![]() Related Questions Answered by Laxmi on 2005-05-13 16:42:53: Staging area is place where you hold temporary tables on data warehouse server. Staging tables are connected to work area or fact tables. We basically need staging Latest Answer : The staging area is:- One or more database schema(s) or file stores used to “stage” data extracted from the source OLTP systems prior to being published to the “warehouse” where it is visible to end users.Data ... What are the various methods of getting incremental records or delta records from the source systems? Latest Answer : draw the inference if slowly changing dimension and based on the Type 1/2 or3 tables defined. ... Techniques of Error Handling - Ignore , Rejecting bad records to a flat file , loading the records and reviewing them (default values) Lets suppose we have some 10,000 odd records in source system and when load them into target how do we ensure that all 10,000 records that are loaded to target doesn't contain any garbage values. How do we test it. We can't check every record as number of records are huge. Read Answers (8) | Asked by : Ram How you capture changes in data if the source system does not have option of storing date/time field How you capture changes in data if the source system does not have option of storing date/time field in source table from where you need to extract the data? The DW database can be Oracle or Teradata. The requirement here is to pull data from source system and ETL need to device a mechanism to identify the changes or new records. The source system can be a Read Answers (1) | Asked by : GeekNo1 Develop a mapping to extract the employee drawing maximum salary where deptno = department drawing maximum sum(salary) group by dept.sources are cobol files / flat files. This is the recent question faced in ibm. Read Answers (4) | Asked by : naresh Why is it necessary to clean data before loading it into the Warehouse Latest Answer : Warehouse data is used as source data for data analysis and reporting. The data is organized into groups and categories (aggregation) and then summarized upon those groups (dimensions). These groups are based upon exactness.
For example "house", ...
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