This webinar was co-hosted by Curiosity and RCG Global Services on January 20th, 2022. Watch the webinar on demand: https://www.curiositysoftware.ie/solving-test-data-webinar Outdated test data management practices are today a sinkhole for testing and development time. They stifle release velocity, risk costly legislative non-compliance, and yet still do not provide the data needed to protect releases from damaging bugs. To achieve true quality at speed, the test data paradigm must shift. Enterprises must move beyond slowly copying large sets of production data to a limited number of out-of-date test environments. In this webinar, Global Head of Quality Engineering at RCG, Niko Mangahas, draws on extensive project experience to define the test data challenges facing enterprises today. He then helps you identify the right test data solution for your organisation, setting out principles for effective requirements gathering and program design. Niko then hands over to veteran test data inventor, Huw Price, who demoes some of the latest techniques for making complete and compliant data available on-the-fly during parallel testing, development, and CI/CD.

1. © Curiosity Software Ireland Ltd. 2022
Solving Test Data
The greatest Quality Engineering Bottleneck
for enterprises today?
Huw Price
Managing Director
Curiosity Software
Huw.Price@Curiosity.Software
@DataInventor
Niko Mangahas
Niko.Mangahas@rcggs.com
Global Head of Quality Engineering
RCG Global Services
@RCG_Global_Svcs

2. © Curiosity Software Ireland Ltd. 2022
Solving Test Data
The greatest Quality Engineering Bottleneck for enterprises today?
1. Test Data: The World Has Changed
2. Effective TDM Project Implementation
3. Demo: Automated Data “Find and Makes”
4. Q&A and next steps

3. © Curiosity Software Ireland Ltd. 2022
The world has changed: That’s a
problem and an opportunity
• The cloud
• Microservices
• Highly integrated systems
• APIs
• ERPs
• Message stacks
• Containerisation
• Graph databases
• Clever technologies coming out all the
time
• Horizontal and vertical scaling
• APIs are widespread
• Reusable components and Git

4. Test Data Management Project
Implementation
4

5. TDM Implementation Process
1
2
5
3
4
Defining the Problem
Inherent vs. Specific Issues
Establishing
Requirements
• Use Cases
• Use Flows
• Data Sources
• Output Formats
• Integrations
Compare Approaches
Design
Architecture
Translate to Attributes
Data
Modeling
• Parameterized Fields
• Coupled Data
• History-sensitive
Implementation
Management
Map Activities and Dependencies

6. This flow is not directly
connected to Manual and
Automated Test Flows
Production Test Data does not cover:
• Hypothetical Data
• Outliers / Edge Cases
• Negative Scenarios
• New Features
Defining the Problem
6
Test Data
Requirements
Application
Data Model
Subsetting
Process
Synthesis
Process
Encryption
Process
Retention
and Cleanup
Process
Selection
Process
Review Usage
Metrics and
Reports
Test
DB
Master
Data
Prod
DB / DBs
Common TDM Issues
Data Design / Model Data Journey - Applications
Data at Rest Data in Flight
Client-Specific TDM Issues
Reported Challenges Impacted
Systems
Impact
Corrupted, changing and expired test data causes test failures.
HIGH
Test data is not common across internal and external data sources. MEDIUM
Insufficient test data results in high dependency on simulated test
data.
MEDIUM

7. Business Objectives and Attributes
7
Current Ideal
EFFORT
QUALITY
SPEED /
TIMING
OTHERS
• Some data sources are unreliable and need to be
cross checked for validity
• Security and Access is loosely managed
• Test Data can take significant time to procure, or
synthesize
• Data Expires when consumed or according to time
• Release planning is time and effort intensive
• There are multiple and various solutions for
functional, non-functional, manual, automated and
API testing
• Significant Effort to manually or automatically
generate test data takes away from other testing
activities
• Test Data can come from different sources
• High reliability and validated test data
• Easier process for managing access, secure
repository
• Test Data is reasonably acquired in line with rapid
deployment
• Data expiration is manageable against testing
windows
• More decoupled test data usage
• Should support functional and non-functional
testing
• Should support manual and automated testing
• Should support several formats
• Test Data Generation takes up little to no effort
(fully automated)
• Data generation and synthesis is dynamically
triggered with automated testing execution (or
self-service, on-demand)
• Test Data is managed centrally
•
No
current
data
points
/
analytics
/
logging
/
visualization
to
optimize
test
data
management
•
Analytics
and
reports
allow
for
the
further
optimization
of
test
data
usage
and
test
coverage
No Overarching Strategy, Governance, Compliance, Access Management Strategic and Centralized TDM Service

8. Comparison of Approaches
8
OPTION1
CURIOSITY
SOFTWARE
$$$ - Significant Investment
to Build the foundational
TDM platform with initial
interfaces
$$ - Smaller investment to Expand
and Focus on similar data sources
(i.e. APIs) and create each interface –
according to the ROI
Solution is expanded per
individual ‘step’ that
requires test data
End State is an in-house, self-
service TDM platform that QA
and others can use to solve
virtually any TDM need
$$ - Medium Investment to pilot
TDM tool and automating a few
key master flows
$$ – Similar investment to add
new flows, combinations and sub-
flows - according to ROI
Solution expansion is based on
new flows, sub-flows (steps) and
combinations of flows
End State is a DevOps Ready solution
focused on optimizing testing for QA,
but may not solve all needs
Current
State
Future
State
Approach
Continued
Investment
Solution
Expansion
Approach
Solution
End State
Initial
Investment

9. Test Data Flows
9

10. Setup and Scoping Data Profiling & Data Modelling Implementation and Integration Demo and Rollout
1
2 3
4
5
6 8 11
12
15
14
13
10
9
7
TDM Pilot Implementation
10
Phase 1 Phase 2 Phase 3 Phase 4
1 Project Kickoff
2
3
4
5
6 Create Data Catalogue
7
8
9
10
11
12 CI/CD Integration
13
14
15
Full Demo and
Operationalization

11. © Curiosity Software Ireland Ltd. 2022
Automated data “find and
makes”
A first step in making complete and compliant data available on-the-fly
during parallel testing, development, and CI/CD

12. © Curiosity Software Ireland Ltd. 2022
How do people find and make their data now?
• Finding data is random
• Finding data is not structured
• If you can’t find data you have to make it or ignore it
• People don’t reuse what other have done
• Data is not integrated with any of the dev/test toolchain
Up to 50% of a testers time can be spent finding
or making data

13. © Curiosity Software Ireland Ltd. 2022
Unstructured Find and Make
Tester Looking for
Data
• It’s Slow
• It’s Random
• It’s Unpredictable

14. © Curiosity Software Ireland Ltd. 2022
Finding Data – A Structured Approach
• Split the “business” from the “technical”
• Create shopping carts – aggregated views of data
• Add in extra “business” attributes as they come up
• Connect the find to “allocation” – keep data separate
• Store user searches for replay and analysis – recreate the data when re-
provisioning the environment
• Auto create “covered” combinations of data when you provision any environment
• Integrate your finds into your automation

15. © Curiosity Software Ireland Ltd. 2022
Structured Find and Make
Tester Looking for
Data
BP
CT
AR
FIN
NM
AC
FI
TP
Test Data Mart
EX
FR
Add Attributes
Not Found
Look for Similar & Modify
Clone Existing
Make New
Allocated Data to test – Read or Transact
T1-2 T2-3 T3-2 T4-2 T5-6 T6-10
Direct into the DB,
Message, UI or API
Business Technical
# Bankruptcies
Currently In default
Late Payments
Age
Fraud Hold

16. © Curiosity Software Ireland Ltd. 2022
Environment or Container Provisioning
TDM – Subset – Mask - Condition
Clone interesting, rare or bugs
Production
Dev/Test/QA
Conditioning Engine
Mask
Virtual Databases
FIND
SQL1
FIND
SQL2
FIND
SQL3
MAKE1 MAKE2 MAKE3 MAKE4
AD HOC
MAKE5
MODEL
PROCESS MODEL
DATA MODEL
DATA COMBINATIONS

17. Demo
© Curiosity Software Ireland Ltd. 2022

18. © Curiosity Software Ireland Ltd. 2022
A Quick Summary - Find, Make & Condition
What does it do?
• Builds and captures business queries
• Stores and analyses the data you are looking for
• Breaks down queries to look for similar data
• Calculates the data needed to satisfy the find
• Maps the finds to a make, update, clone
• Models the potential variations of data
• Creates data across multiple systems in any format
• Allocates data to tests based on criteria
How does it help?
• Learns the data that you need to test with
• Builds up a systematic set of data
• Saves time searching for data
• Save time working out what data is needed
• Systematically works out what to make
• Uses the requirements to model your data
• Saves time setting up complex integration tests
• Allows teams to work efficiently
Green == Quality Improvements
Blue == Save time and Speed up
development

19. © Curiosity Software Ireland Ltd. 2022
Questions and Discussion

20. © Curiosity Software Ireland Ltd. 2022
Carry on the conversation?
• Book a free online test data workshop – Visit TestDataAutomation.io
and hit “Arrange Demo”.
• Contact Niko on LinkedIn to discuss your test data projects.
• Follow Curiosity Software on LinkedIn and @CuriositySoft on Twitter for
resources and news.
• Follow RCG on LinkedIn and @RCG_Global_Svcs on Twitter.
• Join Curiosity’s next Test Data webinar on March 17th.

21. © Curiosity Software Ireland Ltd. 2022
Thank you
Huw.Price@Curiosity.Software
Niko.Mangahas@rcggs.com