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Data Warehouse Testing

VAssure’s Data warehouse & BI testing strategy focuses on the two main structures within a data warehouse architecture: the ETL (Extraction, Transformation and Loading) layer and the data warehouse with its front-end applications. Each of these units must be treated separately, and since there may be multiple components in each (multiple feeds to ETL, multiple databases or data repositories that constitute the warehouse, and multiple front end applications), each of these subsystems must be individually validatedit

Constraints Testing - During constraint testing, the objective is to validate unique constraints, primary keys, foreign keys, indexes, and relationships. Some ETL processes are developed to validate constraints during the loading of the warehouse.

Counts - The objective of the count test scripts is to determine if the record counts in the source match the record counts in the target.

Source to Target Data Validation - No ETL process is smart enough to perform source to target field-tofield validation. This piece of the testing cycle is the most labor intensive and requires the most thorough analysis of the data. There are a variety of tests that can be performed during source to target validation.

Threshold testing - expose any truncation that may be occurring\ during the transformation or loading of data

Field to Field Field-to-field testing - is a constant value being populated during the ETL process? Do the values in the source fields match the values in the respective target fields? Below are two additional field-to-field tests that should occur.

Initialization - During the ETL process if the code does not re-initialize the cursor (or working storage) after each record, there is a chance that fields with null values may contain data from a previous record.

Integration Testing

The first level of testing and validation begins with the formal acceptance of the logical data model. All further testing and validation must be based on the understanding of each of the data elements in the model and how they will assist the company, specifically in the subject area(s) for your particular increment, meet specific business objectives in the areas of reporting and analysis.

Data Validation

Reviewing the mapping utilized by the ETL tool is the primary task during data validation. Due to the shear volume of data to be loaded into the fact tables, it is imperative that care is taken that the mapping is validated to verify that the data that you think is being loaded into specific data elements is in fact being sourced from tables that we know contain the information in the operational system.


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