Uploaded on Jul 8, 2022
Data Warehouse Testing is the process to develop and execute complex test cases to access the integrity of the data. Test and automate the data in your Data Warehouse Testing with ICEDQ and avoid data-related risks to overcome testing challenges.
Data Warehouse Testing
Data Warehouse Testing
Make sure the sanctity of your data is preserved and avoid data related
risks.
What is Data Warehouse Testing?
The process of verifying the entire data warehouse landscape for data accuracy, data
completeness, data integrity, and data quality is called Data Warehouse Testing.
Data Warehouse Testing Challenges
• Testing a data warehouse with a high volume of
Data.
• Comparing data across heterogeneous data
sources.
• Testing across multiple environments.
• Testing a Business Intelligence (BI) Report.
• The inability to identify data issues on time.
Type of Data Warehouse Testing Checks
Source data validation - This test is to ensure that
the data in the source table or file does not have any
Data Quality or Data Accuracy issues.
Source to target reconciliation - This Data
Warehouse test is for Data Completeness
between source and target when there is not
transformation involved, and it is a one to one
load.
ETL reconciliation - Testing the Data
Warehouse for any Data Transformation,
Conversion, or Calculation issues is crucial to
ensure Data Completeness.
Type of Data Warehouse Testing Checks
Business validation - The purpose is to ensure
that data is not breaking any business rules
even if the ETL has loaded the table successfully.
Business reconciliation - Ensuring that
data between two subject areas is
consistent and is not breaking any
business rule is one of the Data
Warehouse testing check users perform.
Five Things to Look For in Data Warehouse Testing
Tool
High data Test across
volume Regression data sources
testing testing
Integration Reportin
g
Use iCEDQ for Data Warehouse Testing
• Test 100% of the data in your Data Warehouse and identify
any data issues using our in-memory engine or the Apache
Spark engine.
• Users can connect to different data sources, be it a
database, file source, or a reporting tool, and validate and
compare data across them.
• Create test suites for regression testing, release
management testing, or for reusing the same Data
Warehouse tests across multiple environments.
• Integrate iCEDQ with your test management tool like HP
ALM, ticketing systems like JIRA, or CICD tools like Jenkins
using our Rest API or CLI utilities.
Request a Demo
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