Data Warehousing and OLAP

2008 ◽  
pp. 169-178
Author(s):  
Jose Hernandez-Orallo
Keyword(s):  
Information Systems ◽  
Data Warehousing ◽  
Relevant Information ◽  
Decision Makers

Information systems provide organizations with the necessary information to achieve their goals. Relevant information is gathered and stored to allow decision makers to obtain quick and elaborated reports from the data.

Data Warehousing and OLAP

2005 ◽  
pp. 127-133
Author(s):  
Jose Hernandez-Orallo
Keyword(s):  
Information Systems ◽  
Data Warehousing ◽  
Relevant Information ◽  
Decision Makers

Information systems provide organizations with the necessary information to achieve their goals. Relevant information is gathered and stored to allow decision makers to obtain quick and elaborated reports from the data.

Haunted by a Doppelgänger

2014 ◽  
Vol 61 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Bettina von Helversen ◽  
Stefan M. Herzog ◽  
Jörg Rieskamp
Keyword(s):  
Relevant Information ◽  
Psychological Research ◽  
Decision Makers ◽  
Human Judgment ◽  
Rule Based ◽  
New Employees ◽  
High Performing ◽  
Facial Similarity ◽  
Similarity Effect ◽  
Judgment Strategy

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

scholarly journals Simple rules for an efficient use of Geographic Information Systems in molecular ecology

2017 ◽  
Author(s):  
Kevin Leempoel ◽  
Solange Duruz ◽  
Estelle Rochat ◽  
Ivo Widmer ◽  
Pablo Orozco-terWengel ◽  
...  
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Open Source ◽  
Spatial Data ◽  
Molecular Ecology ◽  
Relevant Information ◽  
Geographic Information ◽  
Environmental Data ◽  
Essential Information ◽  
Open Source Gis

AbstractGeographic Information Systems (GIS) are becoming increasingly popular in the context of molecular ecology and conservation biology thanks to their display options efficiency, flexibility and management of geodata. Indeed, spatial data for wildlife and livestock species is becoming a trend with many researchers publishing genomic data that is specifically suitable for landscape studies. GIS uniquely reveal the possibility to overlay genetic information with environmental data and, as such, allow us to locate and analyze genetic boundaries of various plant and animal species or to study gene-environment associations (GEA). This means that, using GIS, we can potentially identify the genetic bases of species adaptation to particular geographic conditions or to climate change. However, many biologists are not familiar with the use of GIS and underlying concepts and thus experience difficulties in finding relevant information and instructions on how to use them. In this paper, we illustrate the power of free and open source GIS approaches and provide essential information for their successful application in molecular ecology. First, we introduce key concepts related to GIS than are too often overlooked in the literature, for example coordinate systems, GPS accuracy and scale. We then provide an overview of the most employed open-source GIS-related software, file formats and refer to major environmental databases. We also reconsider sampling strategies as high costs of Next Generation Sequencing (NGS) data currently diminish the number of samples that can be sequenced per location. Thereafter, we detail methods of data exploration and spatial statistics suited for the analysis of large genetic datasets. Finally, we provide suggestions to properly edit maps and to make them as comprehensive as possible, either manually or trough programming languages.

Conceptualizing Emergency Department Scenarios

2015 ◽  
pp. 1351-1368 ◽  
Author(s):  
Maya Kaner ◽  
Tamar Gadrich ◽  
Shuki Dror ◽  
Yariv N. Marmor
Keyword(s):  
Emergency Department ◽  
Real Life ◽  
Relevant Information ◽  
Literature Survey ◽  
Decision Makers ◽  
Simulation Experiments ◽  
Management Staff ◽  
Ed Operations ◽  
Relevant Factors

To handle problems and trends in emergency department (ED) operations, designers and decision makers often simulate and evaluate various case-specific scenarios before testing them in a real-life environment. However, conceptualizing broad possible scenarios for ED operations prior to simulation operationalization is usually neglected. The authors developed a methodology that integrates design of simulation experiments (DSE) as follows: 1) From a literature survey, they culled generic factors whose varying levels determine possible scenarios; 2) the authors drew up a set of generic interactions among these generic factors; 3) a questionnaire was constructed to serve as an instrument to gather the relevant information from management staff about relevant factors, their levels and interactions for a specific ED. Questionnaire responses support a schematic conceptualization of scenarios that should be simulated for a specific ED. They illustrate the application of the authors' methodology for conceptualization of ED simulation scenarios in two different EDs.

Towards Private-Public Research Partnerships Combining Rigor and Relevance in DWH/BI Research

2012 ◽  
pp. 163-175
Author(s):  
Anne Cleven ◽  
Robert Winter ◽  
Felix Wortmann
Keyword(s):  
Information Systems ◽  
Business Intelligence ◽  
Data Warehousing ◽  
Academic Discipline ◽  
Public Research ◽  
Research Partnerships ◽  
Close Link ◽  
Research And Practice ◽  
Two Sides

Business intelligence (BI) and data warehousing (DWH) research represent two increasingly popular, but still emerging fields in the information systems (IS) academic discipline. As such, they raise two substantial questions: Firstly, “how rigorous, i.e., fundamental, constituent, and explanatory, is DWH BI research?” and, secondly, “how relevant, i.e., useful and purposeful, is this research to practitioners?” In this article, the authors uphold the position that relevance and rigor are by no means dichotomous, but two sides of the same coin. Naturally, this requires well-defined approaches and guidelines—for scholarship in general and DWH/BI research in particular. Therefore, this paper proposes the competence center (CC) approach—a private-public partnership between academia and practice. The authors illustrate how the CC approach can be applied within the field of DWH/BI and suggest that a close link between research and practice supports both enhancing relevance to practice and strengthening rigor of research.

A Model to Assist the Maintenance vs. Replacement Decision in Information Systems

2012 ◽  
pp. 137-157 ◽  
Author(s):  
O. Tolga Pusatli ◽  
Brian Regan
Keyword(s):  
Information Systems ◽  
Software Quality ◽  
Decision Makers ◽  
Software Quality Assurance ◽  
Extensive Literature ◽  
Science Literature ◽  
Overburden Pressure ◽  
Proposed Model ◽  
Maintenance Activities ◽  
Change Requests

An extensive literature review shows that Information Systems (IS) are changed and eventually replaced by substitutes under the influence of productivity, popularity, and specialisation of IS along with associated available support facilities, maintenance activities, failures, and user feedback. This chapter compiles those factors emerged from software engineering, IS, software quality assurance measurements, and computer science literature. A final product is a proposed model bringing those factors together as they are suspected to raise a need for taking the decision of evaluating change requests that may lead to a further maintenance or replace the IS. While keeping in mind that limitations on advanced testing exist, an expected service of such a model may help decision makers to explain maintenance/replacement decision of IS/component in a more itemized manner, hence diminish overburden pressure of experience responsibility on them.

Data Quality and Work Alignment

2011 ◽  
pp. 291-320
Author(s):  
Latif Al-Hakim ◽  
Hongjiang Xu
Keyword(s):  
Information Systems ◽  
Adverse Effects ◽  
Data Quality ◽  
Case Studies ◽  
Theoretical Background ◽  
Decision Makers ◽  
It Professionals ◽  
Improve Data Quality ◽  
Other Information ◽  
Importance Analysis

Organisational decision-makers have experienced the adverse effects of decisions based on information of inferior quality. Millions of dollars have been spent on information systems to improve data quality (DQ)1 as well as the skills and capacity of IT professionals. It is an important issue that the IT professionals align their work within the expectation of the organization’s vision. This chapter provides some theoretical background to DQ and establishes a link between DQ, performance-importance analysis and work alignment. Four case studies are presented to support the theory developed in this chapter and to answer the question as to whether the IT professionals consider DQ issues differently from other information users.

Semantic Integration of Structured and Unstructured Data in Data Warehousing and Knowledge Management Systems

2011 ◽  
pp. 81-105
Author(s):  
Liane Haak
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Data Warehousing ◽  
Semantic Integration ◽  
Unstructured Data ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Application Area ◽  
Ontology Integration ◽  
Basic Ideas

Nowadays, increasing information in enterprises demands new ways of searching and connecting the existing information systems. This chapter describes an approach for the integration of structured and unstructured data focusing on the application to Data Warehousing (DW) and Knowledge Management (KM). Semantic integration is used to improve the interoperability between two well-known and established information systems in the business context of nowadays enterprises. The objective is to introduce a semantic solution in the field of Business Intelligence based on ontology integration. The main focus of this chapter is not to provide a complete literature review of all existing approaches or just to point put the motivation for such an approach. In fact, it presents, under consideration of the most important research approaches, a solution for how a Semantic Integration could be technically achieved in this specific application area. After pointing out the motivation, a short introduction to Semantic Integration, the problems and challenges occurring from it, and the application area of Knowledge Management and Data Warehousing are given. Besides the basic ideas of ontologies and ontology integration are introduced. The approach itself starts with a short overview on the determined requirements, followed by a concept for generating an ontology from a Data Warehouse System (DWS) to be finally integrated with Knowledge Management Systems (KMS) ontology. Finally SENAGATOR, an exemplarily system for semantic navigation based on integrated ontologies, is shortly introduced.

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