Rancangan Desain Data Warehouse Kunjungan Wisatawan Ke Bali Baw Tour & Travel

This business development in the globalized era provoked fierce competition especially with the application of it to support his daily process especially in data management, therefore, the BAW Tour & Travel needs a system for data processing so that data can be stored and integrated with each other or what's called data warehouse and followed by other regulatory ETL, OLAP methods in analysis and quick decision-making. Using the data warehouse can figure out a spike in visitors' visits so it can predict people to be able to predict the number of guides during a month in case there's a spike that reduces anyone's denial of acceptance on the grounds of lack of a guide and to booked a motel because it's already full.

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Structuring and visualization of indicators in multidimensional data cubes

Informacionno-technologicheskij vestnik ◽

10.21499/2409-1650-2018-4-79-87 ◽

2018 ◽

pp. 79-87

Author(s):

E. E. Akimkina

Keyword(s):

Decision Making ◽

Data Processing ◽

Data Management ◽

Multidimensional Data ◽

End User ◽

Processing Technologies ◽

Data Cubes ◽

Multidimensional Visualization ◽

Multidimensional Data Cubes ◽

Practical Recommendations

The problems of structuring of indicators in multidimensional data cubes with their subsequent processing with the help of end-user tools providing multidimensional visualization and data management are analyzed; the possibilities of multidimensional data processing technologies for managing and supporting decision making at a design and technological enterprise are shown; practical recommendations on the use of domestic computer environments for the structuring and visualization of multidimensional data cubes are given.

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Study on Data Warehouse Based Equipment Support Data Management

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.462-463.1072 ◽

2013 ◽

Vol 462-463 ◽

pp. 1072-1075

Author(s):

Feng Xie ◽

Jiang Sheng Sun ◽

Wei Jie Liang ◽

Dong Sheng Dai

Keyword(s):

Decision Making ◽

Data Management ◽

Data Warehouse ◽

Heterogeneous Data ◽

Data Partitioning ◽

Point Of View ◽

Data Management System ◽

Management Systems ◽

Equipment Management ◽

Data Granularity

There are more and more data produced in equipment management systems. For decision making, we must collect and integrate all kinds of data and information from different management systems. By analyzing the distributional and heterogeneous data resources, the architecture of equipment management data warehouse is proposed in this paper. We discussed important components of data warehouse for equipment support. The components include metadata, data market, data granularity and data partitioning. By discussing the organization of the data warehouse from the macroscopic point of view, the equipment support data management system with the function of decision making will be used in the future.

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

Equilibrium ◽

10.12775/equil.2009.016 ◽

2009 ◽

Vol 2 (1) ◽

pp. 171-180

Author(s):

Michał Kukliński

Keyword(s):

Decision Making ◽

Data Processing ◽

Data Warehouse ◽

Business Intelligence ◽

Data Warehouses ◽

Economic Decisions ◽

Business Intelligence Systems ◽

Effective Decision ◽

Effective Decision Making ◽

Answering Questions

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

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APPLIED DATA WAREHOUSE AND DATA VISUALIZATION IN AQUACULTURE DATA MANAGEMENT IN TRA VINH PROVINCE

Scientific Journal of Tra Vinh University ◽

10.35382/18594816.1.28.2017.47 ◽

2017 ◽

Vol 1 (28) ◽

pp. 64-73

Author(s):

An Bao Nguyen ◽

Lam Nhut Nguyen ◽

Vi Thi Thuy Ha

Keyword(s):

Decision Making ◽

Information System ◽

Data Analysis ◽

Data Management ◽

Data Warehouse ◽

Data Visualization ◽

Sql Server ◽

Microsoft Excel

This paper introduces an information system developed to maintain data management and reporting on aquaculture in Tra Vinh province. A data warehouse was also built for data analysis and visualization in order to produce general reports and charts that help the managers in decision making. The proposed system was built using .NET technology, Microsoft SQL Server 2014 DBMS, Microsoft SQL Analysis Services and OLAP features of Microsoft Excel 2013

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Applying Deep Learning to Audit Procedures: An Illustrative Framework

Accounting Horizons ◽

10.2308/acch-52455 ◽

2019 ◽

Vol 33 (3) ◽

pp. 89-109 ◽

Cited By ~ 9

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.

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Design of Marine Data Warehouse ETL System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.668-669.1374 ◽

2014 ◽

Vol 668-669 ◽

pp. 1374-1377 ◽

Cited By ~ 1

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.

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