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International Journal of Engineering Applied Sciences and Technology, 2018 Vol. 3, Issue 7, ISSN No. 24552143, Pages 9097 Published Online November 2018 in IJEAST (http://www.ijeast.com)PRIVACY PRESERVATION
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How to fill out extraction transformation and loading

01
Identify the data sources you want to extract data from.
02
Define the data transformation logic needed to clean, filter, and format the data.
03
Set up the necessary tools or scripts to perform the extraction, transformation, and loading processes.
04
Extract the data from the source systems using the defined logic.
05
Transform the extracted data according to the defined transformation logic.
06
Load the transformed data into the target destination, such as a data warehouse or database.
07
Monitor and validate the ETL process to ensure data accuracy and completeness.

Who needs extraction transformation and loading?

01
Companies or organizations that want to integrate and consolidate data from multiple sources.
02
Data analysts and data scientists who need clean and structured data for analysis.
03
Business intelligence teams that require accurate and timely reporting for decision-making.
04
Data engineers responsible for building and maintaining data pipelines and ETL processes.
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Extraction Transformation and Loading (ETL) is a process in data warehousing that involves extracting data from various sources, transforming it to fit operational needs, and loading it into the end target (database, data warehouse, etc.) for analysis and reporting.
Data analysts, data engineers, and other professionals involved in managing data for an organization are typically responsible for the extraction transformation and loading process.
To fill out extraction transformation and loading, one must first extract data from multiple sources, transform it to meet specific requirements, and then load it into a destination for further analysis.
The purpose of extraction transformation and loading is to ensure that data is cleansed, integrated, and stored in a format that is suitable for analysis and reporting.
Information such as source data locations, data transformation rules, target database specifications, and data loading schedules must be reported on extraction transformation and loading.
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