The CCGDG framework is focused on the following 5 key competencies. These 5 competencies were identified as areas within DG that have the biggest ROI for you, our customer. The pandemic has uncovered many challenges related to governance, therefore the backbone of this model is the emphasis on risk mitigation.
1. Program Management
2. Data Quality
3. Data Architecture
4. Metadata Management
5. Privacy
1. Data Governance
• Welcome & Introductions
• Learning Objectives
• Fundamentals of DG
• Drivers
• Benefits
• CCGDG Framework; the top
5 components of an
effective Data Governance
program
• Competency/Marker Level
Analysis and Scoring
• Prioritization
• Roadmap Creation
• Q & A
3. Agenda
Time Topic
9:00 – 9:10 Housekeeping, Introductions
9:10 – 11:00 Data Governance (DG) Workshop
• Fundamentals of DG (Drivers & Benefits)
• CCGDG Framework Overview
• Competency/Marker Level Analysis and Scoring
11:00-11:10 Break
11:10 – noon • Prioritization
• Roadmap Creation
noon– 12:50 Profisee: Enable Your Master Data Management (MDM) Journey
12:50 – 1:00 Q&A
4. SEND QUESTIONS TO
SAMI. SHE WILL SEND TO
NATALIE TO REVIEW
DURING BREAK.
PLEASE MUTE YOUR LINE!
WE WILL NOT FORCE
MUTE.
LINKS:
SEE CHAT WINDOW
WORKSHEET:
SEE HANDOUTS WINDOW
THIS SESSION WILL NOT
BE RECORDED.
WE WILL SHARE SLIDES
WITH YOU.
TO MAKE PRESENTATION
LARGER, DRAW THE
BOTTOM HALF OF SCREEN
‘UP’
Housekeeping
5. Corporate – Tampa, Florida
Founded by 4 former Arthur Andersen consultants (they still own 100% of our company)
Data & Analytics Solutions & Services since 2006
Case studies on our website:
https://ccganalytics.com/resources/case-studies
CCG Quick Facts
Microsoft Gold Partner in Data Analytics and Cloud. Our consultants have a passion for helping clients
overcome business challenges by leveraging modern analytic solutions
6. CCGDG: A full spectrum of solutionsRapidDG Accelerator
Gain insight into your organizations need for data
governance and what you can do to improve your success
using this lightweight framework that delivers an actionable
roadmap to guide your next year of data governance.
CCG offers a range of solutions to support your data governance journey, starting with our RapidDG accelerator and leading into a
full spectrum of DG offerings to address your organizations unique challenges.
• Operating Model Definition and Enablement
• Business Case Development
• Communication Planning and Execution
• Budget Planning Support
• Training Material Development and Execution
• Policy Assessment and Gap Analysis
• P&P Authoring Support
• Metadata Tool Selection and Enablement
• Architectural Standards Development and Enablement
• Master Data Management Assessment and Enablement
• Data Integration Management
• Regulatory Compliance Support (GDPR/CCPA)
• Data Quality Program Development and Enablement
CCGDG
Data Governance: Strategy & Enablement
7. Director of Strategy and Data Governance, CCG
Accomplished multi-functional executive with a proven track
record of managing global/regional projects and programs
across diverse IT and business environments. Consistently
deliver results and assume responsibilities with increasing
complexity. Recognized as a senior advisor who utilizes
knowledge and insight to create actionable innovation strategies
Learn more by clicking on the links below:
https://ccganalytics.com/solutions/data-governance-data-
management
https://www.linkedin.com/in/nataliegreenwood/
https://www.youtube.com/watch?v=1xrEiGCKeOc
https://blog.ccganalytics.com/data-governance-challenges-
9-ways-overcome
Natalie Greenwood
8. Data Governance Specialist, CCG
Experienced consultant serving wide spectrum of clients across variety
of industries. Delivering long term solutions through business analysis and
data governance expertise. Leveraging multiple Scrum certifications to
successfully manage & strategize in ever changing project environments.
Building analytical deliverables with a strong background in Power BI, SQL,
and Excel.
Learn more by clicking on the links below:
https://ccganalytics.com/solutions/data-governance-data-
management
www.linkedin.com/in/forresthook
Forrest Hook
9. Name, Company, Title, What do you hope to get out of today’s workshop?
Virtual Introductions
10. 1 2 3
10
Describe what Data
Governance is, key
drivers, and benefits
Assess your
organizations DG needs
using the proven DG
framework
Develop an actionable
plan
Workshop Learning Objectives
11. Take one minute to write a short definition of data governance on your sticky note.
Defining Data Governance (DG)
https://funretro.io/publicboard/XNYLqW3gcNR1B2Wl2Jfv5KpuHiz2/0ee1c93c-91d2-4983-9a6a-
2bce1044da18?utm_campaign=Virtual%20Governance%20in%20a%20Time%20of%20Crisis%20%7C%2006-
2020&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz--
6u7BtMiQOSJYu6whzI7mOHU6abF9HkOpBgdGu4Cl8f2ERUPCeMulcVFmZoefpy80O7MRk
12. What is Data Governance?
Data Governance is the organizational approach to
data and information management, formalized as
policies and procedures that encompass the full life
cycle of data, including acquisition, development,
use, and disposal.
Defining DG
13. 1 2 3Inactive
There are some aspects
of DG employed within
the organization, but
there are no enterprise
standards in place(e.g.
the IS team has
developed a data
dictionary).
Reactive
The enterprise is
responding to a specific
issue or problem (e.g.
data breach or audit).
The enterprise is facing
a major change or there
is a potential regulatory
threat to the
organization (e.g. GDPR,
acquisitions, or
preparing for a public
offering)
Proactive
The enterprise
recognizes the value of
data and has decided to
treat data as a corporate
asset (e.g. recruitment of
a CDO, budgeted DG
program, etc.).
Key Drivers for Data Governance:
What are your organizational drivers?
Please post in comments section
14. 1 2 3Increase Revenue
Improve
profitability with
better analytics
for improved
decision making
Increase
opportunity
through
availability of
information for
business insights
and competitive
advantage
Reduce Cost through
Operational
Efficiencies
Standardized and
high quality
information
Reduce IT costs
by reducing
duplicate work
effort or re-work
Minimize Risk
Reduce regulatory
compliance risk and
improve confidence in
operational and
management decisions
Provide better insights
into fraud with improved
analytics; Improve
reporting to regulators
and authorities through
defined data processes
and data management
Benefits of Data Governance
What benefits will your organization realize?
Please post in comments section
17. We needed to assess faster, deriving actionable insights that could be quickly implemented with
minimal disruption.
To achieve this, we needed to develop a simplified, more targeted framework and methodology.
18. I don’t trust my data
(Data Quality)
Data architecture is the wild,
wild west
(Data Architecture)
There is no single way to
request data/reports
(Data Architecture)
I don’t know how my metrics
are defined
(Metadata Management)
I can’t tell you what source
system the data came from
(Metadata Management)
I don’t know who has access to
the data
(Data Architecture)
I don’t know who is responsible
for the data
(Program Management)
We don’t classify or manage
sensitive data
(Data Architecture)
I’m not sure what policies and
procedures exist for approving
data access or if they are up-to-
date
(Data Privacy)
I’m responsible for
implementing GDPR or CCPA
and I have no idea where to
start?
(Data Privacy)
Most Common Challenges/Themes
What are your challenges?
Please post in comments section
19. CCGDG establishes five proven competencies that are
the backbone of our data governance framework.
Program Management
Data Architecture
Data Privacy
Data Quality
Metadata Management
CCGDG Framework
20. At CCG, we measure maturity across 5 competencies, each comprised of several
markers. We rate Program Management on a 1-5 scale, and the others on a 1-3 scale.
23. Enforced
The enterprise-wide DG
Program is well
established. Adherence is
mandatory for assigned
business units. Business
units rely on the
enterprise for direction.
Shared
Accountability
Governance is centrally
controlled. Adherence is
measured. Continuous
monitoring and program
improvement as the
organization scales.
Emerging
Enterprise-wide DG
Program planning &
requirements gathering
has begun. Business units
are primarily siloed and
making governance
decisions locally.
Sponsored
An enterprise-wide
sponsored DG Program
has been defined. Business
Units are encouraged to
adhere. Adoption in
critical business units
started.
Undisciplined
There is no Enterprise-
wide DG Program or
enterprise support. DG is
not considered a priority
and/or is managed locally
within individual business
units.
1
2
3
4
5
Program Management
Maturity
Capability
Rate yourself!
Capability Maturity Model: Level 1
24. Consider your
level of maturity
within each
marker
https://funretro.io/publicboard/XNYLqW3gcNR1B2Wl2Jfv5KpuHiz2/fafffcec-4d39-4155-a228-81e2c9e87895
Data architecture is a broad term that refers to the
set of policies, standards, functions, methods,
processes, procedures, tools, and models that
govern and define the type of data, information, and
content collected, and how it is used, stored,
managed and integrated within an organization and
in and between its data stores.
Data Architecture
26. What metadata
management
functions do you
have/need
enabled?
https://funretro.io/publicboard/XNYLqW3gcNR1B2Wl2Jfv5KpuHiz2/fafffcec-4d39-4155-a228-81e2c9e87895
The set of policies, standards, functions,
processes, procedures and tools utilized and
adhered to that form the behavioral model
through which the administration and
management of an organization’s metadata
resources can take place.
Metadata Management
31. Legal Disclaimer
CCG Analytics Solutions & Services (“CCG”) is not a law firm, nor does it represent one. Therefore, neither CCG, nor any of its employees,
consultants, and sub-contractors provide legal advice on data privacy regulations (e.g. CCPA).
CCG expects that any enterprise that engages CCG leverages the enterprise’s Legal and Data Privacy experts, often with outside Counsel, to
interpret the data privacy regulation or law (e.g. CCPA) as they require.
Furthermore, CCG expects that the designated enterprise’s Legal and Data Privacy expert(s) participate throughout any engagement
involving CCG to provide advice, guidance and interpretation (along with advice and/or guidance from designated outside Counsel) of the
impact of the data privacy regulation or law (e.g. CCPA) on the enterprise.
CCG’s role is not to provide this advice and/or guidance, but rather CCG partners with the appropriate enterprise Legal and Data Privacy
experts and other key personnel in Data Governance, IT, Risk, Procurement, etc., to translate the Legal and Data Privacy experts’
interpretation into operationalized practices supporting data privacy compliance.
CCG does not guarantee compliance with any applicable laws and/or regulations (e.g. CCPA) in any jurisdictions (e.g. European Union.) The
expectation is that the enterprise reviews and vets the CCG work products – including, but not limited to - content, deliverables, Readiness
Assessment tools (e.g. CCPA) – essentially all artifacts – with accredited legal experts for final opinions.
32. 32
Data Privacy Markers
Data Classification
The practice of formally tagging and classifying data in documentation and metadata to serve as guidance in use of the data. Data classification tags
data according to its type, sensitivity, and value to the organization if altered, stolen, or destroyed. It helps an organization understand the value of
its data, determine whether the data is at risk, and implement controls to mitigate risks. Data classification also helps an organization comply with
relevant industry-specific regulatory mandates such as SOX, HIPAA, PCI DSS, and GDPR.
Classification categories typically consist of:
Personal Information (PI): Any data that can reasonably be linked to an individual
Personally Identifying Information (PII): the subset of PI that is data elements that are identifiers of an individual, e.g. Social Security Number,
Driver’s License Number (and which are most important in identity theft)
Sensitive Personal Information (SPI): the subset of PI that is information which does not identify a person, but which they would reasonably want to
keep private, e.g. medial records, employment information, criminal record, credit history.
Retention & Disposition
A retention and disposition policy / schedule is a plan of action that indicates the period of time an organization should retain records. Records
schedules allow you to dispose of records in a timely, systematic manner by setting retention and disposal guidelines based on administrative, legal,
fiscal, or research needs.
Disposition refers to the final decision about whether to dispose of records or keep records permanently. Disposition of records can mean either
destroying them or formally donating them to another organization after the records have met their legal retention period.
Data Access Control Auditing
Systematic, documented, and regularly scheduled processes for auditing data access controls are necessary to ensuring that proper accesses are
granted to the right people for the right data at the right time.
Process Register
A data processing register is a record of which personal data an organization processes and who/where the organization shares this data with. This
enables an organization to reveal what exactly has been done with a customer's data since recorded into the organization's systems. This is crucial in
the event of litigation.
Consent Management
Consent management is a system, process or set of policies for allowing consumers to determine what data/information they are willing to allow an
organization to acquire, retain, and distribute. Record of the "consent" should be retained for legal liability. This enables an organization to reveal
what exactly has been done with a customer's data since recorded into the organization's systems. This is crucial in the event of litigation.
Consent has to be: freely given, specific, informed, and unambiguous.
Regulatory Reporting
Regulatory reporting consists of all legal context around Data Privacy.
Relevant regulations consist of SOX, HIPAA, PCI DSS, CCPA, and GDPR.
33. Overview of Data Privacy Technology Implementation
• Today there is an ever-expanding range of options for Data Privacy
technologies.
• Some of these technologies and purely focused on Data Privacy
needs. Others are more general tools which incorporate specific
Data Privacy capabilities.
• CCG helps clients to implement these tools and adapt them to the
client’s specific needs.
• Since Data Privacy is new and not always intuitive, CCG is careful to
include training that links Data Privacy concepts and best practices
to specific tool capabilities.
35. Using your competency scores, prioritize your action items on your placemat
Action Plan
Improve system utilization and process
efficiency, advanced analytics
Data
Architecture
Clearer communication, better decisions
Metadata
Management
Cost avoidance, regulatory compliance
DataPrivacy
Better decisions, clearer insight
DataQuality
Improve resource allocation, strategic support
Program
Management
ROIWrite your findings hereCompetency
36. 1 2 3
36
Describe what Data
Governance is, key
drivers, and benefits
Assess your
organizations DG needs
using the proven DG
framework
Develop an actionable
plan
Recap on Learning Objectives
39. Solutions Engineer, Profisee
John is a highly motivated, results-driven executive
consultant with twenty years of experience serving clients in
several industries; including high tech, retail,
airline/aerospace, government (Federal, State, Municipal),
consumer packaged goods, and financial services.
He has deep experience in setting the direction and
priorities for entire organizations as well as individual
business functions like operations, sales, research and
development and finance.
John is a subject-matter expert in Master Data Management
with a focus on strategy, governance, and process.
John Rossiter
43. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Data Quality
Data Profiling
Deduplication
Data Governance
Data Glossary
Data Catalog
Policies
Master Data
Management
Data
Modeling
Golden
Record
Management
Data
Stewardship
Workflow
Management
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
Engage Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
Customer Journey
Realization of full business value
Solution Platform
Industrial strength with full flexibility
44. 05_01_20
ENGAGE AND ENABLE
Data
Stewardship
Workflow
Management
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
Engage Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
Customer Journey
Realization of full business value
Solution Platform
Industrial strength with full flexibility
46. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Enable
MDM Fast Start
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
• Business
• Volume-based pricing, with no domain limits
• Attractive services ratio
• Self-service training
• Technical
• Installation
• Modeling
• Batch integration
• Data Quality
• GRM
• Reporting
• Real-time integration
• Workflow
PROFISEE HAS
MORE
IMPLEMENTATI
ONS TAKING
UNDER THREE
MONTHS THAN
ANY OTHER
VENDOR IN
THIS MAGIC
QUADRANT.
- GARTNER
47. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
• “Failure to use a structured framework that delivers financial
benefits …often leads to program failure.”
• Business Impact Roadmap
1. Builds stakeholder buy-in
2. Develops value prioritization
• Collaboration/communication/clarification around BIR reduces
program risk
#1
REASON
FOR MDM
FAILURE
- GARTNER
Business Impact Roadmap
48. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Data Verification/
Standardization
Data Quality
Rules
Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
• ‘The only constant is change’
• External events
• Changes in business requirements
• Changes in data sources
• Additional use cases and domains
• Evolving/tightening MDM styles
ITERAT
E.
REPEAT
.
EVALUA
TE.
- AGILE
DEVELOPMENT
PRINCIPLES
Iterative Deployment
49. 05_01_20
ENGAGE AND ENABLE
Data
Stewardship
Workflow
Management
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
Engage Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
Customer Journey
Realization of full business value
Solution Platform
Industrial strength with full flexibility
50. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
Engage Enable
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
51. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
• Any real-world business outcome touches on multiple domains
• Profisee is inherently multi-domain
• Typical customer has multiple domains
• Some with up to 10 domains running in a single production environment
• ‘Most multi-domain’ vendor, according to Gartner*
• The ‘right’ MDM style will change over time
• Profisee is inherently multi-style
• All MDM styles supported, including hybrid
• Easy to evolve style as implementation maturity develops
Multi-Domain, Multi-Style
REGISTRY CONSOLIDATED COEXISTENCE CENTRALIZED
52. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Data Verification/
Standardization
Data Quality
Rules
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
• Consistent user experience
• Shorter learning curve
• Faster configuration
Single Code Base
Other Vendors
Workflow Stewardship
Golden Record
Management
Event
Management
Data Quality
Hierarchy
Management
Matching
*some assembly required
53. 05_01_20
DATA MANAGEMENT SOLUTION SPACE
Multi-domain,
Multi-Style
Single
Code Base
Cloud-Native
Architecture
Cloud Native Architecture
Workflow
API Gateway
ProfiseeCore
File
Attachment
Portal Pod
Kubernetes Service
Database Server
Repository
File Server
Workflow
API Gateway
ProfiseeCore
File
Attachment
Portal Pod
Kubernetes Service
Workflow
API Gateway
ProfiseeCore
File
Attachment
Portal Pod
Kubernetes Service
Load Balancer
Cloud-native architecture also benefits
on-premise deployment
= Containerized Microservice