Saurav has posted a new article here on Incremental Aggregation Using Informatica.
The need of incremental aggregation arise when we capture our source data (transactional data) incrementally in a frequency faster than the aggregation period.
Take this example, a data warehouse system is refreshed every night from source data. The data warehouse has a monthly aggregated table. So it is obvious that every day's data you need to aggregate and put together in the monthly table. But in stead of loading the monthly table at month end, if you consider loading this monthly table everyday or every week or bi-monthly, then incremental aggregation is possibly the best option for you.
Now performance wise, it remains an open question on how good is Informatica in doing incremental aggregation. I think Saurav might consider an other article by putting informatica in test with considerable data volume.
The need of incremental aggregation arise when we capture our source data (transactional data) incrementally in a frequency faster than the aggregation period.
Take this example, a data warehouse system is refreshed every night from source data. The data warehouse has a monthly aggregated table. So it is obvious that every day's data you need to aggregate and put together in the monthly table. But in stead of loading the monthly table at month end, if you consider loading this monthly table everyday or every week or bi-monthly, then incremental aggregation is possibly the best option for you.
Now performance wise, it remains an open question on how good is Informatica in doing incremental aggregation. I think Saurav might consider an other article by putting informatica in test with considerable data volume.
We can use an update strategy transformation in this case. Isn't it?
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Good content. You write beautiful things.
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