scholarly journals Research on Some Problems Before Decision Making of Party Committee of State-owned Enterprises Based on Data Model

2021 ◽  
Vol 1744 (4) ◽  
pp. 042014
Author(s):  
Wensheng Li ◽  
Chuanbao Gong ◽  
Junliang Li
Keyword(s):  
Decision Making ◽  
Data Model ◽  
Party Committee

Decision Making in Team Sports: Data, model and applied perspective

2008 ◽  
Author(s):  
Pedro J. M. Passos ◽  
Duarte Araujo ◽  
Keith Davids ◽  
Ana Diniz ◽  
Luis Gouveia ◽  
...  
Keyword(s):  
Decision Making ◽  
Data Model ◽  
Team Sports ◽  
Sports Data

scholarly journals Quality of data model for supporting mobile decision making

2007 ◽  
Vol 43 (4) ◽  
pp. 1675-1683 ◽  
Author(s):  
Julie Cowie ◽  
Frada Burstein
Keyword(s):  
Decision Making ◽  
Data Model ◽  
Quality Of Data

scholarly journals Data Warehouse Schemas using Multidimensional Data Model for Retail

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

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

DATA model for a multidimensional decision making in healthcare

2016 ◽  
Vol 6 (2) ◽  
pp. 138
Author(s):  
Antonella Petrillo ◽  
Fabio De Felice ◽  
Laura Petrillo
Keyword(s):  
Decision Making ◽  
Data Model

Building a geospatial data model for humanitarian response

2014 ◽  
Vol 12 (5) ◽  
pp. 383
Author(s):  
Nuala M. Cowan, DSc, MA, BA
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Information Management ◽  
Emergency Response ◽  
Data Model ◽  
Rapid Assessment ◽  
Geospatial Data ◽  
Geographical Information ◽  
Collection Management ◽  
Response Effort

Objective: An effectual emergency response effort is contingent upon the quality and timeliness of information provided to both the decision making and coordinating functions; conditions that are hard to guarantee in the urgent climate of the response effort. The purpose of this paper is to present a validated Humanitarian Data Model (HDM) that can assist in the rapid assessment of disaster needs and subsequent decision making. Substandard, inconsistent information can lead to poorly informed decisions, and subsequently, inappropriate response activities. Here we present a novel, organized, and fluid information management workflow to be applied during the rapid assessment phase of an emergency response. A comprehensive, peer-reviewed geospatial data model not only directs the design of data collection tools but also allows for more systematic data collection and management, leading to improved analysis and response outcomes.Design: This research involved the development of a comprehensive geospatial data model to guide the collection, management and analysis of geographically referenced assessment information, for implementation at the rapid response phase of a disaster using a mobile data collection app based on key outcome parameters. A systematic review of literature and best practices was used to identify and prioritize the minimum essential data variables.Subjects: The data model was critiqued for variable content, structure, and usability by a group of subject matter experts in the fields of humanitarian information management and geographical information systems.Conclusions: Consensus found that the adoption of a standardized system of data collection, management, and processing, such as the data model presented here, could facilitate the collection and sharing of information between agencies with similar goals, facilitate the better coordination of efforts by unleashing the power of geographic information for humanitarian decision support.

scholarly journals PARTISIPASI MASYARAKAT DALAM PEMBANGUNAN KAMPUNG WISATA “WARNA-WARNI” JODIPAN KOTA MALANG JAWA TIMUR

2017 ◽  
Vol 2 (1) ◽  
pp. 90-102
Author(s):  
Kus Indarto
Keyword(s):  
Decision Making ◽  
Community Participation ◽  
Social Participation ◽  
Data Model ◽  
Interactive Model ◽  
The People ◽  
Participation In Decision Making ◽  
Degree Of Participation ◽  
Descriptive Method

AbstrakPenelitian ini bertujuan untuk mendeskripsikan dan menganalisis partisipasimasyarakat Kampung Wisata “Warna-Warni” Jodipan dalampembangunan/pengecatan kampung mereka. Pembangunan Kampung Wisata“Warna-Warni” Jodipan diinisiasi oleh mahasiswa Universitas MuhammadiyahMalang yang sedang melaksanakan tugas praktikum. Guna melakukanpengecatan, mahasiswa bekerja sama dengan PT. Indana Paint. Penelitian inimerupakan penelitian kualitatif dengan metode deskriptif. Data yang diperolehdianalisis dengan menggunakan analisis data model interaktif yang dikemukakanoleh Miles, Huberman dan Saldana. Hasil temuan di lapangan menunjukkanbahwa masyarakat Kampung Wisata “Warna-Warni” Jodipan berpartisipasidalam pembuatan keputusan (participation in decision making), implementasi(participation in implementation), kemanfaatan (participation in benefit) dan jugaevaluasi (participation in evaluation). Bentuk-bentuk partisipasi masyarakatKampung Wisata “Warna-Warni” Jodipan dalam pembangunan/pengecatankampung mereka berupa partisipasi buah pikiran, partisipasi tenaga, partisipasiharta benda, partisipasi keterampilan dan kemahiran serta partisipasi sosial(keguyupan). Derajat partisipasi masyarakat Kampung Wisata “Warna-Warni”Jodipan berada dalam derajat pertanda partisipasi, dan berada pada anaktangga yang ke lima, yaitu penentraman (placation).Kata kunci: derajat partisipasi, partisipasi, masyarakatAbstractThe aims of this research are to describe and analyze the Jodipan “Colorful”Village Tour community participation in the developmen/painting their village.Development Jodipan “Colorful” Tour Village was initiated by University ofMuhammadiyah Malang (UMM) students who were carrying out practical tasks.In order to do the painting, students work together with PT. Indana Paint.Thisresearch is a qualitative with descriptive method. Data were analyzed using dataanalysis interactive model proposed by Miles, Huberman and Saldana. Thefindings in the field shows that the people in Jodipan “Colorful” Tour Villageparticipate in decision-making, implementation, benefit and evaluation. Forms ofcommunity participation in the development of Jodipan “Colorful” Tour Villagenamely: ideas participation, force participation, the participation of property,participation skill and finesse, and social participation. The degree of communityparticipation Jodipan “Colorful” Tour Village are in degrees sign ofparticipation, and are on the fifth rung, namely placation.Key words: degree of participation, participation, community

Using Data Mining Techniques to Discover Patterns in an Airline's Flight Hours Assignments

2021 ◽  
pp. 107-126
Author(s):  
Francisco Javier Villar Martín ◽  
Jose Luis Castillo Sequera ◽  
Miguel Angel Navarro Huerga
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information System ◽  
Predictive Modeling ◽  
Data Model ◽  
Free Software ◽  
Data Mining Techniques ◽  
Visualization Tools ◽  
Using Data

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.

Relating Business Intelligence and Enterprise Architecture — A Method for Combining Operational Data with Architectural Metadata

2016 ◽  
Vol 25 (02) ◽  
pp. 1650007 ◽  
Author(s):  
R. K. M. Veneberg ◽  
M.-E. Iacob ◽  
M. J. van Sinderen ◽  
L. Bodenstaff
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Data Model ◽  
Enterprise Architecture ◽  
Business Analytics ◽  
Raw Data ◽  
Architecture Model ◽  
Model Based ◽  
Operational Data ◽  
Support Decision Making

Combining enterprise architecture and operational data is complex (especially when considering the actual ‘matching’ of data with enterprise architecture elements), and little has been written on how to do this. In this paper we aim to fill this gap, and propose a method to combine operational data with enterprise architecture to better support decision-making. Using such a method may result in either an enriched enterprise architecture model (which is very suitable as basis for model-based architecture analyses) or a warehouse data model where operational data is enriched with enterprise architecture metadata (which leads to more traceability by easing the retrieval and interpretation of raw data and of business analytics results). The method is illustrated by means of a case and evaluated by experts. Also, a model for mapping enterprise architecture, operational data, and time is proposed, which allows the model-based execution of new types of analyses.

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