Dhivya Venkatachalam - Data Governance in the cloud first world Digital Transformations and Cloud ecosystems are an inevitable reality for all modern organisations. In this journey to the cloud, Data Management and Governance becomes the need of the day. Without good data, all existing inefficiencies and limitations get propagated to the clouds. It’s essential to have good quality data available, accessible and secure to derive business value from your cloud implementations. In this session, we will talk about data focussed preparation to start your journey, what to look out for in an implementation and how to make cloud data governance operational. We will also look at data and information assets that help with the implementation, best practices and how best to embed our cloud data governance into Business As Usual

1. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Data Governance in a Cloud First
World
June 2019 2018
Cloud Security Alliance AGM 2019
Dhivya Venkatachalam
Data Synergie1
© Data Synergie, 2018
www.datasynergie.com

2. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Introduction to the Speaker
 Dhivya Venkatachalam is a Data & Information expert, advisor and a
speaker.
 Dhivya has been instrumental in building the Data Area from ground up
in organisations and enjoys supporting the delivery of complex
information-centric transformation programs.
 Before Data Synergie, Dhivya headed up the Data Governance Practice
at Schroder Investment Management.
 Dhivya also runs very successful training programs in Data Governance,
Management and GDPR/Data Protection training programs and
awareness campaigns in organisations.
dhivya@datasynergie.com
www.linkedin.com/in/dhivyavenkatachalam
@datasynergie
2

3. © Data Synergie, 2019
www.datasynergie.comData Governance in the 3
Data Governance Framework
The Big Picture
Ecosystem
Project
Management
Change
Management
Risk and Audit
Value
Generation
Framework (DG)
Operational
Models
Operating
Bodies
Workflow
Measures and
Metrics
Foundations
People Policy Procedure Process

4. © Data Synergie, 2019
www.datasynergie.comData Governance in the
How is the Cloud Different?
4
 Cloud seen as an IT Offering
 Complexity
 Agility, Flexibility
 Operational and Regulatory challenges
(Storage and Processing)
 Cloud based Actors and Structure
 Cloud Deployment and Service delivery
models
 Cloud Based KPIs

5. © Data Synergie, 2019
www.datasynergie.comData Governance in the
The Journey to the Cloud
5
 Before you start
 Know your data
 Classify
 Get the Stakeholders involved
 Work out Success Criteria
 Extend your information Ecosystem

6. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Data Catalogue
Data
Dictionary
•Data Entity &
Characteristics –
Name, Description,
Owner, Usage,
Purpose
•Relationships (
between Objects) –
Name, Description,
Definition
•Metadata
•Criticality
•Special
circumstances
Information
Classification
•Classification
According to
Information
Security
•GDPR
Classification
•Confidentiality
Marker
Data Quality
•Quality Statement
•Metrics
•RAG Rating ( for
quality)
•Best Source
Data
Ownership
•Owner
•Steward
•Other Stakeholders
( Responsibility)
•Any Governance
Process Associated
Data Policy
•Data Rules
•Required retention
period
Data Lineage
(captured as
applications)
•Information
Producers
•Information
Consumers
•Information
Transformers
Know your Data

7. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Data Architecture led
7
 Know your data should also have a good data
model / schema attached
 Data Lineage and Integrations

8. © Data Synergie, 2019
www.datasynergie.comData Governance in the
The People – Accountability
Model8
Data Governance Working Group
Moderator: Data Governance Analyst
Attendees : Project representatives, IT
Representatives, Operational Stewards, Data Analyst
Data Governance Steering Group
Moderator: Data Governance Officer Attendees : Data Stewards, Data Analyst
Data Governance Council
Data Owners

9. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Accountability Model
9
Data Governance Working Group
Moderator: Data Governance Analyst
Attendees : Project representatives, IT
Representatives, Operational Stewards,
Data Analyst, Cloud Actors
Data Governance Steering Group
Moderator: Data Governance Officer
Attendees : Data Stewards, Data Analyst,
Cloud Admin
Data Governance Council
Data Owners
1. Cascading Levels of
responsibility at the
right level
2. Identifying the right
people, right application
and the right process
(data stewards)
3. Tracking and Traceability
between the levels (MI)
4. Management of Data
throughout its lifecycle (
from creation to archive)
5. To maintain and
propagate good data

10. © Data Synergie, 2019
www.datasynergie.comData Governance in the
10
Deliverables –
Data Architecture Led
DataGovernance
Deliverables
• Principles
• Ownership and
Accountability Model
• Rules of Engagement
• Roles and Responsibilities
• Controls
• Data Standards
• Glossaries
• Metrics, Audits and
Assessments
• Tools for DG
DataArchitecture
Deliverables
• Digital Twinning
• Documentation
• Systems
• Data Flows
• Control Points
• Target Data Models
• Canonical Schemas
• Data Dictionary

11. © Data Synergie, 2019
www.datasynergie.comData Governance in the
The Business As Usual
11
 Cloud governance to be an extension of
Traditional Data Governance
 Embed in organisational Ecosystem
 KPIs and Metrics – Define and Track

12. © Data Synergie, 2019
www.datasynergie.comData Governance in the 12
Data Governance Framework
The Big Picture
Ecosystem
Project
Management
Change
Management
Risk and Audit
Cloud
Governance
Framework (DG)
Operational
Models
Operating
Bodies
Workflow
Measures and
Metrics
Foundations
People Policy Procedure Process

13. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Data Factors
Unstructured Data
Lack of a proper data
taxonomy and model
The Variety and Volume
of the data areas / entities
Lack of proper data
management
Technology
Deployment Model
Service Delivery Model
Complexity of the
underlying systems and
technology
Maturity of the system
Number and locations of
the source system
People &
Organization
Self Service Model and
Awareness
Culture of the company
Complexity of
organization
Number of products and
offerings
Process
Trinity of IT, Data and
Cloud Governance
Lack of documentation
and audit trails
Complex business
process that complicate
underlying data
Maturity of the process
Challenges

14. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Best Practices
 Value creation by moving to the Cloud – Focus on and
Communicate
 Build strong foundations before the journey to the cloud
 Govern Data Areas and not the platform, application or
location
 Reuse and build from existing infrastructure
 Data Integration efforts to be robust
 Work breakdown approach – without losing the big picture
 Build “living” data and information assets
 Meaningful measures and metrics
 React, record and refine
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15. © Data Synergie, 2019
www.datasynergie.comData Governance in the
Data Synergie – Who are we ?
15
 Data Synergie works with enterprises to build a sustainable, holistic data
ecosystem where all facets of data (data governance, management,
security, architecture, analytics and the data in projects) in the enterprise
work seamlessly together to create better value for the organization.
 Data Synergie specialize in Data requirements for Governance, Risk and
Compliance
 Data Synergie provides an accelerator and templates that help the Data,
Technology and the business teams to collaborate around Data and build a
holistic and sustainable data ecosystem in the organisation.
 Data Synergie also runs successful Data Governance, Management and
GDPR/Data Protection training programs and awareness campaigns in
organisations.