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Showing posts from October, 2015

OBIEE 12c realised!!!!

Yuppppy,  long awaited OBIEE 12c has been released.  I can't wait to download and check it out. Here is the download link of OBIEE 12c  http://www.oracle.com/technetwork/middleware/bi-enterprise-edition/downloads/business-intelligence-2717951.html OBIEE 12c Lets download OBIEE 12c and have fun. Warm Regards Kashif M

Joiner Transformation Interview Question ( Part - 1)

What is a Joiner Transformation and why it is an Active one?   Answer: A Joiner is an Active and Connected transformation used to join two source data streams coming from same or heterogeneous databases or files. The Joiner transformation joins sources with at least one matching column. The Joiner transformation uses a condition that matches one or more pairs of columns between the two sources. In the Joiner transformation, we must configure the transformation properties namely Join Condition, Join Type and optionally Sorted Input option to improve Integration Service performance. The join condition contains ports from both input sources that must match for the Integration Service to join two rows. Depending on the join condition and the type of join selected, the Integration Service either adds the row to the result set or discards the row. Because of this reason, the number of rows in Joiner output may not be equal to the number of rows in Joiner Input. This is why Join

Expression Transformation Interview Question ( Part - 2)

Describe the approach for the requirement. Suppose the input is:   The desired output is:   Answer: Use an Expression transformation:- Expression Transformation Interview Question ( Part - 2) Keep in mind the string length of the variable and output ports. CUME function is used to calculate the cumulative amount based on the argument of the cumulative function. This means, if we call CUME with argument 1, e.g. CUME(1); then on the first call it will re-turn 1; on the second call, it will return 2; on the third call, it will return 3 and so on. Since Informatica process data row by row, this means that when the first row is processed CUME(1) will return 1; for the next row, it will return 2 and so on. How can we implement aggregation operation without using an Aggregator Transformation in Informatica?   Answer: We will use the very basic concept of the Expression Transformation, that at a time we can access the previous row dat

Filter Transformation and why it is an Active one?

  A Filter transformation is an Active and Connected transformation that can filter rows in a mapping. Only the rows that meet the Filter Condition pass through the Filter transformation to the next transformation in the pipeline. TRUE and FALSE are the implicit return values from any filter condition we set. If the filter condition evaluates to NULL, the row is assumed to be FALSE. The numeric equivalent of FALSE is zero (0) and any non-zero value is the equivalent of TRUE. Filter Transformation and why it is an Active one? As an ACTIVE transformation, the Filter transformation may change the number of rows passed through it. A filter condition returns TRUE or FALSE for each row that passes through the transformation, depending on whether a row meets the specified condition. Only rows that return TRUE pass through this transformation. Discarded rows do not appear in the session log or reject files.

Source Qualifier Transformations Filter Vs Filter Transformation

Source Qualifier Transformations Filter Vs Filter Transformation SQ Source Filter Source Qualifier transformation filters rows when read from a source. Source Qualifier transformation can only filter rows from relational sources. Source Qualifier limits the row set extracted from a source. Source Qualifier reduces the number of rows used throughout the mapping and hence it provides better performance. The filter condition in the Source Qualifier transformation only uses standard SQL as it runs in the database. Filter Transformation Filter transformation filters rows from within a mapping Filter transformation filters rows coming from any type of source system in the map-ping level. Filter transformation limits the row set sent to a target. To maximize session performance, include the Filter transformation as close to the sources in the mapping as possible to filter out unwanted data early in the flow of data from sources to targets. Filter Transformation can define a condition