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Forum post in BI General: Re: What is the difference between ETTL and ETL
https://forums.sdn.sap.com/thread.jspa?threadID=366021&messageID=3253858#3253858
hi
for ETL
ETL: Extracting , transforming and loading is the process of reading (extracting) from heterogeneous sources and transform them so that discrete data from different sources gets integrated and then loading into the data warehouse.
Extracting: Reading and understanding the source data and copying the parts that are needed to the data staging area for further work.
Transforming: Data transformations are often the most complex and, in terms of processing time, the most costly part of the ETL process.
Loading: Discrete data from different sources gets integrated and then loading into the data warehouse
https://www.sdn.sap.com/irj/sdn/weblogs?blog=/pub/wlg/2059
https://www.sdn.sap.com/irj/sdn/thread?threadID=356107
For ETTL
Besides the difference in designing the database, building a data warehouse involves a critical task that does not arise in building an OLTP system: to extract, transfer, transform, and load (ETTL) data from diverse data sources into the data
In data extraction, we move data out of source systems, such as an SAP R/3 system. The challenge during this step is to identify the right data. A good knowledge of the source systems is absolutely necessary to accomplish this task.
In data transfer, we move a large amount of data regularly from different source systems to the data warehouse. Here the challenges are to plan a realistic schedule and to have reliable and fast networks.
In data transformation, we format data so that it can be represented consistently in the data warehouse. For example, we might need to convert an entity with multiple names (such as AT&T, ATT, or Bell) into an entity with a single name (such as AT&T). The original data might reside in different databases using different data types, or in different file formats in different file systems. Some are case sensitive; others may be case insensitive.
In data loading, we load data into the fact tables correctly and quickly. The challenge at this step is to develop a robust error-handling procedure.
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