Implementasi Pengembangan Sistem Model Water Fall Untuk Data Warehouse Akademik

Data warehouse is a concept and a technology to store transactional data from several sources that have been through the process of filtering and selection of data. By using the Ectract, Transform and Load (ETL) process in the data warehouse, OLTP data is processed to produce good data and ready for use for the analysis process. For the design of this warehouse data will be built by using the Nine Step Method from Kimbal, so that the resulting warhouse data can be as expected. For the development of life flow system (SDLC) with waterfall model. By using the wate fall model will be built a prototype to implement the data warehouse design results.

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Desain Dan Implementasi Data Warehouse Pada Perpustakaan Daerah Provinsi Sumatera Selatan

Jurnal Nasional Ilmu Komputer ◽

10.47747/jurnalnik.v2i1.520 ◽

2021 ◽

Vol 2 (1) ◽

pp. 33-50

Author(s):

Nia Adila ◽

Andri Andri

Keyword(s):

Data Warehouse ◽

Data Storage ◽

Storage System ◽

Data Retrieval ◽

Design Stage ◽

Process Selection ◽

Step Method ◽

Analysis Process ◽

Data Book ◽

Data Member

This research will focus on processing visitor data, member data, book borrowing data and book return data at the Regional Library of South Sumatra Province. The data is stored in the form of an excel file with a large amount of data, causing problems in the storage system such as data accumulation, data loss, no data analysis and delays in the reporting process. The process of data storage and data retrieval will be well integrated by building a data Warehouse at the Regional Library of South Sumatra Province. Data Warehouse is a system that contains several years of history and facilitates decision making. At the data Warehouse design stage using the Nine-Step method (Kimball, 2002), in this method there are nine steps in designing a data Warehouse, namely Process Selection, Grain Selection, Identification of dimensional adjustments, Fact Selection, Storage of initial calculations in the fact table, Reviewing the dimension table, selecting the database duration, tracking dimension changes, and prioritizing, querying the model and selecting the physical design. And the design and data processing process will use the Pentaho kettle and public Tableau applications, with the design and implementation of the data Warehouse, it is expected to help facilitate the reporting and analysis process for the Regional Library of South Sumatra Province.

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Implemetasi Data Warehouse pada Bagian Pemasaran Perguruan Tinggi

ComTech Computer Mathematics and Engineering Applications ◽

10.21512/comtech.v3i1.2417 ◽

2012 ◽

Vol 3 (1) ◽

pp. 315

Author(s):

Eka Miranda ◽

Rudy Rudy ◽

Eli Suryani

Keyword(s):

Higher Education ◽

Decision Making ◽

Data Warehouse ◽

Ad Hoc ◽

External Data ◽

Study Results ◽

Marketing Activities ◽

Warehouse Design ◽

Transactional Data ◽

Support Decision Making

Transactional data are widely owned by higher education institutes, but the utilization of the data to support decision making has not functioned maximally. Therefore, higher education institutes need analysis tools to maximize decision making processes. Based on the issue, then data warehouse design was created to: (1) store large-amount data; (2) potentially gain new perspectives of distributed data; (3) provide reports and answers to users’ ad hoc questions; (4) perform data analysis of external conditions and transactional data from the marketing activities of universities, since marketing is one supporting field as well as the cutting edge of higher education institutes. The methods used to design and implement data warehouse are analysis of records related to the marketing activities of higher education institutes and data warehouse design. This study results in a data warehouse design and its implementation to analyze the external data and transactional data from the marketing activities of universities to support decision making.

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Why is the snowflake schema a good data warehouse design?

Information Systems ◽

10.1016/s0306-4379(02)00021-2 ◽

2003 ◽

Vol 28 (3) ◽

pp. 225-240 ◽

Cited By ~ 58

Author(s):

Mark Levene ◽

George Loizou

Keyword(s):

Data Warehouse ◽

Good Data ◽

Warehouse Design

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Desain Data Warehouse pada Sistem Informasi Sumber Daya Manusia Sub-Sistem Rekrutmen

ComTech Computer Mathematics and Engineering Applications ◽

10.21512/comtech.v3i1.2416 ◽

2012 ◽

Vol 3 (1) ◽

pp. 307

Author(s):

Eka Miranda

Keyword(s):

Decision Making ◽

Resource Management ◽

Data Warehouse ◽

High Performance ◽

Ad Hoc ◽

Process Efficiency ◽

Literature Study ◽

Recruitment Activities ◽

Warehouse Design ◽

Transactional Data

Employees as a resource management are essential to improve the effectiveness of company’s performance and process efficiency. This paper discusses the implementation of data warehouse and its role in assisting the decision making related to recruitment activities undertaken by Human Resources Department. In this research built a data warehouse design to store large amounts of data and to gain potentially a new perspective of data distribution as well as to provide reports and solutions for users the ad hoc question and to analyze the transactional data. This study aims to design a data warehouse to support accurate decision making related to human resource management in order to create high performance productivity. The method used in this paper consists of: (1) data collection using interview and literature study related to employee recruitment and (2) data warehouse design derived from Teh Ying Wah et al. This research results in a data warehouse design and its implementation to analyze transactional data from the related activities of recruitment and employee management to support decision making.

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Development of Thermal Performance Metrics for Direct Gas-Fired Circulating Heaters

Agriculture ◽

10.3390/agriculture11070588 ◽

2021 ◽

Vol 11 (7) ◽

pp. 588

Author(s):

Benjamin C. Smith ◽

Brett C. Ramirez ◽

Steven J. Hoff

Keyword(s):

Mass Flow ◽

Measurement System ◽

Thermal Efficiency ◽

Performance Metrics ◽

Standardized Test ◽

Flow System ◽

Standard Test ◽

Testing System ◽

Measurement Systems ◽

Selection Of

Many climate-controlled agricultural buildings use direct gas-fired circulating heaters (DGFCH) for supplement heat. There is no standardized test to calculate thermal efficiency for these heaters. This study aimed to develop a measurement system and analytical analysis for thermal efficiency, quantify the measurement uncertainty, and assess economics of DGFCH efficiency. The measurement system developed was similar to the ASHRAE 103 standard test stand with adaptations to connect the apparatus to the DGFCH. Two different propane measurement systems were used: input ratings < 30 kW used a mass flow system and input ratings > 30 kW used a volumetric gas meter. Three DGFCHs (21.9, 29.3, 73.3 kW) were tested to evaluate the system. Thermal efficiencies ranged from 92.4% to 100.9%. The resulting uncertainty (coverage factor of 2; ~95% Confidence Interval) ranged from 13.1% to 30.7% for input ratings of 56.3 to 11.4 kW. Key sources of uncertainty were propane and mass flow of air measurement. The economic impact of 1% difference in thermal efficiency ranged from USD $61.3 to $72.0 per heating season. Refinement of the testing system and procedures are needed to reduce the uncertainty. The application of this system will aid building designers in selection of DGFCHs for various applications.

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