Data transformation (computing): Difference between revisions

Revision as of 10:03, 1 August 2023

Revision as of 11:00, 1 August 2023

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The steps can be described as follows:

'''Data discovery''' is the first step in the data transformation process. Typically the data is profiled using profiling tools or sometimes using manually written profiling scripts to better understand the structure and characteristics of the data and decide how it needs to be transformed.<ref>{{Cite web |last=Meeks |first=Travis |date=2023-03-30 |title=Data & Predictive Analytics in Insurance: Clients vs. Prospects |url=https://analytics-iq.com/data-and-predictive-analytics-in-insurance-targeting-clients-vs-prospects/ |access-date=2023-08-01 |website=AnalyticsIQ |language=en-US}}</ref>

'''Data mapping''' is the process of defining how individual fields are mapped, modified, joined, filtered, aggregated etc. to produce the final desired output. Developers or technical data analysts traditionally perform data mapping since they work in the specific technologies to define the transformation rules (e.g. visual [[Extract, transform, load|ETL]] tools,<ref>DWBIMASTER. Top 10 ETL Tools. Retrieved from: http://dwbimaster.com/top-10-etl-tools/ {{Webarchive|url=https://web.archive.org/web/20170829035105/http://dwbimaster.com/top-10-etl-tools/ |date=2017-08-29 }}</ref> transformation languages).