Data extract transform and load, normally referred to as ETL, is a process that many people have used, although they may not have realized it at the time or even known what it was called. This process is used whenever data is pulled from a source, formatted into a method that fits the desired storage system, and then placed directly into that specific storage system. Many companies make use of data integration and ETL software today to handle the large amounts of data that they work with on a regular basis.
How It Works
ETL can be broken down into three different phases. First comes data extraction, which involves withdrawing the required data from the original data source. This can include pulling all of the data or only selected pieces of data, depending on what the user needs. This is the most important part of ETL because if the data is not extracted correctly, if some data is missing, or if extraneous data gets added unintentionally, it can result in the data being rendered useless or too difficult to sift through.
Next come the transformation phase formats, where the individual configures the extracted data so that it can be useful. This includes formatting it for storage in a spreadsheet, database, or other data storage method. This may mean applying a number of different rule sets to the data so that it can be loaded correctly into the target structure. Some data may not need to be transformed in any way.
Finally, the loading portion of ETL involves loading the transformed data into a database, data warehouse, CSV, or any other final location. Depending on what the user needs, this process may require overwriting existing data, adding data to an existing file or database, or filling a blank file or database with the new information.
In many cases involving large amounts of data, ETL processes are done in parallel. As data is extracted, it is transformed and then loaded into the target storage structure. This saves time and reduces the amount of transitional memory used, since only some of the data is being transformed rather than all of it being held in memory during this phase. Running ETL through one platform like Adeptia’s data integration solutions does is another way to make the process simpler and more efficient.
Many people look to an integration suite of software for ETL to help reduce the overall issues and difficulties that are inherent in this process. While designers often create an ETL process with a certain amount of data in mind, that data may grow over the years. The process may not be able to handle a very large amount of extraction data, plus the source file may become bloated and slow down search and access times. The data range may also expand over time, leading to the need to extract and save much more data than what was originally planned.
Using data integration software, it’s very easy to modify the ETL process to handle all of these shortcomings. Data can be quickly validated as it is extracted, ensuring that the final data file contains error-free information that the user can take advantage of.