Data governance and data quality are often described as two sides of the same coin. Data governance provides a data framework relevant to business needs, and data quality provides visibility into the health of the data. If you only have a data governance tool, you’re missing half the picture. Trillium Discovery seamlessly integrates with Collibra for a complete, closed-loop data governance solution. Build your data quality rules in Collibra, and they are automatically passed to Trillium for data quality processing. The data quality results and metrics are then passed back to Collibra – allowing data stewards and business users to see the health of the data right within their Collibra dashboard. View this webinar on-demand to see how you can leverage this integration in your organization to readily build, apply, and execute business rules based on data governance policies within Collibra.

1. Building Rules for Data
Governance
Marco de Jong
Michael Sisolak

2. Housekeeping
Webcast Audio
• Today’s webcast audio is streamed through your
computer speakers.
• If you need technical assistance with the web
interface or audio, please reach out to us using
the chat window.
Questions Welcome
• Submit your questions at any time during the
presentation using the chat window.
• We will answer them during our Q&A session
following the presentation.
Recording and slides
• This webcast is being recorded. You will receive
an email following the webcast with a link to
download both the recording and the slides.
2

3. Speakers
Marco de Jong
• Product Management Director, Syncsort Trillium
• 20+ years in Information Management, Data Quality, Integration, and Data Governance
• Passioned about Data Quality and Data Governance
Michael Sisolak
• Pre-Sales Consultant for Syncsort
• 20+ years data management experience
• Specializes in Data Quality, Data Governance, Data Integration and Big Data.

4. Agenda
• Why Data Governance is top of mind
• The relationship between DQ and DG
• Use Case
• Solving the challenge
• Demonstration
• Q&A

5. • Broader and deeper compliance
& regulation
• Volume and complexity of data
is growing
• May 2018 • Jan 2020
Data Governance
is top of mind
5

6. Only 35%of senior executives have
a high level of trust in
the accuracy of their
Big Data Analytics
KPMG 2016 Global CEO Outlook
92%of executives are concerned
about the negative impact of
data and analytics on
corporate reputation
• KPMG 2017 Global CEO Outlook
Only 2%of firms consider
themselves fully CCPA
compliant today
International Association of Privacy Professionals,
October 2019
Data
Governance
Needs
Data Quality
GDPR Fines 2019: 27
€ 428,545,407https://alpin.io/blog/gdpr-fines-list/
December 15, 2019
The importance of data
quality in the enterprise:
• Compliance
• Decision making
• Customer centricity
• Brand reputation
• Risk Mitigation
6

7. Terminology
& Goals
Data Governance
• The set of policies, processes, rules,
roles and responsibilities that help
organisations manage data as a
corporate asset.
• Ensures the availability, usability,
integrity, accuracy, compliance and
security of data by:
• Putting trusted data assets in the
right hands
• Providing insight across the
organization
• Streamlining data management
with repeatable practices
Data Quality
• The processes and rules that help
ensure that data is “fit for use” in its
intended operational and decision-
making contexts.
• Covers the accuracy, completeness,
consistency, relevance, timeliness and
validity of data by:
• Assessing the current state of data
quality
• Putting rules in place to validate
data in ongoing form
• Delivering insights on data to those
who need to know
7

8. Relevant
Rules & Policies
Data Quality needs appropriate Data Governance tools to ensure the data is
cleaned and maintained within an appropriate data framework which is relevant
and pertinent to the business needs
High Quality Data
Data Governance needs appropriate Data Quality tools to not-only clean the
raw data, but to illustrate data errors, peculiarities and issues, in order to
help compile the best standards and monitor the data quality over time
DQDG
Symbiotic relationship between DQ & DG
8

9. Data Governance Tools
• Help business users define rules to govern the
level of data quality that is acceptable
• Analyze metrics to understand trends, risks,
and costs
• Provide reports for common insight into data
across the organization
• Show data lineage to enhance trust in data and
identify impacts downstream
Data Quality Tools
• Profile the data to determine current state of quality,
distribution of data, relationships between data sets
• Express business rules in valid technical syntax so they
can be evaluated against the actual data
• Measure data to determine compliance with business
rules and thresholds on an ongoing basis
• Correct data to make it more usable, and make it pass
business requirements
Integration of DQ & DG adds insight/value
Right Rules High Quality
9

10. Maximizing Business Value of
Data Use Case
To drive real value, organizations must empower every data citizen to find the
right information, assess its quality and trustworthiness, and use it confidently
to make better decisions.
• Make it discoverable. Help your data users find data that is fit-for-
purpose, discover new datasets crowdsourced by their peers, or tag data
that’s important to them.
• Make it understandable. Give your data users a clear picture of who owns
the data, where it comes from, what it means, and how reliable it is.
• Make it trustworthy. Help your data users know what data they can use,
how to use it, and when to share it.

11. Trillium Discovery
• Market-leading, best-of-breed
data quality solution
• Profile and understand all the
critical data
• Leverage highly flexible business
rules for the right metrics
• Find ALL the DQ issues
Out-of-the-box integration of DQ
metrics with Collibra DGC
✓ bi-directional solution
✓ Automated & synchronized
✓ Configurable to organizational
needs for all profiling results –
broad API support
Collibra DGC
• Market-leading, best-of-breed
data governance solution
• Establish a common
understanding of the business
• Automate governance and
stewardship tasks
• Interact with common workflows
Deploy Trillium’s bi-directional data
quality integration to ensure:
✓ All key business rules are
implemented and validated
✓ DQ metrics are automatically
delivered to those who need to
know when they need to know
Why Trillium and
Collibra?
11

12. Business
Initiative:
Improve Cash
Optimization
Verify Invoicing
Policy & Rules
Approve New Rule
for
Implementation
Implement New
Rule
Investigate &
Monitor
Stewardship
Judy Clark
John Fisher
Mike Jones
FinanceData
Steward
DataQuality
SME
CFO
Business
Raise Issues
Profile Data &
Verify Rule
Integrated DQ facilitates Data Governance Workflow
12

13. Let’s take a look at
it in action…

14. The need for Data Governance is growing
• Regulations are increasing and issues are becoming more frequent and more public
• Significant fines already in Europe
Trillium DQ with Collibra DGC has several unique advantages:
• Bi-directional solution with Collibra
• Automated & synchronized out-of-the-box
• DQ metrics delivered to those who need to know
Trillium DQ
• Rich, robust set of capabilities to profile, evaluate, and measure data quality across platforms
• Simple, straightforward UI to get business analysts quickly working
• Native connectivity and execution which can scale for the largest data volumes and broad array of sources
Key Takeaways
14