Post on 03-Sep-2020
Maximum overkill –
minimum effort testing
SAS Fans, 29/09-2016
Trond Sogn-Lunden
2Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Traditional datawarehouse testing is tedious and manual
3Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
You should consume information by the same standards as your end-users
4Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Establishing a continuous health check on your information structures
ExampleGuidelinesBenefits
5Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Establishing a continuous health check on your information structures
ExampleGuidelinesBenefits
6Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Why should you build a data quality metrics framework?
Increase
• Quality
• Trust
• Fun
Reduce
• Efforts
• Errors
• Non-rewarding tasks
7Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Establishing a continuous health check on your information structures
ExampleGuidelinesBenefits
8Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Six steps in three phases will get you started
Prepare
• Build a test repository
• Enrich with metadata
Run
• Run regularly (scheduled)
• Store results from every test run
Analyze
• Monitor the results in a reporting tool
• Maintain test scripts and metadata
9Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Introduce standard testing for typical data warehouse elements
Dimensions
Historical consistency in slowly changing dimensions
DOG-tests
Foreign keys
Referential integrity
Key consistency and uniquness
Source key consistency
Reconciliation
E.g. number of records in source and target should be the same
Other
Data profiling (e.g. null values, formatting)
Duplication
Hierarchy consistency
Business logic
…
10Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Your test repository might look something like this
11Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Build test metadata which enable effective analysis
Test information
Category
Accuracy
Completeness
Consistency
Duplication
Integrity
Timeliness
Name
Description
Test subject
Subject area/Domain
Layer
Staging
Integration
Reporting
Table name
Column name
Owner
Test importance
Priority
High/Medium/Low
Severity
Error
Discrepancy
Info
Run indicator
Yes
No
Metadata elements will be the dimensions of your quality report
12Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Run and store your results
Run the queries from your test repository
SAS code
ETL tool
Stored Procedures
Store results in results table
Store results from all your test runs
Include all metadata
Include the query which was executed
Include the date and timestamp of the test run
Storing every test run will allow you to spot quality trends
13Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Next step is to get on board the continuous improvement cycle
Prepare
RunAnalyze
Improve
14Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Establishing a continuous health check on your information structures
ExampleGuidelinesBenefits
15Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
This is an example of how the reports might look in SAS Visual Analytics
22Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Redistribute your efforts on testing and start systematically improving
Increase
• Quality
• Trust
• Fun
Reduce
• Efforts
• Errors
• Non-rewarding tasks
Prepare
RunAnalyze
Improve
23Copyright © Capgemini 2016. All Rights Reserved
Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016
Contact information
Trond
Sogn-LundenManaging Consultant | Insights & Data
trond.sogn-lunden@capgemini.com
The information contained in this presentation is proprietary.
It is for Capgemini internal use only. Copyright © 2015 Capgemini. All rights reserved.
Rightshore® is a trademark belonging to Capgemini.
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