Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort...

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Maximum overkill minimum effort testing SAS Fans, 29/09-2016 Trond Sogn-Lunden

Transcript of Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort...

Page 1: Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort testing | SAS Fans, 29/9-2016 Run and store your results Run the queries from your test

Maximum overkill –

minimum effort testing

SAS Fans, 29/09-2016

Trond Sogn-Lunden

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2Copyright © Capgemini 2016. All Rights Reserved

Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016

Traditional datawarehouse testing is tedious and manual

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You should consume information by the same standards as your end-users

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Establishing a continuous health check on your information structures

ExampleGuidelinesBenefits

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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

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Why should you build a data quality metrics framework?

Increase

• Quality

• Trust

• Fun

Reduce

• Efforts

• Errors

• Non-rewarding tasks

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Maximum overkill – minimum effort testing | SAS Fans, 29/9-2016

Establishing a continuous health check on your information structures

ExampleGuidelinesBenefits

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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

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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

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Your test repository might look something like this

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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

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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

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Next step is to get on board the continuous improvement cycle

Prepare

RunAnalyze

Improve

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Establishing a continuous health check on your information structures

ExampleGuidelinesBenefits

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This is an example of how the reports might look in SAS Visual Analytics

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Page 18: Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort testing | SAS Fans, 29/9-2016 Run and store your results Run the queries from your test
Page 19: Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort testing | SAS Fans, 29/9-2016 Run and store your results Run the queries from your test
Page 20: Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort testing | SAS Fans, 29/9-2016 Run and store your results Run the queries from your test
Page 21: Maximum overkill - minimum effort testing · 9/29/2016  · Maximum overkill –minimum effort testing | SAS Fans, 29/9-2016 Run and store your results Run the queries from your test
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Redistribute your efforts on testing and start systematically improving

Increase

• Quality

• Trust

• Fun

Reduce

• Efforts

• Errors

• Non-rewarding tasks

Prepare

RunAnalyze

Improve

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Contact information

Trond

Sogn-LundenManaging Consultant | Insights & Data

[email protected]

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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.

www.capgemini.com

About Capgemini

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foremost providers of consulting, technology and outsourcing services. The Group

reported 2014 global revenues of EUR 10.573 billion.

Together with its clients, Capgemini creates and delivers business and technology

solutions that fit their needs and drive the results they want. A deeply multicultural

organization, Capgemini has developed its own way of working, the Collaborative

Business Experience™, and draws on Rightshore®, its worldwide delivery model.

Learn more about us at www.capgemini.com.