Enterprise Data Management - Audit and Evolve

1. Enterprise Data Management
Audit and work towards futuristic EDM
capabilities
Discovery Workshop – Initial Session

2. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
High Level Objective/Agenda
Discussion on the provided response to the Questionnaire
In order to Identify the desired future vision and its success criteria
Right path to start and long term vision assessment
Business Goals
Facilitated session helping stakeholders identify their current business problems
Identify the desired future vision and its success criteria
Facilitated session helping stakeholders identify the top three high level use cases for data analytics
Understand the business value of these use cases
Discussion around potential solutions using new generation data services
EDM Technology Landscape
Describe ongoing endeavours, the current EDM technology platform, people and processes
Identify data governance and security requirements
Assess the available data stewardship framework, if any
Determine how technology and processes are used, and identify improvement and modernization opportunities to align with the stated data strategy vision
Understand need for a multi-layer data architecture implementation
Data and Architecture Qualification
Interview data owners and subject matter experts to identify data characteristics – Various Source Systems Details
Determine what data exists, where it resides and identify any required transformations
Volumetrics, Types and Availability
Data Security Requirement Identification
Data Temperature Considerations
Data Architecture Design Discussions
Data Governance Future Expectations
Data Consumption Patterns Discussion
Microsoft
Word Document

3. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
Key Observations Summary So far…
Awareness about Data Importance is very high
Current Data Use case spans – strategic, planning, decision making, service and product improvement
purposes
Right Data is collected for clearly specified, explicit and legitimate purposes. Data Quality awareness
about the extracted data needs attention
Data Analysis is automated and primarily of operational report and descriptive analytics nature
Some of the Analytics Approaches used are – Basic count/charts, averages, variation, range, past
trends
Data Experimentation and Advanced Analytical Capabilities Support is not available currently
Data Program is a major organisational priority – Including upliftment of Organizational Skillset

4. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
High Level Objective/Agenda
Discussion on the provided response to the Questionnaire
In order to Identify the desired future vision and its success criteria
Right path to start and long term vision assessment
Business Goals
Facilitated session helping stakeholders identify their current business problems
Identify the desired future vision and its success criteria
Facilitated session helping stakeholders identify the top three high level use cases for data analytics
Understand the business value of these use cases
Discussion around potential solutions using new generation data services
EDM Technology Landscape
Describe ongoing endeavours, the current EDM technology platform, people and processes
Identify data governance and security requirements
Assess the available data stewardship framework, if any
Determine how technology and processes are used, and identify improvement and modernization opportunities to align with the stated data strategy vision
Understand need for a multi-layer data architecture implementation
Data and Architecture Qualification
Interview data owners and subject matter experts to identify data characteristics – Various Source Systems Details
Determine what data exists, where it resides and identify any required transformations
Volumetrics, Types and Availability
Data Security Requirement Identification
Data Temperature Considerations
Data Architecture Design Discussions
Data Governance Future Expectations
Data Consumption Patterns Discussion

5. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
SAMPLE Use Cases
Microsoft
Excel Worksheet

6. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
High Level Objective/Agenda
Discussion on the provided response to the Questionnaire
In order to Identify the desired future vision and its success criteria
Right path to start and long term vision assessment
Business Goals
Facilitated session helping stakeholders identify their current business problems
Identify the desired future vision and its success criteria
Facilitated session helping stakeholders identify the top three high level use cases for data analytics
Understand the business value of these use cases
Discussion around potential solutions using new generation data services
EDM Technology Landscape
Describe ongoing endeavours, the current EDM technology platform, people and processes
Identify data governance and security requirements
Assess the available data stewardship framework, if any
Determine how technology and processes are used, and identify improvement and modernization opportunities to align with the stated data strategy vision
Understand need for a multi-layer data architecture implementation
Data and Architecture Qualification
Interview data owners and subject matter experts to identify data characteristics – Various Source Systems Details
Determine what data exists, where it resides and identify any required transformations
Volumetrics, Types and Availability
Data Security Requirement Identification
Data Temperature Considerations
Data Architecture Design Discussions
Data Governance Future Expectations
Data Consumption Patterns Discussion

7. Every Organisation Needs An Effective Enterprise Data Strategy
Data Development
Data Quality Management
Data Operations Management
Metadata Management
Document and Content Management
Reference and Master Data Management
Data Architecture
Management
Data Governance
Data Warehousing and Business Intelligence
Management
Data Security Management
Reporting
Insight/
Forecast
Monitoring Analysis
Solid
Data
Management
Foundation
and
Framework
} You Cannot
Have This ...
... Without
This

8. Channel
Sources
Images/Documents
In Sync Host
Application Log
Audio & Video
Core System
CRM
Finance
BTB
Channels
Corporate
website Agents
POS
IVR Call
Center SMS eMail
Mail
Mobile
App
Social
Media
Analytic Tools & Applications
BI / Report / Query
MIS / Dashboard / Alerts
Applications
Regulatory
BI Tool
Others
Visualization
Visualization Tool
Digital experience
BU Performance
Operation Dashboard
Data Service and Management
Hybrid Cloud Data Quality Data Security Metadata
Data Governance Architecture &
Standards
Data Integration and Platform Management
Data Ingestion/ ETL / ELT Tool Platform Management
Accounting
HUB
Real-Time
Marketing
Operational
Analytics
Real-Time
Services
Data Science
Data Lab/ Data Science
AI/ML
The Nirvana State
Logical View of the Analytical Data Platform environment

9. Data Audit Views - High Level Categories
 Data Landscape View – quantify and understand where data exists
 Data Supply Chain View – quantify and understand data exchanges and interfaces
 Data Model View – quantify and understand the development and specification of the enterprise
data model
 Data Lifecycle View – identify how well the processes and the controls associated with the lifecycle
stages are defined
 Current Information And Data Architecture And Data Strategy View - identify current information and
data architecture and implementation and operational under the key component areas
 Current Data Management View – quantify the relative importance and current state of
implementation and operation of data management components and functional elements

10. Data Management View – Importance and Status
 Coding of data management components and functional
elements
= High Importance = Good State
= Medium Importance = Medium State
= Low Importance = Poor State
 Understand their importance and current state of
implementation and operation

11. Goals and
Principles
Activities Primary
Deliverables
Roles and
Responsibilities
Practices and
Techniques
Technology Organisation
and Culture
Importance
Current
State
Importance
Current
State
Importance
Current
State
Importance
Current
State
Importance
Current
State
Importance
Current
State
Importance
Current
State
Data Governance
Data Architecture
Management
Data Development
Data Operations
Management
Data Security
Management
Data Quality
Management
Reference and Master
Data Management
Data Warehousing and
Business Intelligence
Management
Document and
Content Management
Metadata
Management
Data Management View – Importance and State

12. Data Audit Approach – Application Landscape
Application
1
Application
2
Application
3
Application
4
Application
5
Application
6
Application
7
Application
8
Application
9

13. Data Audit Approach – Infrastructure And System View
Application
Web Server
Database
Web Server
Application
Server
Application
Server
Database Server Database Server
Load Balancer Load Balancer Authentication
Server
User Directory
Firewall Firewall
Consists
of

14. Classification Information By Operational Data, Master and Reference Data, Analytic
Data and Unstructured Data
Architect, Budget, Plan, Design andSpecify
Enter, Create, Acquire, Derive, Update, Integrate,
Capture
Secure, Store, Replicate andDistribute
Present, Report, Analyse,Model
Preserve, Protect andRecover
Archive and Recall
Delete/Remove
Implement Underlying Technology
Define, Design, Implement, Measure,Manage,
Monitor, Control, Staff, Train and Administer,
Standards, Governance,Fund
Operational
Data
Analytic and Unstructured
Derived Data Data
Master and
Reference
Data

15. Business Functions And Application Use
Application1 Application2 Application3
Application4 Application5 Application6
Application7 Application8 Application9
Business
Function1
Business
Function2
Business
Function3
Business
Function4

16. Identify How Well The Processes And Their Controls Associated With The
Lifecycle Stages Are Defined
Architect, Budget, Plan, Design andSpecify
Enter, Create, Acquire, Derive, Update, Integrate,
Capture
Secure, Store, Replicate andDistribute
Present, Report, Analyse,Model
Preserve, Protect andRecover
Archive and Recall
Delete/Remove
Implement Underlying Technology
Define, Design, Implement, Measure,Manage,
Monitor, Control, Staff, Train and Administer,
Standards, Governance,Fund
Data Type
1
Data Type
3
Data Type
4
Data Type
2

17. Current Information and Data Architecture And Data Strategy and View
• Review current information and data
architecture and implementation
and operational under the key
component areas
Information and Data
Architecture
Data Governance
Data Architecture
Management
Data Development
Data Operations
Management
Data Security Management Data Quality Management
Reference and Master Data
Management
Data Warehousing and
Business Intelligence
Management
Document and Content
Management Metadata Management

18. Channel
Sources
Images/Documents
Application Log
Audio & Video
BTB
Channels
Corporate
website Agents
POS
IVR Call
Center SMS eMail
Mail
Mobile
App
Social
Media
Analytic Tools & Applications
BI / Report / Query
MIS / Dashboard / Alerts
Applications
Regulatory
BI Tool
Others
Visualization
Visualization Tool
Digital experience
BU Performance
Operation Dashboard
Data Service and Management
Hybrid Cloud Data Quality Data Security Metadata
Data Governance Architecture &
Standards
Data Integration and Platform Management
Data Ingestion/ ETL / ELT Tool Platform Management
Accounting
HUB
Real-Time
Marketing
Operational
Analytics
Real-Time
Services
Data Science
Data Lab/ Data Science
AI/ML
High Level Ecosystem View
Please help fill the source system details

19. Elements Of Information And Data Management Strategy
 Vision for data management
 Summary business case for data management
 Guiding principles, values, and management perspectives
 Mission and long-term directional goals of data management
 Management measures of data management success
 Short-term data management programme objectives
 Descriptions of data management roles and business units along with a summary of
their responsibilities and decision rights
 Descriptions of data management programme components and initiatives
 Outline of the data management implementation roadmap
 Scope boundaries

20. Data Management Strategy
Generic Post Audit Phase Activities
Data Management
Scope Statement
Goals and objectives for a
defined planning horizon and
the roles, organisations, and
individual leaders accountable
for achieving these objectives
Data Management
Programme Charter
Overall vision, business case,
goals, guiding principles,
measures of success, critical
success factors, recognised risks
Data Management
Implementation
Roadmap
Identifying specific programs,
projects, task assignments, and
delivery milestones

21. Thanks