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© 2018 IT PEERS – Strictly Confidential

Case Study

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The Customer

Top 5 Portuguese bank with more than 3.5 million

customers

Presence in several countries across three different

continents

Operations in retail, private banking, corporate, investment

banking and digital platforms

Highly regarded as a leader in innovation in finance

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Customer Challenge

A highly complex Quality Assurance environment

supporting over 200 different applications, using different

technologies and database vendors, some of which

contained inter-dependencies

Due to this complexity, an 8 FTE team was permanently

allocated to managing this QA landscape serving

development and testing teams in an ad-hoc basis

Last complete environment refresh was 6 years old

Basic (script based) or no data masking was applied on

databases supplied to systems integrators and contractors

An extremely high level of expensive infra-structure

resources was allocated to all the required environments

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Project

Proof of Concept2 inter-connected

applications

EvaluationQuality TestsGap Analisys

Roll OutFull coverage of applications

QA environment orchestrationFully automated management

Project start Quality gate Project end

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Datapeers Benefits

Automation

• Automated test environment creation (single model several executions

several extractions test environments with up-to-date data)

• Automates scrambling/masking of sensitive data, integrated with test

environment creation

• Provides the abillity to generate humanly readable test data

• Allows to maintain data consistency between different environments

• By improving data quality, testing activities are more productive, hence

reducing the need for re-testing

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Datapeers Benefits

Clone production data on test environments, protecting

confidential data

• Datapeers requires less effort to create test environments: selected

sensitive data in the resulting environment will be protected

(scrambled, masked, ...)

• Once the datamodel has been defined, test environment creation is

automated, reducing staff requirements

• A Datapeers operator does not need to be a DBA

• In such a complex layout, the QA team frequently requests 30+

environment refreshes during a project lifecycle. In some particular

situations, they even require daily or weekly data refreshes

(protecting confidential information). Datapeers turns this into a

simple task that can be executed with just a few mouse clicks

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Datapeers Benefits

Generate additional data on test environments

• When testing new products or new features of an existing application,

an automated test data generation tool is very useful: the overall

data quality is better and easily meets project testing requirements

• To perform ‘what-if’ scenarios (like validating the behavior of

applications after opening or acquiring 150 new branches),

Datapeers can generate controlled data to meet such requirements

• To prepare a test environment to perform volume/stress tests,

Datapeers also proves to be a very powerful tool

• Datapeers is an integrated suite of modules/products, generating

test data on top of a production clone with scrambled data, keeping

all referential integrity rules

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ROI

New testing need

• A new development creates a new testing need

• Datapeers identifies new database objects on the test plan

Prepare environments

• Datapeers introduces high degree of automation

Build new Data Gen/Import Scripts

• Database Metadata already contains business rules and sensitive data definitions

• New data automatically follows all its dependencies

Environment re-creation

• Simply restore Datapeers last extraction/data generation

New testing need

• A new development creates a new testing need

• Consultants had to identify all new database objects on the test plan

Prepare environments

• Involvement of DBA’s to create environments and the database objects

Build new Data Gen/Import Scripts

• For each new database table, a script to populate it with data had to be created and executed

• The new data must follow business rules and data security policies (Importing production data is harder)

Environment re-creation

• Recurrent need to re-create environment s for re-testing having to execute the same complete cycle once more

Average

Headcount *

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ROI

Up to 75% reduction in headcount associated with test

data management

Time to deploy new environments was shortened by a

factor of 50% or more

Increased data quality resulting in less than 35% the

average number of re-test cycles

Ability to create controlled test cases resulted in a

significant reduction in software defects going to

production

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Conclusion

Qualitative objectives achieved

• Certified quality data in all environments

• Environments are now delivered in a timely fashion increasing the

speed of project implementation in the organization

• Complete environment refresh (previously thought of as an almost

impossible task)

• Sensitive information is securely masked and protected – increased

compliance with internal and external (SOX, …) regulations

Proven Returned on Investment

• Headcount effectively reduced

• Less compute resources are now supporting non production

environments

• ROI objectives achieved in less than 6 months (some were even met

before project completion, like not performing planned infrastructure

upgrades)

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www.itpeers.com