ETL Validator gives quick and easy way to create test cases for profiling and comparing source & target data sources. Here, we will create a test case that will profile the data with various aggregates.

1. ETL Validator Usecases:
Data Profiling
(Counts, Missing Values, Averages etc)
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2. ETL Validator
Comprehensive Testing
Automation
Extract. Load. Validate (Patented)

3. 100% Test
Coverage
Repeatability Cost Reduction Faster Time to
Market
End to End Testing
ETL Validator
Key Benefits

4. Usecase :
Create a test case:
Profile data in source
and target tables.
Start with creating a
new Data Profile Test
Plan
Data Profile

5. Usecase:
Name the test plan.
Select the Target and
Source Database
Connection.
Navigate to the next
screen.
Data Profile

6. Usecase:
SQL for query can be
typed into Target Query
and Source Query areas.
OR
Use Query Builder.
Data Profile

7. Usecase:
Query Builder opens up.
Select the Target and
Source Data Sources.
Drag and drop the tables
in their respective panes.
Data Profile

8. Usecase:
When the tables are
dragged into the Query
Columns panes, all the
columns appear.
Click on ‘Save’.
Drag & Drop
Duplicates
Data Profile

9. Usecase:
The Target and Source SQL
queries are auto generated.
They can be modified if
needed.
Click on ‘Execute Query’ to
check if the data is being
fetched properly.
Navigate to the next screen.
Data Profile

10. Usecase:
In order to run test cases
of only the ‘Customers’
table –
• Click on settings icon
• Unselect other tables.
Save the settings.
Click on ‘Run’
Data Profile

11. Usecase:
The list of fields from both
tables is displayed.
In the first column, select/de-
select fields as per
requirement.
Source table fields should
correspond with that of
target fields. In case they are
off, select the right one from
the dop-down.
Select the required aggregate
functions and variance.
Navigate to next screen.
Data Profile

12. Usecase:
Click on ‘Run’.
Data Profile

13. Usecase:
‘Overall Status’ = ‘Failure’
indicates that at least one
aggregator didn’t match
for each of those data
fields.
Individual aggregators like
‘Count’, ‘Missing Fields’
etc will show ‘Failure’ in
case they didn’t match.
This data can be exported
in Excel.
The report can also be
viewed in browser.
Data Profile
Export to Excel
Report in Browser

14. Usecase:
Same info is
displayed in web
layout.
The link can be
shared with others.
Data Profile

15. More with ETL Validator….
• Validating Field and Data Format
• Data counts validation with allowed variance
• Check Data Quality using Data Rules Test Plan
• Advanced ETL Testing using a Component Test Case
• Avoiding inline views on your queries in ETL Validator
• Checking for Mandatory Fields
• Data Profiling of Source and Target
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