The ETL Process

The ETL Process:

       What is ETL?

ETL is an acronym for a process known as extract, transform, and load. It is especially used within databases and data warehousing. The extracting comes from the function of pulling data from homogenous or heterogeneous data sources. ETL then transforms the data and stores it in a proper format for analysis purposes. The final stage is loading the data into either a an operational data store, a data mart, or a data warehouse.

These three process’s are normally run at the same time since data acquisition is normally a lengthy process. This combination of processes allows data to be stored more efficiently as the processes do not wait for each other to be finished.

Extraction is normally seen as the pivotal aspect of ETL since extracting the data properly can negatively or positively effect the rest of the processes. Most projects utilizing ETL grab data from multiple sources to vary their results. However this also requires data validation as the data is confirmed against expected values.

Once the Data has reached the transformation stage as series of stages are applied to identify what classifications the data meets. Some data doesn’t require a transformation at all, these are referred to as “direct move” data. Finally the load stage takes any and all data and properly files it away.

      Where Does ETL fit in a Business Standpoint?

ETL is essentially how you tell your system of customer information who you want to look for and their traits that will link them to other like minded individuals. This is key when employing marketing techniques as you can reduce the cost of your marketing campaign by centralizing the advertisement in areas with a high number of probable buyers rather then marketing toward everyone, including non prospective buyers. This reduced cost for marketing coupled with a higher chance to increase sales is quite worth the time and effort to isolate your consumer base and an ETL system helps save time and money doing so.