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THE GLOBAL LEADER IN CONTINUOUS TEST AUTOMATION
Data Integrity
Automation
Drive better business
outcomes through data you
can trust

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Data Integrity Automation Agenda
Why? To reduce your risk of failures, you must test your processes for integrity. Data Integrity can ONLY be
achieved by testing ALL your data processes and ensure integrity end-to-end, with automation, and do it
continuously
Problem to be Solved Why it is not Solved
How to Solve it Benefits of doing so
What are the Consequences

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Data Governance for Data Trust
Metadata
and Data
Catalogs
Thousands of Hours to Create Complex Reports
People – Process – Technology
Data Delivery Culture – Access – Stewardship – Quality - Utilization - Acquisition
Data
Quality
Master
Data
Data
Security
Data Governance is the
Epicenter of Data Disruption
comes with Information
Stewardship
Data
Lifecycle

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Change is constantly at work
across your digital landscape
Application
Changes
Data
Changes
Environment
Changes
On-Prem
Cloud
Partner
ecosystem
web apps
AI/ML-
driven
initiatives

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Application
Changes
Data
Changes
Environment
Changes
On-Prem
Cloud
Partner
ecosystem
web apps
Application problems:
Technical/UI changes
Business requirements
Customizations
Data problems:
Incorrect data
Duplicate data
Missing data
Environment problems:
System / desktop updates
Integrations
Network changes
Compliance
reports
Reports,
dashboards,
visualizations
AI/ML-
driven
initiatives
Change is constantly at work
across your digital landscape

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Accelerated Digital Change
*Sources: Mayfield CXO Survey – Post COVID-19 Impacts to IT, IDC FutureScape IT Industry 2021 Predictions, ASUG Tricentis Survey 2021 – Future of SAP Delivery
CLOUD
MIGRATION
85% plan to shift to
cloud-centric
infrastructure &
applications twice as
fast as before the
pandemic
APPLICATION
MODERNIZATION
67% plan to migrate
half of on-prem
applications. 91% plan
to upgrade to SAP
S/4HANA in next 24
months
RAPID AND
REGULAR UPDATES
released by enterprise
apps like SAP, Salesforce,
ServiceNow
DATA
MIGRATION
43.5% say data
migration is the main
challenge when moving
to advanced
versions/upgrades
DIGITAL
OPTIMIZATION
50% plan to digitize
eCommerce, deliver
new features to
improve customer
self-service & UX

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If you don’t deal with change, expect consequences…
Delivering poor quality Being late Inefficient resource
management
Large multinational bank
24h downtime = $7 million loss
and reputational damage
Telecommunications provider
Manual testing = 10K tests
3 releases/yr, delayed innovation
Global oil & gas company
Required highly technical skills,
>$45 million maintenance costs

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If you don’t deal with change, expect consequences…
Accounting Failures Costly Compliance
Fines
Major insurer ERP consolidation of
data flows,
Leads to business operations
failures (40K Invoices)
Major Bank
>$50 million in
due to bad data quality used
for AML/KYC regulatory
requirements
Loss due to Data
Analytics Platform
Mistrust
For WorldPay, we helped deliver
decision-grade data to business
teams from massive volumes of
transactional payment data.
Thousands of hours of manual
effort saved per month AND
Trust in the numbers regained

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Data can break anywhere in the process
because of dangerous data management gaps
DATA WAREHOUSE
DATA ANALYTICS / BI
ECOSYSTEM
Information
Steward
Data
Services
Advanced Data
Migration by Syniti
MDG

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Why? - Data Gaps in Testing Coverage
Gap Reasons
• Point Solutions only check one point in the process. Examples, MDM, ETL Test Tools..
• MDM is a production problem catcher, not a fixer, and not a tester solution
• Solutions like Snowflake are focused on the data processes themselves not guaranteeing the
quality of the data OUTSIDE their processes.
• ETL providers
• Report Testing

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So, the race is on to find the data errors
EXTRACT
Enterprise data
warehouse
Data marts/
cubes
Business data
sources
TRANSFORM LOAD AGGREGATE TRANSFORM REPORT
?
Did the problem
originate in the
source data?
Was there an issue
with a data load?
?
Did a transformation
job go wrong?
Did a job fail to run or
run too many times?
Were there
issues with the
transformation logic?
?
Is the report pulling
from the right
data mart?
Is there a problem with
the report logic?
Is the report rendering
incorrectly?
REFINE
Reports,
dashboards,
visualizations

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Manual “stare and compare” is slow
and doesn’t scale.
And is not a great use of your team’s brainpower.
So why isn’t your data
better already?

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To Trust the
Production
Environment:
ENTERPRISE
DATA WAREHOUSE
DATA LAKE
DATA ANALYTICS / BI
ECOSYSTEM
Information
Steward
Data
Services
Advanced Data
Migration by Syniti
MDG
ENTERPRISE
DATA WAREHOUSE
DATA LAKE
DATA ANALYTICS / BI
ECOSYSTEM
APPLICATION
ECOSYSTEM
You must End
to End Test in
the Test
Environment:

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It’s time to think differently
about how you maintain
the integrity of your data

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It’s time to bring the discipline
of end-to-end testing
to the world of data

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End-to-end Automated Continuous
Implement a data testing solution
that’s…
Enterprise
Data Integrity Testing

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Automated Continuous
A data testing solution that’s…
Includes data, UI, and
API testing across your
landscape.
End-to-end
Enterprise
Data Integrity Testing

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Catch more data
issues up front
Get higher data
quality
Test at scale
and at speed
So, you can…
Enterprise
Data Integrity Testing

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Automation — the key to moving from data integrity to decision
integrity
EXTRACT
Enterprise data
warehouse
Data marts/
cubes
TRANSFORM LOAD AGGREGATE TRANSFORM REPORT
REFINE
Reports,
dashboards,
visualizations
PRE-
SCREENING
Metadata checks
Format checks
VITAL
CHECKS
Completeness
Uniqueness
Nullness
Referential integrity
FIELD
TESTS
Aggregation
Value range
Transformation
RECONCILIATION
TESTS
Detailed source to
target comparison tests
ETL validation
REPORT & APP
TESTING
UI automation
Visual checks
Content checks
Security checks
CONTINUOUS MONITORING Row counts, Job run times, Data distribution

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Keep your automation easy, faster and at scale
with model-based test automation
Make quick
tweaks to either
layer as things
change.
Create Maintain
Auto-
generate
tests.
Auto-
update
tests.
Business logic
Template
2
1 3
4
Separate out what you need to test into layers for
fast, easy creation and maintenance.
Build a flexible
testing model.
Test case
design
sheets
Test
cases

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8 advancing opportunities
Proven strategies to tackle test automation challenges
Empower any user
to contribute to automation
through a codeless approach
that removes programming
resources.
Test what matters
Aligning testing with business
risks delivers high ROI in
the shortest time and with less
effort.
Cover all testing needs
Seek a comprehensive toolset
that is technology-agnostic
to avoid relying on specialists
as and to expand testing use
cases.
Eliminate maintenace
The less maintenance is
required, the lower your total
costs. Seek resilient, codeless
test automation approaches.
Get on-demand test data
Eliminate wait time and false
postives by enabling testers to
create and access test data
when needed.
Promote collaboration
through reusable test artifacts
that can be plugged into a
central repository for end-to-
end test automation.
Shift left testing
Test at the API layer
and use AI-based technologies
to create UI tests before UIs
are completed.
Simulate environments
Get rid of access fees and
ensure that testing can
proceed even if test
environments are unavailable
or unstable.
SUSTAINABLE
AUTOMATION
RESILIENCY
AND REUSE
SELF-SERVICE
+ SHIFT LEFT

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How CI/CD with CT works
to continuously test across
your digital enterprise
FIX
QA
Collaborate across teams to
build better tests—end-to-end
Business Data
No-code, low-code solution
No expert programming skills required
AUTOMATE
Tests in parallel
at scale and
speed
Get detailed,
actionable reports.
RUN
requirements
& test case
design
PLAN
CREATE
model-based
tests.
Pinpoint the root
cause of problems
REPORT

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Thank You!
Questions?