Parallel Data Extraction from Multiple Data Source in ExtractionTransformation-Loading (ETL) Process

Authors

  • Mr. JANI HARSH M M.Tech CE Department of Computer Engineering C U Shah College of Engineering & Technology, Gujarat, India.
  • Asst. Pro. Ms. VIRAL A PAREKH Department of Computer Engineering C U Shah College of Engineering & Technology, Gujarat, India.

Keywords:

Data Warehouse, ETL Process, Parallel Data Extraction, Multiple Data Source.

Abstract

Information is very important in all the fields. This information is collected from Data
Warehouse. Extraction-Transformation-Loading (ETL) Process is used to fill Data
Warehouse. In Data Warehouse, data is extracted from multiple data sources. Now a day’s
data is extracted from one data source at that time other data sources is ideal. After
completion of extraction from one data source, second data source will be introduced for
data extraction. This process is very time consuming. This paper proposes parallel data
extraction method to optimize ETL. The proposed method is an all-in-one solution that
supports processing different types of data from operational systems. This method improves
ETL flexibility and increase the speed of extraction to the data warehouse. This paper
evaluates the proposed method empirically, which shows that it is more efficient and less
intrusive than the standard ETL method

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Published

2017-04-25

How to Cite

Mr. JANI HARSH M, & Asst. Pro. Ms. VIRAL A PAREKH. (2017). Parallel Data Extraction from Multiple Data Source in ExtractionTransformation-Loading (ETL) Process. International Journal of Advance Research in Engineering, Science & Technology, 4(4), 705–713. Retrieved from https://ijarest.org/index.php/ijarest/article/view/1290

Issue

Vol. 4 No. 4 (2017): Volume: 04, Issue: 04 - April, 2017.

Section

Articles