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Extract-Transform-Load (ETL) processes play an important role in data warehousing. Typically, design work on ETL has focused on performance as the sole metric to make sure that the ETL process finishes within an allocated time window. However, other quality metrics are also important and need to be considered during ETL design. In this paper, the authors address ETL design for performance plus fault-tolerance and freshness. There are many reasons why an ETL process can fail and a good design needs to guarantee that it can be recovered within the ETL time window. How to make ETL robust to failures is not trivial. There are different strategies that can be used and they each have different costs and benefits.
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