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DC Field | Value | Language |
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dc.contributor.author | Runtuwene, Julyeta P. A. | - |
dc.contributor.author | Tangkawarow, Irene R. H. T. | - |
dc.contributor.author | Manoppo, C T M | - |
dc.contributor.author | Salaki, R J | - |
dc.date.accessioned | 2019-12-19T02:56:28Z | - |
dc.date.available | 2019-12-19T02:56:28Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/363 | - |
dc.description | Conference | en_US |
dc.description.abstract | The current growth of data and information occurs rapidly in varying amount and media. These types of development will eventually produce large number of data better known as the Big Data. Business Intelligence (BI) utilizes large number of data and information for analysis so that one can obtain important information. This type of information can be used to support decision-making process. In practice a process integrating existing data and information into data warehouse is needed. This data integration process is known as Extract, Transformation and Loading (ETL). In practice, many applications have been developed to carry out the ETL process, but selection which applications are more time, cost and power effective and efficient may become a challenge. Therefore, the objective of the study was to provide comparative analysis through comparison between the ETL process using Microsoft SQL Server Integration Service (SSIS) and one using Pentaho Data Integration (PDI). | en_US |
dc.language.iso | en | en_US |
dc.publisher | IOP Publishing | en_US |
dc.relation.ispartofseries | IOP Conf. Series: Materials Science and Engineering 306 (2018) 012066; | - |
dc.title | Comparative Analysis of Extract, Transformation and Loading (ETL) Process | en_US |
dc.type | Article | en_US |
Appears in Collections: | Lecturer Scientific Papers |
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