Informatica Interview Questions and Answers

When the organization data is created at a single point of access it is called as enterprise data warehousing. Data can be provided with a global view to the server via a single source store.  One can do periodic analysis on that same source. It gives better results but however the time required is high.

Database includes a set of sensibly affiliated data which is normally small in size as compared to data warehouse. While in data warehouse there are assortments of all sorts of data and data is taken out only according to the customer’s needs. On the other hand, data mart is also a set of data which is designed to cater the needs of different domains. For instance an organization having different chunk of data for its different departments i.e. sales, finance, marketing etc.

When all related relationships and nodes are covered by a sole organizational point, it’s called domain. Through this data management can be improved.

Repository server controls the complete repository which includes tables, charts, and various procedures etc. Its main function is to assure the repository integrity and consistency. While a powerhouse server governs the implementation of various processes among the factors of server’s database repository.

Partitioning a session means solo implementation sequences within the session. Its main purpose is to improve server’s operation and efficiency. Other transformations including extractions and other outputs of single partitions are carried out in parallel.

For the purpose of creating indexes after the load process, command tasks at session level can be used. Index creating scripts can be brought in line with the session’s workflow or the post session implementation sequence. More over this type of index creation cannot be controlled after the load process at transformation level.

A teaching set that needs to be implemented to convert data from a source to a target is called a session. Session can be carried out using the session’s manager or pmcmd command. Batch execution can be used to combine sessions executions either in serial manner or in a parallel. Batches can have different sessions carrying forward in a parallel or serial manner.

One can group any number of sessions but it would be easier for migration if the number of sessions is lesser in a batch.

When values change during the session’s execution it’s called a mapping variable. Upon completion the Informatica server stores the end value of a variable and is reused when session restarts. More over those values that do not change during the sessions execution are called mapping parameters.  Mapping procedure explains mapping parameters and their usage. Values are allocated to these parameters before starting the session.

It allows one to do aggregate calculations such as sums, averages etc. It is unlike expression transformation in which one can do calculations in groups.

Values can be calculated in single row before writing on the target in this form of transformation. It can be used to perform non aggregate calculations. Conditional statements can also be tested before output results go to target tables.

It is a medium of filtering rows in a mapping. Data needs to be transformed through filter transformation and then filter condition is applied.  Filter transformation contains all ports of input/output, and the rows which meet the condition can only pass through that filter.

Joiner transformation combines two affiliated heterogeneous sources living in different locations while a source qualifier transformation can combine data emerging from a common source.

It is used for looking up data in a relational table through mapping. Lookup definition from any relational database is imported from a source which has tendency of connecting client and server. One can use multiple lookup transformation in a mapping.

It is a diverse input group transformation which can be used to combine data from different sources. It works like UNION All statement in SQL that is used to combine result set of two SELECT statements.

Option for incremental aggregation is enabled whenever a session is created for a mapping aggregate. Power center performs incremental aggregation through the mapping and historical cache data to perform new aggregation calculations incrementally.

When the inputs are taken directly from other transformations in the pipeline it is called connected lookup. While unconnected lookup doesn’t take inputs directly from other transformations, but it can be used in any transformations and can be raised as a function using LKP expression. So it can be said that an unconnected lookup can be called multiple times in mapping.

A recyclable object that is using mapplet designer is called a mapplet. It permits one to reuse the transformation logic in multitude mappings moreover it also contains set of transformations.

Reusable transformation is used numerous times in mapping. It is different from other mappings which use the transformation since it is stored as a metadata. The transformations will be nullified in the mappings whenever any change in the reusable transformation is made.

Row by row processing is done by informatica.  Every row is inserted in the target table because it is marked as default. Update strategy is used whenever the row has to be updated or inserted based on some sequence. More over the condition must be specified in update strategy for the processed row to be marked as updated or inserted.

This happens when it faces DD Reject in update strategy transformation.  Moreover, it disrupts the database constraint filed in the rows was condensed.

Surrogate key is a replacement for the natural prime key. It is a unique identification for each row in the table.  It is very beneficial because the natural primary key can change which eventually makes update more difficult. They are always used in form of a digit or integer.

In order to perform session partition one need to configure the session to partition source data and then installing the Informatica server machine in multifold CPU’s.

During session runs, the files created are namely Errors log, Bad file, Workflow low and session log.

It is a chunk of instruction the guides Power center server about how and when to transfer data from sources to targets.

This specific task permits one or more than one shell commands in UNIX or DOS in windows to run during the workflow.

This task can be used anywhere in the workflow to run the shell commands.

Command task can be called as the pre or post session shell command for a session task. One can run it as pre session command r post session success command or post session failure command.

It is a file-watch event. It waits for a specific file to arrive at a specific location.

Following are the features of complex mapping

• Difficult requirements
• Many numbers of transformations
• Complex business logic

One can find whether the session is correct or not without connecting the session is with the help of debugging option.

Yes, one can do because reusable transformation does not contain any mapplet or mapping.

Aggregator transformations are handled in chunks of instructions during each run. It stores transitional values which are found in local buffer memory. Aggregators provides extra cache files for storing the transformation values if extra memory is required.

Lookup transformations are those transformations which have admission right to RDBMS based data set. The server makes the access faster by using the lookup tables to look at explicit table data or the database. Concluding data is achieved by matching the look up condition for all look up ports delivered during transformations.

The dimensions that are utilized for playing diversified roles while remaining in the same database domain are called role playing dimensions.

Repository reports are established by metadata reporter. There is no need of SQL or other transformation since it is a web app.

The types of metadata include Source definition, Target definition, Mappings, Mapplet, Transformations.

When data moves from one code page to another provided that both code pages have the same character sets then data loss cannot occur. All the characteristics of source page must be available in the target page. More over if all the characters of source page are not present in the target page then it would be a subset and data loss will definitely occur during transformation due the fact the two code pages are not compatible.

All the mappings cannot be validated simultaneously because each time only one mapping can be validated