sources where the base data reside is avoided. However, when the sources change, the views in the warehouse can become inconsistent with the base data and must be maintained. A variety of approaches have been proposed for maintaining these views incrementally. At the one end of the spectrum, the required view updates are computed without restricting which base relations can be used. View maintenance with this approach is simple but can be expensive, since it may involve querying the external data sources. At the other end of the spectrum, additional views are stored at the warehouse to make sure that there is enough information to maintain the views without ever having to query the data sources. While this approach saves on external source access, it may require a large amount of information to be stored and maintained at the warehouse. In this thesis, we propose an intermediate approach to warehouse maintenance based on what we call Runtime View Self-Maintenance, where the views are incrementally maintained without using all the base relations but without requiring additional views to facilitate maintenance. Under limited information, however, maintaining a view unambiguously may not always be possible. Thus, the main questions in runtime view self-maintenance are: (1) View self-maintainability. Under what conditions (on the given information) can a view be maintained unambiguously with respect to a given update? (2) View self-maintenance. If a view can be maintained unambiguously, how do we maintain it using only the given information? The information we consider using for maintaining a view includes: (1) At least the contents of the view itself and the update instance; (2) Optionally, the contents of other views in the warehouse, functional dependencies the base relations are known to satisfy, a subset of the base relations, and partial contents of a base relation. Developing efficient complete solutions for the runtime self-maintenance of conjunctive-query views is the main focus and the main contribution of this thesis.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 22 of 80
Thesis Type Ph.D.
University Stanford University
Category Data Warehousing Theory
Research Questions How to survive changes in the data source without excessive CPU time or storage space.
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
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11 Author John, George Harrison
Year 1997
Title Enhancements to the Data Mining Process (Machine Learning, Pattern Recognition, Stock Selection)
Keywords computer science; economics, finance; artificial intelligence
Abstract Data mining is the emerging science and industry of applying modern statistical and computational technologies to the problem of finding useful patterns hidden within large databases. This thesis describes the data mining process and presents advances and novel methods for the six steps in the data mining process: extracting data from a database or data warehouse, cleaning the data, data engineering, algorithm engineering, data mining, and analyzing the results. We show how the standard data extraction process can be improved by building a direct interface between a data- mining algorithm and a relational database management system. Next, in data cleaning, we show how automatically iterating through the data mining process can identify records that can be profitably ignored during data mining. For data engineering, we develop an automated way to iterate through the data mining process to choose the subset of attributes that yields the best estimated results. In algorithm engineering, a similar process is used to automatically set the parameters of a mining algorithm. For the data mining algorithms, we study enhancements to classification tree induction methods and Bayesian methods. Our new flexible Bayes data-mining algorithm is fast, understandable, and more accurate than the standard Bayesian classifier in most situations. In classification tree induction we study various univariate splitting criteria and multivariate partitions. The analysis of results is necessarily domain-dependent. In an example applying data mining to stock selection, we discuss a key requirement in real-world applications using appropriate domain-dependent methods to evaluate the proposed solution.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 28 of 80
Thesis Type Ph.D.
University Stanford University
Category Data Warehousing Theory
Research Questions What are some new ways of carrying out the six steps in data warehousing?
Research Type Qualitative?
Theme Data warehouse implementation.
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12 Author Kawaguchi, Akira
Year 1998
Title Implementation Techniques For Materialized Views
Keywords computer science
Abstract Modern relational databases support views, virtual tables defined in terms of queries. A view is not necessarily explicitly stored. However, a view can be materialized by physically storing the result of the view in the database. The major advantage of using materialized views is speed--it is often quicker to access a materialized view than to recompute the corresponding query from scratch. The database system in our work maintains a materialized view incrementally to reestablish view consistency whenever the underlying data pertinent to the view is modified. The ability to use materialized views yields a significant performance benefit, not only to novel applications built on a data-warehouse, but also to already existing business applications. The problem of supporting materialized views is a re-emerging research topic, since some of the fundamental work was done during the late 80s. Nevertheless, the question of practical feasibility has remained unclear. The purpose of the research gathered in this thesis is to answer this question. Our first contribution is a set of solutions to the efficiency and consistency problems that arise when extending today's database system to support materialized views. We develop a number of key techniques that minimize the overhead of maintaining the auxiliary information required for view maintenance. We develop a model based on the notion of view groups to facilitate multiple view maintenance policies. We also develop concurrency control algorithms that guarantee serializability to transactions running in the presence of materialized views. In addition, we examine an extension of these techniques to cope with more complex, nested type of view definitions. In order to demonstrate technical feasibility of materialized views, we produce a prototype system on Ode, a publicly available object-oriented database system. The second contribution is the lessons gained from this experience. A number of implementation strategies detailed in this thesis will provide a hint for any database systems wishing to incorporate materialized views. Another contribution is a variety of detailed performance studies based on this implementation. The result gives a very good understanding of the costs, strengths, weaknesses, and tradeoffs of our proposals.
Search String "data warehouse"
Search Date 31-Jul-00
Search Num of
Thesis Type Ph.D.
University Columbia University
Category Data Warehousing Theory
Research Questions How can materialized views be maintained efficiently and accurately when there are changes to the underlying data structures?
Research Type Qualitative/Quantitative?
Theme Query optimization and change management
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13 Author Kim, Hyeoncheol
Year 1998
Title Knowledge Discovery: a Neural Network Approach (Rule Extraction)
Keywords computer science; artificial intelligence
Abstract Constructing a good model based on observed data and understanding the knowledge generated by the model are two key issues in knowledge discovery problems. The neural network is a good model that can estimate any smooth nonlinear function from the training data without any a priori assumptions. Recently, there has been much research on rule extraction from neural networks. One of the major problems investigated is reduction of rule search space. Several heuristics based on the KnowledgeTron algorithm have been introduced to reduce the search space. The algorithm can also be used to refine the neural network structure. In this thesis, a new search algorithm based on ordered attributes is introduced. It reduces search space dramatically and finds maximally general and confident rules for nodes in the network. In quantitative domains, a GA-based search algorithm is also proposed for rule extraction on the continuous-valued attributes. For a case study, industrial efforts in data mining and data warehousing are described, and customer churn analysis in the telecommunications industry is used as a demonstration of the proposed algorithms for industrial application.
Search String "data warehousing"
Search Date 30-Jan-00
Search Num 8 of 49
Thesis Type Ph.D.
University University Of Florida
Category Data Warehousing Theory
Research Questions How to reduce the search space requirement for data mining using neural network based artificial intelligence.
Research Type Quantitative
Theme Data mining research
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14 Author Kuno, Harumi Anne
Year 1996
Title View Materialization Issues In Object-Oriented Databases
Keywords computer science
Abstract Recent advances in information technology introduced a need for techniques to integrate heterogeneous sources, to cache and re-use results of queries across multiple information sources (data warehousing), to support customized interfaces to shared data, and to integrate such mechanisms with the powerful constructs of the object-oriented programming model. Object-oriented database (OODB) view technology can help provide such techniques. A view is a query that is stored and given a name by which it can be used in other queries. Typically a view's contents are derived using the view's stored query. View materialization, i.e., the generation of derived extents of views, improves the performance of queries by eliminating the need for such recomputation. However, it requires the maintenance of the contents of materialized views in the face of updates. This thesis proposes a methodology for the support and maintenance of materialized OODB views. We have implemented a prototype of this methodology in the context of the MultiView OODB view system, one of the first view management systems for object-oriented databases and (to the best of our knowledge) the first to support updatable incrementally materialized object-oriented views. The primary contribution of this work is the development of algorithms that exploit OO characteristics for the incremental maintenance of materialized OODB views. In particular, we address two potential inefficiencies to which update propagation algorithms are subject--the propagation of updates to irrelevant derived classes and the propagation of self-cancelling updates. We present cost models and experimental results that demonstrate that our techniques of hierarchical registration of the dependency of virtual classes on properties invoked in their predicates and derivation-ordered propagation successfully address these problems. We also propose a new Satisfiability Indicating Multi-Index (SMX) organization specifically tailored to optimize the maintenance of views defined by selection queries along aggregation paths (path query views). A key characteristic of our SMX solution is to maintain minimal partial information indicating whether or not the endpoints reachable from an object satisfies the query predicate. Our cost models confirm that the SMX dramatically improves upon the performance of traditional index structures with respect to the problem of path query view maintenance.
Search String "data warehousing"
Search Date 25-Aug-00
Search Num of
Thesis Type Ph.D.
University The University Of Michigan
Category Data Warehousing Theory
Research Questions How to maintain materialized views in an Object-oriented database (OODB).
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme Change management
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15 Author Little, Robert Grover Jr
Year 1998
Title Identification of Factors Affecting the Implementation of Data Warehousing (Firms, Decision-Making)
Keywords business administration, management; computer science
Abstract Increasing levels of change in competition and technology in the business environment are causing organizations to dramatically modify their strategies, information architectures, and methods of conducting business. Many firms have turned to data warehousing to assist in making decisions about the changes needed. While a few practitioner articles and books have addressed the issues affecting the implementation of data warehousing in organizations, there have been no empirical studies that rigorously address the factors. This study surveyed 242 members of data warehousing project implementation teams in 41 companies to obtain their perceptions of the extent that each of 116 items had actually contributed to the firm's implementation project during the actual implementation process. Each respondent was also asked to respond to his or her perceptions about how much each of the items should have contributed to the implementation (to capture their views of the extent of the increase or decrease in the relative strength of the item). The respondents included three categories or constituencies of project team members: functional managers/staff, IS managers/staff, and consultants directly involved in the data warehousing project. At the individual level of analysis, the study identified nine significant factors that actually impacted the implementation of data warehousing and eight significant factors that reflect the team members' perceptions of what should have impacted the implementation process. These factors represent key areas of the implementation process that should be addressed and resolved within the organization if the process is to be effective. The study also investigated the respondents' perceptions at the group level of analysis. Using multiple comparison techniques, significant differences were found between one or more pairs of the constituencies on over half of the items that respondents perceived to impact the implementation process and over two-thirds of the items that respondent groups believed should have impacted the process. Significant differences at the factor level between members of different constituency groups were also found. A major implication is that there needs to be closer interaction between researchers and practitioners on data warehouse implementation research in particular and increased levels of data warehousing research in general to be commensurate with the level of attention data warehousing is receiving in organizations.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 16 of 80
Thesis Type Ph.D.
University Auburn University
Category Data Warehousing Practice
Research Questions What are the important factors an organization needs to consider when implementing a data warehouse?
Research Type Qualitative
Theme Data warehouse implementation
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16 Author McGee, Kimberlee Roi
Year 1997
Title The Bottlenecks of Implementing a Successful Data Warehouse
Keywords business administration, general; computer science; information science
Abstract The successful implementation of the data warehouse has not been widely accomplished in industry. Even though the data warehouse has been clearly defined in numerous trade journals and some text books, its successful implementation has been sparse. Following the traditional systems development life cycle (SDLC) of planning, analyses, design, development, implementation and maintenance (Ahituv and Neumann 1990) the information technology teams attempt to implement the data warehouse in hopes of meeting the needs of the corporation and acquiring acceptance from the end user community. This thesis addresses the bottlenecks experienced in implementing a successful data warehouse. It covers lessons learned from real life projects, advice from professionals, experiences of the writer, and the views of end users. This thesis provides in depth knowledge of data warehousing and its components. The fundamentals of the data warehouse are presented, as well as findings from research surveys in the corporate environment which validate, through observation, the bottlenecks of implementing a successful data warehouse.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 23 of 80
Thesis Type M.S.
University The University Of Texas At Arlington
Category Data Warehousing Practice
Research Questions What can be learned from experience about the bottlenecks that occur when implementing a successful data warehouse?
Research Type Qualitative
Theme Data warehouse implementation
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17 Author Park, Yong-Tae
Year 1999
Title The Effects of Data Warehousing (DW) As a DSS Database Component On Decision Performance: an Experimental Study of DW in DSS Contexts (Decision Support Systems)
Keywords business administration, management; information science
Abstract Many organizations implement data warehousing (DW) as IT infrastructure to enhance the system quality and/or information quality of decision support systems (DSS) and thus to improve the decision performance of DSS users. However, no empirical evidence is available on the effects of DW on decision performance. To examine the effects of DW on decision performance, a laboratory experiment was conducted. Two levels of task complexity and three different DSS database characteristics (a traditional DSS database, DW with long-time history, and DW with long-time history and aggregated data) yielded a 2 x 3 factorial design with one within-subjects factor (task complexity) and one between-subjects factor (DSS database). The results show that the decision performance of DSS users supported with both long-time history and aggregated data was significantly higher than that for DSS users supported only with a traditional database. However, the performance of DSS users supported with both long-time history and aggregated data was not significantly different from that of DW groups with long- time history only. Also, no significant difference was found between the traditional DSS group and the DW group with long-time history only. Therefore, the findings of this study imply that to improve decision performance of DSS users, a DW must provide both long-time history and aggregated data. Providing long-time history without aggregation does not, in most cases, meet the information requirements of the decision tasks in DSS contexts. The findings also indicate that DSS users can expect to improve their decision performance by enhancing individual components of a DSS, without necessarily improving the whole information system. These findings expand the understanding of the effects of DW on decision performance. They also support the idea that the basic concepts of established IS models and theory (such as the IS success model, the conceptual theory of an advanced information technology, and technology-task fit model) are still valid in the context of a data warehouse and decision support systems.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 6 of 80
Thesis Type Ph.D.
University The Claremont Graduate University
Category Data Warehousing Practice
Research Questions This asks the question I want to answer.
Research Type Qualitative
Theme Impact of data warehousing on decision support
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18 Author Patterson, James Elder
Year 1996
Title Workflow and Data Warehousing Taxonomy
Keywords computer science; engineering, system science; information science
Abstract The concept of workflow has evolved from the need to automate business processes. Data warehousing represents a need to store large amounts of data from many heterogeneous sources for the purpose of allowing user queries and data mining. This thesis presents a literature review of attributes and concepts generally discussed in conjunction with workflow, workflow management systems, and maintaining a data warehouse. The workflow portion includes relaxed and enhanced transaction models that may be applied to workflow situations. Other models that are not transactional in nature, have been developed to define business scenarios and to provide a foundation for the specification and development of computer software to support processing of these business activities. The data warehouse portion introduces concepts and problems of setting up a data warehouse and in subsequently maintaining its views.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 33 of 80
Thesis Type M.S.
University The University Of Texas At Arlington
Category Data Warehousing Theory
Research Questions What are the essential concepts and attributes of workflow systems and data warehouses?
Research Type Qualitative
Theme Workflow theory, problems of data warehouse setup and maintenance
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19 Author Quass, Dallan Wendell
Year 1997
Title Materialized Views in Data Warehouses (Query Processing)
Keywords computer science
Abstract Data warehouses collect data from one or more external sources and translate it to a common schema that is easily queryable. In contrast to traditional on-line transaction processing (OLTP) database systems in which clients perform a mix of short-duration read and update transactions on the database, warehouse clients typically perform complex read-only queries, in order to analyze the data for trends and anomalies. This type of query processing is often referred to as on-line analytical processing (OLAP). In order to speed up the evaluation of such complex queries, warehouses usually precompute and store the results of certain queries. The stored results are called materialized views, and often involve aggregating data from large base relations. As changes are made to the source base relations, the warehouse views must be updated. Source changes are often applied to the warehouse views at regular intervals, usually once a day, in a large batch. Maintaining views in a data warehousing environment incurs problems not normally encountered when views are stored in the same database as the base data. First, extra information not available in the view itself is often required to maintain the view. This information must be obtained by querying the sources or by storing additional information in the warehouse. Second, aggregation is especially common in warehouse views; therefore, efficient algorithms for maintaining views are critical in data warehousing environments. Third, while the views are being maintained, the warehouse is often made unavailable to readers, which is unacceptable for global warehouses that need to be accessed around the clock. Algorithms are needed that reduce or eliminate the amount of time the warehouse is unavailable during view maintenance. This thesis makes important contributions in each of the above areas.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 21 of 80
Thesis Type Ph.D.
University Stanford University
Category Data Warehousing Theory
Research Questions What algorithms can be found to speed up the precomputation of aggregates to maximize the availability of data warehouse?
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme View maintenance optimization
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20 Author Rallapalli, Prasad Venkataramana
Year 1997
Title View-Less Value Based Security (Database, Query Modification, Dynamic Views, SQL)
Keywords computer science; business administration, management; engineering, system science; information science
Abstract This dissertation presents a new database security policy with broad business applicability, called Value Based Security (VBS). VBS rules create subsets of sensitive objects that depend only on the subject (user) and query type using expressions that specify values of VBS attributes. The rules are independent of: (I) Query language, object, complexity and order; (II) the DBMS; (III) Domains of VBS attributes. The main research question is how to enforce VBS rules effectively and efficiently for dynamic SQL queries--the mainstay of client-server and data warehouse applications. Static, DBMS-dependent facilities such as views or rules can enforce VBS effectively for static SQL queries. However they are infeasible for securing dynamic SQL queries due to: (1) High administrative complexity and coordination costs; (2) Limited Audit trail; (3) Dependence on DBMS; (4) Query scope and type restrictions; (5) Inflexible design; (6) Mandatory schema denormalization to support updates. The dissertation presents new data driven solutions that essentially reduce the research problem to one of dynamically intercepting and modifying a dynamic SQL query to enforce VBS rules. These techniques can create generalized 'dynamic views' for SQL query access. The described field implementation enforces VBS policy for thousands of dynamic SQL SELECT queries in a client- server data warehouse of a Fortune 50 corporation. This confirms the following advantages for the new solution: (1) Effective, consistent, efficient and transparent VBS enforcement; (2) Simple, flexible, scaleable, low cost, robust design; (3) Constant, dynamic enforcement performance independent of query scope, type and VBS rule complexity; (4) Secures SQL Update queries without denormalization; (5) No hidden side effects, independent of DBMS and location; (6) Easy, low cost administration; (7) Effective security audit. The main research contributions of this work are: (I) Formal specification of a new Value Based database security policy. (II) A new, comprehensive, effective solution to enforce VBS policy for dynamic SQL SELECT queries. (III) A new, general technique to create "dynamic views" by dynamically modifying SQL SELECT, UPDATE, INSERT and DELETE queries.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 24 of 80
Thesis Type Ph.D.
University The Claremont Graduate University
Category Data Warehousing Theory
Research Questions How can Value Based Security rules be enforced effectively and efficiently for dynamic SQL queries
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme View-Less Value Based Security
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21 Author Shaposhnikov, Artyom
Year 1998
Title Algorithms For Efficient Transaction Management And Consistent Queries In Client-Server Semantic Object-Oriented Parallel Databases (Lazy Queries)
Keywords computer science
Abstract Large read-only or read-write transactions with a large read set and a small write set constitute an important class of transactions used in such applications as data mining, data warehousing, statistical applications, and report generators. Such transactions are best supported with optimistic concurrency, because locking of large amounts of data for extended periods of time is not an acceptable solution. The abort rate in regular optimistic concurrency algorithms increases exponentially with the size of the transaction. The algorithm proposed in this dissertation solves this problem by using a new transaction scheduling technique that allows a large transaction to commit safely with significantly greater probability that can exceed several orders of magnitude versus regular optimistic concurrency algorithms. A performance simulation study and a formal proof of serializability and external consistency of the proposed algorithm are also presented. This dissertation also proposes a new query optimization technique (lazy queries). Lazy Queries is an adaptive query execution scheme which optimizes itself as the query runs. Lazy queries can be used to find an intersection of sub-queries in a very efficient way, which does not require full execution of large sub-queries nor does it require any statistical knowledge about the data. An efficient optimistic concurrency control algorithm used in a massively parallel B-tree with variable-length keys is introduced. B-trees with variable-length keys can be effectively used in a variety of database types. In particular, we show how such a B-tree was used in our implementation of a semantic object-oriented DBMS. The concurrency control algorithm uses semantically safe optimistic virtual "locks" that achieve very fine granularity in conflict detection. This algorithm ensures serializability and external consistency by using logical clocks and backward validation of transactional queries. A formal proof of correctness of the proposed algorithm is also presented.
Search String "data warehousing"
Search Date 25-Aug-00
Search Num of
Thesis Type Ph.D.
University Florida International University
Category Data Warehousing Theory
Research Questions How can data integrity be preserved during concurrent access involving large read data sets?
Research Type This is neither quantitative nor qualitative research - it is discovery and invention. What is that called?
Theme Efficient locking strategies for large mainly read transaction operations
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22 Author Shim, Junho
Year 1998
Title An Intelligent Cache Manager in Data Warehousing Environment and Its Application to the Web Caching (World Wide Web)
Keywords computer science
Abstract A data warehouse is a stand-alone repository of information consisting of "interesting" and "historic" data from several, heterogeneous, operational databases, and the size of data warehouse is very large and grows over time. Data warehouses are usually dedicated to the processing of queries issued by decision support systems (DSS). The response time of DSS queries is typically several orders of magnitude higher than the response time of OLTP (OnLine Transaction Processing) queries. Since DSS queries are often submitted interactively, techniques for reducing their response time are important. The caching of query results is one such technique particularly well suited to the DSS environment. In this thesis, we present an intelligent cache manager for such an environment. The cache manager can lookup queries either based on an exact query match or using a query split algorithm to efficiently find query results which subsume the submitted query. The cache manager dynamically maintains the cache content by deciding whether a new query result should be admitted to the cache and if so, which query results should be evicted from the cache. The decisions are aimed at minimizing query response time. The decisions are based on the execution cost of each query, the size of each query result, the reference frequency to each result, the cost of maintenance of each result due to updates of the base tables, and the frequency of updates. Experimental evaluation shows that the manager can significantly improve performance when compared to similar systems. Since Web documents vary in their size, and the cost of their materialization depends upon the network delays, a profit based cache replacement algorithm can be applied to Web caching. At the same time, the cache must guarantee some form of consistency of the cached documents. Cache consistency algorithms enforce appropriate guarantees about the staleness of the cached documents. We have developed a unified cache maintenance algorithm which integrates both cache replacement and consistency algorithms. A trace-driven experimental study shows that the unified algorithm not only improves the average response time but also reduces the significant number of stale documents returned to the clients.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 12 of 80
Thesis Type Ph.D.
University Northwestern University
Category Data Warehousing Theory
Research Questions How can query results be intelligently cached in the context of access via the world wide web?
Research Type Qualitative
Theme Intelligent query cache management for serving data warehouse results over the web
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23 Author Sriram, Cadambi
Year 1997
Title Using Materialized Views in Data Warehouses
Keywords computer science; information science
Abstract Decision support functions, such as On-line Analytical Processing, issue queries that need to aggregate large volumes of data present in a data warehouse. To improve the performance of these queries, warehouses typically contain tables that contain data in a summarized form. As new data is brought into the warehouse, these summary tables are updated appropriately. Two factors limit the number of summary tables that can be created: the amount of disk space required by the tables and the processing time incurred to update the tables in response to new data. We examine how materialized views can be used to store and manage summary data efficiently. This thesis discusses the design and implementation of the Queen's Warehousing system which provides facilities to create materialized views for certain aggregate combinations selectively and to maintain the views using incremental maintenance techniques.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 20 of 80
Thesis Type M.Sc.
University Queen's University At Kingston (Canada)
Category Data Warehousing Theory
Research Questions How can materialized views be made more efficient in terms of disk space and processing time?
Research Type Qualitative
Theme Using efficient materialized views in data warehouses
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24 Author Stefanovic, Nebojsa
Year 1997
Title Design and Implementation of On-Line Analytical Processing (OLAP) of Spatial Data
Keywords computer science
Abstract On-line analytical processing (OLAP) has gained its popularity in database industry. With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object- relational databases, it is important to study the methods for spatial data warehousing and on-line analytical processing of spatial data. This thesis investigates methods for spatial OLAP, by integration of nonspatial on-line analytical processing (OLAP) methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies proposed, including approximation and partial materialization of the spatial objects resulting from spatial OLAP operations. Some techniques for selective materialization of the spatial computation results are worked out, and the performance study has demonstrated the effectiveness of these techniques. Spatial OLAP has been partially implemented as a part of GeoMiner, a system prototype for spatial data mining.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 19 of 80
Thesis Type M.Sc.
University Simon Fraser University (Canada)
Category Data Warehousing Theory
Research Questions What methods of spatial data storage yield the best computational performance? 
Research Type Quantitative plus discovery
Theme Design and implementation of OLAP spatial data
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25 Author Tam, Yin Jenny
Year 1998
Title Datacube: Its Implementation and Application in Olap Mining
Keywords computer science; information science
Abstract With huge amounts of data collected in various kinds of applications, data warehouse is becoming a mainstream information repository for decision support and data analysis mainly because a data warehouse facilitates on- line analytical processing (OLAP). It is important to study methods for supporting data warehouses, in particular its OLAP operations, efficiently. In this thesis, we investigate efficient methods for computing datacubes and for using datacubes to support OLAP and data mining. Currently, there are two popular datacube technologies: Relational OLAP (ROLAP) and Multidimensional OLAP (MOLAP). Many efficient algorithms have been designed for ROLAP systems, but not so many for the MOLAP ones. MOLAP systems, though may suffer from sparsity of data, are generally more efficient than ROLAP systems when the sparse datacube techniques are explored or when the data sets are small to medium sized. We have developed a MOLAP system which combines nice features of both MOLAP and ROLAP. Our performance study shows that such an integrated system is faster than plain MOLAP or ROLAP systems in many cases. We also discuss the promising direction of OLAP mining (data mining integrated with OLAP). On top of this MOLAP system, we developed some OLAP mining modules to assist users to discover different kinds of knowledge from the data. Decision makers often do not know exactly what they want when they do OLAP or mining, so OLAP mining helps them explore the data flexibly from different angles and at multiple abstraction levels.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 3 of 80
Thesis Type M.Sc.
University Simon Fraser University (Canada)
Category Data Warehousing Theory
Research Questions What methods for computing datacubes are most efficient in supporting OLAP and data mining, as well as in computation?
Research Type Quantitative
Theme Datacube designs that support efficient OLAP mining
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26 Author Velayas, James Michael
Year 1992
Title Strategic Management Decision Support For A Firm In Pursuit Of The Displaced Ideal Utilizing Data Envelopment Analysis And Entropy
Keywords Operations Research; Economics, Finance; Business Administration, Management
Abstract A firm engaged in competition with other firms is constantly evolving as it pursues its goal of maximizing shareowner wealth. This evolution can be thought of as the firm pursuing the goal of becoming the ideal firm. An ideal firm would be one that embodies all of the superior characteristics of the firms that are in competition with one another. Clearly, with the passage of time firms become more efficient and effective in the pursuit of their goal. So as the firms change so does the ideal firm's characteristics. The purpose of this research is to develop a procedure and illustrate the use of data envelopment analysis (DEA) and entropy as analytical techniques in providing strategic guidance to the firm. The information provided by the companies evaluated under this procedure will originate from the companies' annual reports. This research will use the set of the seven publicly traded Bell Holding Companies in the formation of the empirical database. The database will be used to illustrate the procedure developed in this research. The database will contain financial and operational information concerning each firm's performance. Then this information will be linked with DEA and entropy measures and will provide a normative framework upon which each firm's decision makers can determine the direction they wish to follow in pursuit of the ideal. The analysis will be conducted based upon the publicly available information contained in the seven companies' annual reports during the years 1984 through 1989. Additionally a qualitative dimension will be incorporated into the study to provide additional insight. This research will present the value of DEA and entropy being linked together as a procedure to assist in the strategic management of the firm. The ability to apply these two nontraditional analytical methods in providing strategic direction to the firm will be shown to be a valuable managerial asset.
Search String "qualitative" AND "decision support" AND "database"
Search Date 05-Jul-99
Search Num 8 of 9
Thesis Type Ph.D.
University Saint Louis University
Category Decision Support Practice
Research Questions How can data envelope analysis and entropy be used as analytical techniques to provide strategic guidance in achieving business ideals?
Research Type Quantitative/Qualitative
Theme Applying Data Envelopment Analysis and Entropy in providing strategic direction
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27 Author Wang, Rihui
Year 1997
Title On the Design of a Secure Data Warehouse
Keywords computer science; information science
Abstract The data warehouse is the combination of subject- oriented, authoritative, integrated databases designed to support the DSS (decision support). Data mining means to extract useful information which is previously unknown from information sources. The topic of data warehousing and data mining encompasses architectures, algorithms and tools for collecting selected data from multiple databases or other information sources into a single repository known as a data warehouse which is structured to facilitate query or analysis in supporting decision making. In this thesis, we will discuss the principles, architecture, and implementation of data warehouses. We will also discuss construction of data mining and some algorithms applied to data mining. We will do some research on the security of data warehouses.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 17 of 80
Thesis Type M.S.
University University Of Nevada, Las Vegas
Category Data Warehousing Practice
Research Questions What are the principles of good data warehouse architecture and implementation , and how can effective data mining and security be supported?  (The definitions of data warehousing and data mining given in the abstract strongly resemble those given in Gary White's abstract, written a year earlier at the same university.)
Research Type Qualitative
Theme Principles, architecture, and implementation of data warehouses
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28 Author White, Gary Leon
Year 1996
Title Data Integration With Data Warehousing and Data Mining in Database Environments
Keywords computer science; information science
Abstract The topics of data warehousing and data mining encompasses architectures, algorithms and tools for bringing together selected data from multiple databases or other information sources into a single repository called a data warehouse which is suitable for direct querying or analysis. The querying and analysis can be implemented with any of the data mining tools being developed. Data mining is the non-trivial extraction of implicit, previously unknown and potentially useful information from information sources. In this thesis, we will define a specific data warehousing architecture, its components and give an explanation of the responsibilities of the components in the data warehousing system are defined. The new data warehousing system and it components will also provide suitable topics for exploratory research into their implementation. We will also explain how data mining techniques will be used to extract data from multiple information sources to place data into the central data warehouse of the system and how data mining tools will be used to query and analysis the data warehouse system.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 37 of 80
Thesis Type M.Sc.
University University Of Nevada, Las Vegas
Category Data Warehousing Practice
Research Questions What are some of the key components of the data warehouse design and implementation process?  How can data mining techniques be used to integrate data from multiple sources?
Research Type Qualitative
Theme Using data mining as a technique for integrating data from multiple sources into a single data warehouse
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29 Author Zhuge, Y. U. E.
Year 1999
Title Incremental Maintenance of Consistent Data Warehouses (Whips, View Maintenance)
Keywords computer science
Abstract A data warehouse stores information integrated from distributed and possibly heterogeneous information sources. In effect, the warehouse stores materialized views over the source data. This dissertation studies the maintenance of warehouse views as the data sources are updated. The first part of this dissertation presents a family of algorithms that incrementally and consistently maintain relational materialized views in a data warehouse. This view maintenance problem differs from the traditional one in that the view definition and the base data are decoupled, and data sources are autonomous. We show that this decoupling can result in anomalies if traditional algorithms are applied. We formalize notions of consistency for warehouse views and present new algorithms that maintain consistency as the warehouse is updated. In addition, we develop simple, scalable, algorithms for ensuring mutual consistency among multiple views at a warehouse. We also present the implementation of the algorithms in the WHIPS (WareHousing Information Project at Stanford) prototype and related performance results. The second part of this dissertation studies how to maintain graph-structured materialized views. A graph- structured database consists of records containing identifiers of other records. The data could represent semi-structured information such as Web pages, documents, XML data, or data integrated from heterogeneous data sources. We define views and materialized views for such graph-structured data, analyzing options for representing record identity and references in the view. We then develop incremental maintenance algorithms for these views, discuss how to realize these algorithms in a data warehouse, and study how to maintain the warehouse views without accessing base data.
Search String "data warehouse"
Search Date 30-Jan-00
Search Num 8 of 80
Thesis Type Ph.D.
University Stanford University
Category Data Warehousing Theory
Research Questions What are some new approaches to maintaining materialized views in a data warehouse when the structure of the data sources change?
Research Type Qualitative and discovery
Theme Maintenance of warehouse views as data sources change
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Created: Sunday, July 25, 1999 05:51 PM
Last Modified: Sunday, December 23, 2001 10:36 AM