Case Study: Royal Bank of Canada’s Managing of Test Data Life Cycle with CA Agile Requirements Designer and CA Test Data Manager

1. World®
’16
Case Study: Royal Bank of Canada’s Managing of
Test Data Life Cycle With CA Agile Requirements
Designer and CA Test Data Manager
Elham Bassiri - Director, Quality Engineering - Royal Bank of Canada
DO5X33S
DEVOPS

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The content provided in this CA World 2016 presentation is intended for informational purposes only and does not form any type
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For Informational Purposes Only
Terms of this Presentation

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Abstract
Royal Bank of Canada’s (RBC) data warehouse group is focused on delivering solutions
on time, with reduced cost and minimized risk. For development and testing purposes,
migrating full copies of production data and maintaining them is time-consuming, costly
and prone to risk. The in-house solutions in this regard were mostly manual and require
significant ongoing maintenance. RBC applications are large and complex. As a result,
finding and extracting consistent, realistic subsets by hand is challenging. Provisioning
poor quality data results in poor quality testing. Many data sub-setting techniques
involve multiple steps, which include changing the data to proprietary formats in order
to mask it, which also increases the potential risk of breaches. This presentation will
outline the need for a sub-setting/masking solution, how it can be implemented in such
a large organization like RBC, and possible expected results. RBC will present their use
of CA Agile Requirements Designer alongside CA Test Data Manager, and how test data
life cycle automation is a possibility. Using CA Agile Requirements Designer, BRC is able
to model current testing requirements and generate optimized test cases, and by using
CA Test Data Manager Solution they are able to subset and mask large volumes of
production data, complex data structures following strict regulations that are in place.
Elham
Bassiri
RBC, Enterprise
Information
Management
Director, Quality
Engineering

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Agenda
RBC QUALITY ENGINEERING SERVICES
TEST DATA MANAGEMENT PAIN POINTS
CURRENT BENEFITS AND FUTURE PLANTS
TEST DATA MANAGEMENT OBJECTIVES
PROPOSED SOLUTION
TOOL SELECTION
1
2
3
4
5
6

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Quality Engineering Services
What This Team Does
EIM Services
Optimized Testing
Release
Management
*Test Data
Management and
QA Environment
Other:
Provide QE
approach for
transformational
changes
Automation and
Continuous
Integration
* Focus of this presentation is on our TDM challenges and solution that is also an input to all QE services

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Test Data Management – Pain Points
§ We had too many test environments and they were not in sync
§ Test environments did not sufficiently represent production and
lead to QA and credibility issues and rework
§ Time to deliver on changes/Projects and cost to implement was
increased due to test data challenges
§ In addition test Data ad hoc requests from over 50 Business Units
was becoming unmanageable
Test Data Management Was One of Our Biggest Challenges for Testing,
Exploration and Analysis

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Test Data Management – Objectives
What Was Our Objective:
§ EIM to provide a Test and Development environment to support
internal and business based development lifecycle
§ Establish a Test/Dev platform maintenance approach
§ The environment to contain scheduled refreshed representation
of production data
§ Deploy automated data consistency across environments and
reduce overall development and testing time

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Proposed Solution
Our Proposed Solution Was:
Prod-A
Prod-B
Full Set
Baseline +
New Data
Test-X
Full Set
Baseline
IST
Full Set
Baseline
Test/Dev-B
Full Set
Baseline
Test/Dev-A
Flat Files
1
2
3
1 2 3
§ Automated processes to
extract data from production
into Test-X
§ Data is extracted based on a
sampling criteria (yet to be
determined).
§ These processes will be
scheduled in line with
current production cycles
(weekly, monthly, etc.
§ Test-X to maintain production
level data with limited
history.
§ Platform to serve and provide
access for:
⎻ Power user analytics
⎻ Support work groups
⎻ User driven data discovery and
data profiling
⎻ Provide a ”near-production”
platform to conduct performance
testing and final pre-production
testing
§ Production reflection of data
”masked” in database on Test-
X, then extracted to files.
§ The baseline set of data loaded
to all three test/dev platforms.
§ Version controlled baselines
maintained at each platform
for access while creating
additional objects or changes in
each logical project databases.

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Tool Selection
We Needed a Tool to Help Us With the Proposed Solution
§ Provide data subsetting and masking to build a
golden copy of production like test data
§ Maintain the referential integrity of the data
§ Generate test data that doesn’t exist in the
golden copy

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Our Solution Leveraging CA TDM
Golden Copy of Data Is Created Under Baseline Database
CA
TDM

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Test Data Generation
Synthetic Data Fit for Purpose
In the following cases where we have data
requests that doesn’t exist in our baseline:
§ Specific test data requirements
§ Test data for negative test scenarios
§ Data volume
§ New fields or column requirements
Use CA Test Data
Manager Tool:
§ It follows the same fields and
structure as the actual data
extracted from production server
§ Provides high volume of data faster

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Test Case Optimization
In Addition we use CA Agile Requirements Designer
solution which helps us:
§ Identify gaps in the requirements
§ Generate a set of optimized test cases automatically
§ Helps with agile changes and support agile sprints
§ Integration with our ALM repository
§ Future plants include using automation code generation
and QA risk assessment
CA Has Also Helped Us With Optimizing Our Test Cases

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Our Future Goals
Achieve a hands-
free, 100% test
data automation
using test data
on demand
Expand the Test
Data Management
Services to other
departments
across other
departments in IT
Connect ARD test
cases generated
to our test
execution
automated tool
Generate
synthetic data
custom fit for
test cases

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Questions?

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