Answer / sai krishna karri

Mapplet is a reusable logic that you can use across
different mappings. Normalizer is a dynamic transformation
which converts rows to columns or vice-versa, so that is
dependendent on the input to the normalizer, it is not
fixed logic that you can reuse in other mappings.

Enlist the differences between database and data warehouse.

0 Answers  

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How to update or delete the rows in a target, which do not have key fields?

0 Answers   Informatica,

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Hi can any one tell me the difference between persistence and dynamic caches? On which conditions we are using these caches?

3 Answers  

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hi friends ... i have insurance project(informatica),can you please tell me how many table and mappings we need to use?and explain me.. thank you

0 Answers   IBM,

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my source has 2 columns. 1st column data: ABC ABC ABC XYZ and 2nd column data: 1 2 3 4. And my target should be ABC 1 2 3, XYZ 4

2 Answers   Zensar,

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If i have source as flat file. how can i store the header and trilor into one target and data into one more target. |------>target1(header+trailor) source------ |------>target2(data) can any one please help me

0 Answers   IBM, TCS,

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What is factless fact schema?

1 Answers  

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How do you recover rows from a failed session

1 Answers  

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Consider two cases: (1) Power Center Server and Client on the same machine (2) Power Center Sever and Client on the different machines what is the basic difference in these two setups and which is recommended?

2 Answers  

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what is song in infrmatica...?

0 Answers   CTS,

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Draw a workflow diagram for this situation. If s3 is true session s4 and s5 should concurreently Run.if any one s4 or s5 true it should run s1.If s1 sucess it should execute s2 otherwise exit.can any one give me suggestion.Thanks in advance.

2 Answers   TCS,

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to improve the performance of aggregator we use sorted input option and use sorter t/r befor aggregator. But here we are increasing one more cache in our mapping i.e; sorter. So how can u convince that you are increasing the performance.?

3 Answers   IBM,

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