scholarly journals Analisis Dan Perancangan Data Warehouse Pada PT Gajah Tunggal Prakarsa

2010 ◽  
Vol 1 (2) ◽  
pp. 437
Author(s):  
Choirul Huda ◽  
Bram Pangestu ◽  
Jimmy Lai ◽  
Riantoro Teja
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Data Warehouse ◽  
Research Methodology ◽  
Analysis Study ◽  
Library Research ◽  
Star Schema ◽  
Current Systems

The purpose of this helpful in making decisions more quickly and precisely. Research methodology includes analysis study was to analyze the data base support in helping decisions making, identifying needs and designing a data warehouse. With the support of data warehouse, company leaders can be more of current systems, library research, designing a data warehouse using star schema. The result of this research is the availability of a data warehouse that can generate information quickly and precisely, thus helping the company in making decisions. The conclusion of this research is the application of data warehouse can be a media aide related parties on PT. Gajah Tunggal initiative in decision making. 

scholarly journals Analisis Dan Perancangan Data Warehouse Pada PT Pelita Tatamas Jaya

2010 ◽  
Vol 1 (2) ◽  
pp. 461
Author(s):  
Choirul Huda ◽  
Jumas Ranope ◽  
Marly Lumenta ◽  
Kevin Kevin
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Inventory Control ◽  
Research Methodology ◽  
Data Warehousing ◽  
Business Leaders ◽  
Library Research ◽  
Decision Making Processes ◽  
Current Systems ◽  
Support Decision Making

The purpose of this research is to assist in providing information to support decision-making processes in sales, purchasing and inventory control at PT Tatamas Pelita Jaya. With the support of data warehouse, business leaders can be more helpful in making decisions more quickly and precisely. Research methodology includes analysis of current systems, library research, designing a data warehousing schema using bintang. The result of this research is the availability of a data warehouse that can generate information quickly and precisely, thus helping the company in making decisions. The conclusion of this research is the application of data warehouse can be a media aide related parties on PT Tatamas Pelita Jaya in decision making. 

Facilitate Effective Decision-Making by Warehousing Reduced Data

2015 ◽  
Vol 7 (3) ◽  
pp. 36-64 ◽  
Author(s):  
Faten Atigui ◽  
Franck Ravat ◽  
Jiefu Song ◽  
Olivier Teste ◽  
Gilles Zurfluh
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Conceptual Modeling ◽  
Multidimensional Data ◽  
Meta Model ◽  
Star Schema ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Definition Of ◽  
Reduced Data

The authors' aim is to provide a solution for multidimensional data warehouse's reduction based on analysts' needs which will specify aggregated schema applicable over a period of time as well as retain only useful data for decision support. Firstly, they describe a conceptual modeling for multidimensional data warehouse. A multidimensional data warehouse's schema is composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. The derivation between states is carried out through combination of reduction operators. Secondly, they present a meta-model which allows managing different states of multidimensional data warehouse. The definition of reduced and unreduced multidimensional data warehouse schema can be carried out by instantiating the meta-model. Finally, they describe their experimental assessments and discuss their results. Evaluating their solution implies executing different queries in various contexts: unreduced single fact table, unreduced relational star schema, reduced star schema and reduced snowflake schema. The authors show that queries are more efficiently calculated within a reduced star schema.

Applying Deep Learning to Audit Procedures: An Illustrative Framework

2019 ◽  
Vol 33 (3) ◽  
pp. 89-109 ◽  
Author(s):  
Ting (Sophia) Sun
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Data Warehouse ◽  
Visual Recognition ◽  
Prediction Models ◽  
Historical Data ◽  
Structured Data ◽  
Text Understanding ◽  
Audit Data ◽  
Learning Functions

SYNOPSIS This paper aims to promote the application of deep learning to audit procedures by illustrating how the capabilities of deep learning for text understanding, speech recognition, visual recognition, and structured data analysis fit into the audit environment. Based on these four capabilities, deep learning serves two major functions in supporting audit decision making: information identification and judgment support. The paper proposes a framework for applying these two deep learning functions to a variety of audit procedures in different audit phases. An audit data warehouse of historical data can be used to construct prediction models, providing suggested actions for various audit procedures. The data warehouse will be updated and enriched with new data instances through the application of deep learning and a human auditor's corrections. Finally, the paper discusses the challenges faced by the accounting profession, regulators, and educators when it comes to applying deep learning.

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

scholarly journals Remote Virtual Simulation for Incident Commanders—Cognitive Aspects

2021 ◽  
Vol 11 (14) ◽  
pp. 6434
Author(s):  
Cecilia Hammar Wijkmark ◽  
Maria Monika Metallinou ◽  
Ilona Heldal
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Cognitive Processes ◽  
Research Methodology ◽  
Current Knowledge ◽  
Learning Objectives ◽  
Virtual Simulation ◽  
Practical Training ◽  
Case Research ◽  
Action Case

Due to the COVID-19 restrictions, on-site Incident Commander (IC) practical training and examinations in Sweden were canceled as of March 2020. The graduation of one IC class was, however, conducted through Remote Virtual Simulation (RVS), the first such examination to our current knowledge. This paper presents the necessary enablers for setting up RVS and its influence on cognitive aspects of assessing practical competences. Data were gathered through observations, questionnaires, and interviews from students and instructors, using action-case research methodology. The results show the potential of RVS for supporting higher cognitive processes, such as recognition, comprehension, problem solving, decision making, and allowed students to demonstrate whether they had achieved the required learning objectives. Other reported benefits were the value of not gathering people (imposed by the pandemic), experiencing new, challenging incident scenarios, increased motivation for applying RVS based training both for students and instructors, and reduced traveling (corresponding to 15,400 km for a class). While further research is needed for defining how to integrate RVS in practical training and assessment for IC education and for increased generalizability, this research pinpoints current benefits and limitations, in relation to the cognitive aspects and in comparison, to previous examination formats.

Design of Marine Data Warehouse ETL System

2014 ◽  
Vol 668-669 ◽  
pp. 1374-1377 ◽  
Author(s):  
Wei Jun Wen
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Data Warehouse ◽  
Environmental Data ◽  
Data Sources ◽  
Quality Data ◽  
Critical Step ◽  
Marine Data ◽  
Data Extracting ◽  
Marine Environmental

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

Universal Data Warehousing Based on a Meta-Data Modeling Approach

2003 ◽  
Vol 12 (03) ◽  
pp. 325-363 ◽  
Author(s):  
Joseph Fong ◽  
Qing Li ◽  
Shi-Ming Huang
Keyword(s):  
Data Warehouse ◽  
Data Warehousing ◽  
Object Oriented ◽  
Data Models ◽  
Heterogeneous Databases ◽  
Materialized Views ◽  
Prototype System ◽  
Relational View ◽  
Metadata Model ◽  
Star Schema

Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.

Three-Dimensional Engineering Geology Data Warehouse Constructed by Power Designer

2013 ◽  
Vol 753-755 ◽  
pp. 3112-3115
Author(s):  
Jing Li Huang ◽  
Qing Wang ◽  
Qiu Ling Lang
Keyword(s):  
Data Base ◽  
Data Warehouse ◽  
Data Model ◽  
Engineering Geology ◽  
Three Dimensional ◽  
Soil Mass ◽  
Design Model ◽  
Underground Space ◽  
Geological Data ◽  
Rock And Soil

The Three-dimensional engineering geology data warehouse is constructed by Power Desinger16.1, with the theme as the rock and mass availability in urban underground space, and with the source data as the borehole data of engineering Investigation. Use the Model-driven Architecture method, reverse engineer the Access data base, extract existed data model, combine research theme to construct the Star data structure model. And check the SQL script in SQL Server2005, to ensure normal operation. 0 Forewords The traditional transaction-oriented designed engineering geology data base has the function to storage original data from work, to draw of geological section and to provide simple check and analysis, but without the decision support function in view of a subject. The purpose of construction a 3D engineering geological data warehouse is to build a decision support system in view of availability of rock and soil mass in urban underground space. Based on the data extraction, data integration, data cleaning and data transformation, the 3D engineering geological data warehouse could achieve the integrated management of massive geological data and to provide reliable data source for the rock and soil mass utilization system in urban underground space. The main feature of 3D engineering geological data base is subject-oriented, integrated, time-varying, relatively stable, and is magnanimous collection of engineering geological spatial data and attribute data. According to the design pattern of traditional data base, the construction of 3D engineering geological data warehouse can be divided into three stages: concept design model, logic design model and physical design model. But the 3D engineering geological data warehouse exist iterative in the construction process. Currently, there are many CASE tools to help developers quickly achieving the data base design, such as Rational Rose by Rational company, Erwin and Bpwin by CA company, Power Designer by Sybase company, Office Visio by Microsoft company, and Oracle Designer by Oracle company. The paper uses the Powerdesigner16.1 to achieve the logical data model (LDM) and physical data model (PDM).

A Research Methodology Based on Design Science for the Construction of Cognitive Maps: The Case of a Chinese Steel Company’s Strategic Decision Making

2011 ◽  
Vol 204-210 ◽  
pp. 2098-2102 ◽  
Author(s):  
Ying Hong Zhong ◽  
Hong Wei Liu
Keyword(s):  
Decision Making ◽  
Research Methodology ◽  
Design Science ◽  
Business Environment ◽  
Cognitive Map ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Wicked Problem ◽  
Senior Executives ◽  
Cognitive Decision

In turbulent business environment, executives’ cognition plays an important role in their understanding and the process of decision making. Cognitive map helps the senior executives in their thought process. The construction of information-based cognitive map, however, is a wicked problem, which could hardly be tackled by hard systems methodologies. Design science provides a good solution. This paper puts forward a research methodology, which is divided into six activities, to build up an information systems (IS) based cognitive map for cognitive decision support. The methodology is demonstrated by a case study of a Chinese steel company’s strategic decision making.

scholarly journals Indonesian traveler study: analyze the role of the big five personalities on hard adventure traveler type

2020 ◽  
Vol 2 (2) ◽  
pp. 83-94
Author(s):  
Lusy Asa Akhrani ◽  
◽  
Chintya Fatima Dewi ◽  
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Big Five ◽  
Research Methodology ◽  
Sampling Technique ◽  
Personality Types ◽  
Big Five Personality ◽  
Tourist Attraction ◽  
Regression Techniques

Purpose: This study aims to determine the role of big five personalities simultaneously and partially towards the tendency of hard adventure travelers. Research methodology: This study will also look at the five traits found in the big five personalities which tend to play a role in the hard adventure traveler. This research is a replication study of Kristin Scott and John C. Mowen with a quantitative approach involving 1,558 subjects with a purposive sampling technique. Big five personality was measured using the big five infentory scale, while the hard adventure type would be measured using a scale from Scott & Mowen. Data analysis of this study using multiple regression techniques. Results: The results showed that there is a role of big five personalities that is simultaneous towards traveler's hard adventure type of 7,6%, whereas partially openness, extraversion, and neuroticism trait had a role towards the type of hard adventure, where openness trait had the biggest role towards hard adventure type. Limitations: Based on the magnitude of the role generated in this study, there are still other factors that can influence traveler's decision making to choose the traveling type, so that these other factors are expected to explore more. Contribution: This research can be a reference in the development of tourist attraction marketing by taking into account visitors' personality types.

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