scholarly journals DataWarehouse Design Acceptance of Goods In PT Transmart Using Tools Pentaho and Tableu

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Syam Gunawan
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Design Method ◽  
Graphical Display ◽  
Central Park ◽  
Purchase Order ◽  
Analytical Processing ◽  
Points Of View ◽  
Existing Data ◽  
Analyze Data

The purpose of this research is to process the data of receipt of goods at PT Transmart Central Park, analyze the existing database in the information system of receipt of goods to get the necessary information and design the data warehouse to integrate the existing data so that obtained information to take a decision. Business Intelligence (BI) is one of information technology that can be solution to collect, store and analyze company data. Online Analytical Processing (OLAP) consists of a set of tools in use to help the process of analysis and comparison of data in the database. OLAP tools and methods help users analyze data in a data warehouse by providing a variety of dynamic graphical display data. The data warehouse design method is implemented by applying the 9 steps (Nine-Step Methodology) used by Ralph Kimball in designing the star scheme. The results achieved are data warehouse that provides the desired information and provide summary information in the form of tables and charts, can be compared between the purchase order data with receiving report is global, relevant, and integrated that can be seen from various points of view so useful for the leaders to make a decision.Keywords  : Bussinesn Intelligent,Datawarehouse,OlapNine-Step Methodology

Evolutionary Intelligent Data Warehousing Approach to Knowledge Discovery Systems: Dynamic Cubing

2019 ◽  
Vol 13 ◽  
Author(s):  
Harkiran Kaur ◽  
Kawaljeet Singh ◽  
Tejinder Kaur
Keyword(s):  
Knowledge Discovery ◽  
Data Warehouse ◽  
Business Intelligence ◽  
End Users ◽  
Processing Stage ◽  
Information Update ◽  
On Line ◽  
Analytical Processing ◽  
Warehouse Operations ◽  
Made In

Background: Numerous E – Migrants databases assist the migrants to locate their peers in various countries; hence contributing largely in communication of migrants, staying overseas. Presently, these traditional E – Migrants databases face the issues of non – scalability, difficult search mechanisms and burdensome information update routines. Furthermore, analysis of migrants’ profiles in these databases has remained unhandled till date and hence do not generate any knowledge. Objective: To design and develop an efficient and multidimensional knowledge discovery framework for E - Migrants databases. Method: In the proposed technique, results of complex calculations related to most probable On-Line Analytical Processing operations required by end users, are stored in the form of Decision Trees, at the pre- processing stage of data analysis. While browsing the Cube, these pre-computed results are called; thus offering Dynamic Cubing feature to end users at runtime. This data-tuning step reduces the query processing time and increases efficiency of required data warehouse operations. Results: Experiments conducted with Data Warehouse of around 1000 migrants’ profiles confirm the knowledge discovery power of this proposal. Using the proposed methodology, authors have designed a framework efficient enough to incorporate the amendments made in the E – Migrants Data Warehouse systems on regular intervals, which was totally missing in the traditional E – Migrants databases. Conclusion: The proposed methodology facilitate migrants to generate dynamic knowledge and visualize it in the form of dynamic cubes. Applying Business Intelligence mechanisms, blending it with tuned OLAP operations, the authors have managed to transform traditional datasets into intelligent migrants Data Warehouse.

scholarly journals Business intelligence for social media interaction in the travel industry in Indonesia

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Michael Yulianto ◽  
Abba Suganda Girsang ◽  
Reinert Yosua Rumagit
Keyword(s):  
Social Media ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Marketing Activity ◽  
Social Media Data ◽  
Current Technology ◽  
Media Interaction ◽  
Travel Industry ◽  
Media Data ◽  
Analyze Data

Electronic ticket (eticket) provider services are growing fast in Indonesia, makingthe competition between companies increasingly intense. Moreover, most of them have the sameservice or feature for serving their customers. To get back the feedback of their customers, manycompanies use social media (Facebook and Twitter) for marketing activity or communicatingdirectly with their customers. The development of current technology allows the company totake data from social media. Thus, many companies take social media data for analyses. Thisstudy proposed developing a data warehouse to analyze data in social media such as likes,comments, and sentiment. Since the sentiment is not provided directly from social media data,this study uses lexicon based classification to categorize the sentiment of users’ comments. Thisdata warehouse provides business intelligence to see the performance of the company based ontheir social media data. The data warehouse is built using three travel companies in Indonesia.As a result, this data warehouse provides the comparison of the performance based on the socialmedia data.

Data Warehouse and Business Intelligence Systems in the Context of E-HRM

2009 ◽  
pp. 223-229
Author(s):  
Martin Burgard ◽  
Franca Piazza
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Resource Management ◽  
Human Resource Management ◽  
Data Warehouse ◽  
Human Resource ◽  
Business Intelligence ◽  
Multidimensional Data ◽  
Business Intelligence Systems ◽  
Analytical Processing

The increased use of information technology leads to the generation of huge amounts of data which have to be stored and analyzed by appropriate systems. Data warehouse systems allow the storage of these data in a special multidimensional data base. Based on a data warehouse, business intelligence systems provide different analysis methods such as online analytical processing (OLAP) and data mining to analyze these data. Although these systems are already widely used and the usage is still growing, their application in the area of electronic human resource management (e-HRM) is rather scarce. Therefore, the objective of this article is to depict the components and functionality of these systems and to illustrate the application possibilities and benefits of these systems by selected application examples in the context of e-HRM.

scholarly journals Mapping Student Data Using Data Warehouse for Promotion at Vocational High School of Z

2020 ◽  
Vol 3 (2) ◽  
pp. 55
Author(s):  
Khoirudin Eko Nurcahyo ◽  
Sucipto Sucipto ◽  
Arie Nugroho
Keyword(s):  
High School ◽  
Data Warehouse ◽  
Junior High School ◽  
Business Intelligence ◽  
Junior High ◽  
Vocational High School ◽  
Dimensional Modeling ◽  
Education Organization ◽  
Using Data ◽  
Analyze Data

<em>The purpose of this study is provide data warehouse modeling which make executive of school can analyze data easily, the problem is executive of school are analysis list registrant list difficulty, what the most and least registrant junior high school come from and the major which most and least registrant. This study do is because how important data management on education organization and how the data can be managed better. The study use descriptive quantitative method research and use 4 step data warehouse dimensional modeling by Kimball. On building data warehouse used ETL, data be extracted and transformed into data warehouse as dimension and fact. For next data be imported and be showed by web base business intelligence app. The result of this study is an web base business intelligence app which can show sum of registrant on gender, majors, junior high school graduate come from, recommendation and register year. Data warehouse is good at data analyzing for decision making, because data warehouse can show information quickly and accurate.</em>

scholarly journals Procesamiento Analítico con Minería de Datos / Analytical Processing with Data Mining

2016 ◽  
Vol 5 (9) ◽  
pp. 22
Author(s):  
Angelino Feliciano Morales ◽  
René Edmundo Cuevas Valencia ◽  
José Mario Martínez Castro
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Business Intelligence ◽  
El Sistema ◽  
Toma De Decisiones ◽  
Analytical Processing

Este trabajo describe la utilidad e importancia de la herramienta OLAP en Business Intelligence con el fin de recomendarla a los administradores de empresas para su toma de decisiones. La tecnología OLAP permite el rápido acceso a datos mediante data warehouse, agilizando el analisis de la información. Los cubos proveen de un rápido mecanismo de búsqueda de datos y de un tiempo de respuesta uniforme, independientemente de la cantidad de datos o de la complejidad del procedimiento de búsqueda. Tomando en cuenta su funcionamiento y estructura, el sistema OLAP se clasifica en tres categorías: ROLAP, MOLAP y HOLAP. Actualmente el sistema OLAP que más se utiliza es el denominado ROLAP.

Data Warehouse and Business Intelligence Systems in the Context of E-HRM

2011 ◽  
pp. 1013-1020
Author(s):  
Martin Burgard ◽  
Franca Piazza
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Resource Management ◽  
Human Resource Management ◽  
Data Warehouse ◽  
Human Resource ◽  
Business Intelligence ◽  
Multidimensional Data ◽  
Business Intelligence Systems ◽  
Analytical Processing

The increased use of information technology leads to the generation of huge amounts of data which have to be stored and analyzed by appropriate systems. Data warehouse systems allow the storage of these data in a special multidimensional data base. Based on a data warehouse, business intelligence systems provide different analysis methods such as online analytical processing (OLAP) and data mining to analyze these data. Although these systems are already widely used and the usage is still growing, their application in the area of electronic human resource management (e-HRM) is rather scarce. Therefore, the objective of this article is to depict the components and functionality of these systems and to illustrate the application possibilities and benefits of these systems by selected application examples in the context of e-HRM.

scholarly journals Business Intelligence in the Service of Libraries

2019 ◽  
Vol 38 (4) ◽  
pp. 98-113
Author(s):  
Danijela Tešendić ◽  
Danijela Boberić Krstićev
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Management System ◽  
User Requirements ◽  
Library Management ◽  
Library Management System ◽  
Transactional Databases ◽  
Complete Procedure ◽  
Analytical Processing

This paper describes implementation of business intelligence tools in the libraries. A complete procedure for building a data warehouse is described on the case study of the BISIS library management system. During development of a data warehouse model, user requirements about reporting are detected and structure of already existing transactional databases in the BISIS system is analysed. Based on this analysis, three data warehouse models have been proposed that would satisfy the requirements for analytical processing of data. The paper presents the usage of one OLAP tool, but the proposed data warehouse model is independent of the choice of OLAP tools and any other tool can be integrated with the proposed data warehouse.

scholarly journals Perancangan Data Warehouse Pada Software Laboratory Center

2010 ◽  
Vol 1 (2) ◽  
pp. 585
Author(s):  
Alvin Chandra
Keyword(s):  
Data Warehouse ◽  
System Analysis ◽  
Design Method ◽  
Global Information ◽  
Strategic Decisions ◽  
Design Data ◽  
Analysis And Design ◽  
Running System ◽  
Star Schema ◽  
Points Of View

The purpose of this study is to analyze the existing database on Software Laboratory Center to obtain necessary information and design data warehouse to integrate existing data to obtain some global information. The methods used are analysis and design method. The method of analysis is done by conducting surveys and analysis of the running system, analysis and identification the weaknesses of the running system, and troubleshooting analysis. And the data warehouse design method is done by applying the nine steps (Nine-Step Methodology) that used by Ralph Kimball's to design star schema. The result is data warehouse that provides some global information which global, relevant, and integrated which can be seen from various points of view that is useful for the leaders to make decisions. Separate data warehouse from operational databases that already exist required by Software Laboratory Center to assist leaders in making strategic decisions in a fast and precise way. 

scholarly journals Metadata for Approximate Query Answering Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Francesco Di Tria ◽  
Ezio Lefons ◽  
Filippo Tangorra
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Query Answering ◽  
Approximate Query Processing ◽  
Web Based ◽  
Approximate Query Answering ◽  
Business Intelligence Systems ◽  
Approximate Query ◽  
Analytical Processing ◽  
The Common

In business intelligence systems, data warehouse metadata management and representation are getting more and more attention by vendors and designers. The standard language for the data warehouse metadata representation is the Common Warehouse Metamodel. However, business intelligence systems include also approximate query answering systems, since these software tools provide fast responses for decision making on the basis of approximate query processing. Currently, the standard meta-model does not allow to represent the metadata needed by approximate query answering systems. In this paper, we propose an extension of the standard metamodel, in order to define the metadata to be used in online approximate analytical processing. These metadata have been successfully adopted in ADAP, a web-based approximate query answering system that creates and uses statistical data profiles.

scholarly journals Uma proposta de aplicação de business intelligence no chão-de-fábrica

2005 ◽  
Vol 12 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Marcos Roberto Fortulan ◽  
Eduardo Vila Gonçalves Filho
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

A evolução do chão-de-fábrica tem sido significativa nas últimas décadas, quando grandes investimentos têm sido realizados em infra-estrutura, automação, treinamento e sistemas de informação, transformando-o numa área estratégica para as empresas. O chão-de-fábrica gera hoje grande quantidade de dados que, por estarem dispersos ou desorganizados, não são utilizados em todo o seu potencial como fonte de informação. Com vistas nessa deficiência, este trabalho propõe a implantação de um sistema de Business Intelligence por meio do uso de ferramentas de Data Warehouse e OLAP (On-Line Analytical Processing), aplicadas especificamente ao chão-de-fábrica. O objetivo é desenvolver um sistema que utilize os dados resultantes do processo produtivo e os transforme em informações que auxiliem o gerente na tomada de decisões, de forma a garantir a competitividade da empresa. Um protótipo foi construído com dados simulados para testar a proposta.

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