1. NON- Invasive Workable
Enterprise Data
Governance
By Bhaven Chavan
bhaven2001@yahoo.com
Confidential | 2016
DISCLAIMER
Note: It is understood that the material in this presentation is intended for general information only and
should not be used in relation to any specific application without independent examination and
verification of its applicability and suitability by professionally qualified personnel. Those making use
thereof or relying thereon assume all risk and liability arising from such use or reliance.

2. Objectives ..Problem
● Understanding our data challenges and link them with our technological
& architectural approaches to meet our business Enterprise Data
(Information) Management modernization needs.
Confidential | 2016

3. Data Challenges ..Problem
● To understand our data challenges and find-out pathways to manage it
○ Data is everywhere
○ Data trust
○ Data quality
○ Multi-channel data (social media, web, clickstream, etc) : Velocity
○ Many types of data from many sources: Variety
○ Data volume
○ Data complexity
Confidential | 2016

4. Where we begin? ..Solution
● All must be workable…
 We ARE already govering data but we are doing it either informally or very vertical in nature.
 We CAN formalize how we govern data by putting structure around what we are persently doing.
 We CAN improve:
• How We Manage Data Risk and Secure Data
• Data Quality and Provide Quality Assurance
• Coordination, Cooperation, Communication Around Data
 We DO NOT Have to spend A Lot of Money.
 We NEED Structure. We should consider a Non-Invasive approach.
• Learning occurs when you see a change in thinking as a result of experience.
Confidential | 2016

5. How we proceed? ..Solution
● Before we start the term “Data Governance”, we have to start with what
and where is governing happening. So, there are three interrelated and
key concepts or terms that needs to be understood:
● Enterprise Information Management
1. EIM is the program that manages enterprise information assets to support the business and improve value.
2. EIM manages the plans, policies, frameworks, technologies, organizations, people, and process in an enterprise
toward the goal of maximizing the investment in data content.
● Data Management
1. The function that develops and executes plans, policies, practices, and projects that acquire, control, protect,
deliver, and enhance the value of data and information.
● Data Architecture
1. A Master set of data models and design approaches identifying the strategic data requirements and the
components of data management, usually at an enterprise level.
Confidential | 2016

6. Governance – V
● Definition: Data governance (DG) refers to the overall management of
the availability, usability, integrity, and security of the data employed in
an enterprise. A sound data governance program includes a governing
body or council, a defined set of procedures, and a plan to execute those
procedures.
Data
Information,
and content
life cycle
Confidential | 2016

7. Enterprise Information Management Framework ..Solution
OrganizationPrograms,Projects,Applications
OrganizationAccountability,&Compliance
Business Principles, Rules, Policies
Definition, standards, location, context
Information everyone references- Asset, Customer, Users, Subscribers, Languages, country, etc.
Information everyone uses to get things done
OTLP Apps
Operational
Reporting
Digital
Products
Analytical/BI
Audit
BusinessMetadataCatalog
EnterpriseArchitecture:Solution,Data,
Integration&BI
Information Life Cycle Management
DataQuality/Profiling
Confidential | 2016
Technology and Infrastructure
Information Integrity – Privacy, Security, Control
Business Environment, Drivers, Goals, Priorities

8. Business Environment, Drivers, Goals, Priorities
Business Principles, Rules, Policies
Definition, standards, location, context
Information Everyone References
or Uses to Get Things Done:
3600 View of the Customer
Data Quality / Profiling
Business Metadata
Catalog
Enterprise
Architecture
Audit
Organizational
Accountability &
Compliance
OrganizationPrograms,Projects,Applications
Technology and Infrastructure, Information Integrity
Data Definition Process
• Process and rules for creating & maintaining Asset
& customer data dictionaries
Data Monitoring & Measurement Process
• Establish rules and metrics for monitoring and
improving customer batch data load performance
Data Access & Delivery Process
• Protocols for timing, maintenance and delivery of
asset & customer data to /from external vendors
and internal clients
Roles &
Responsibilities
BUSINESS & TECHNOLOGY:
• Governing bodies
for data
governance
• Producers vs.
Consumers of
standards
Data Governance
Training & Education
BUSINESS & TECHNOLOGY:
• Establish training
process in
standards and
policies
Data Planning &
Prioritization
BUSINESS:
• Determine
Business Value &
Urgency
TECHNOLOGY-Identify:
• Determine
Technical
Feasibility &
System Impact
Organizational Change
Management
BUSINESS & TECHNOLOGY:
• Manage Data
Governance
Protocols for new
initiatives, e.g.
Kid’s project
Business Metadata
Catalog
BUSINESS &
TECHNOLOGY:
• Asset DD
• Customer Data
Dictionary
• Customer Naming
Conventions
Master (Reference)
Data Standards
• Which type of
customer data (if
any) should be
referenced via
master data?
Enterprise
Architecture Solution
• Are governance
standards in place to
ensure consistency
for data model and
architectural designs
and artifacts?
Technology & Tool Standards
• BUSINESS: Are requirements established regarding
how data will be used, e.g. operational, analytical,
predictive?
• TECHNOLOGY: What are the standards regarding
the right tool for the right client at the right time?
What are the application versioning standards?
What are the data integration tool standards?
EnterpriseDataPlatform:BigDataInitiatives
Data Accessibility
BUSINESS: Which business area can
access Asset, customer?
TECHNOLOGY: Which data store owns
the master data and at what granular
level
Data Availability
BUSINESS: What is the customer data
refresh frequency needed for the
business?
TECHNOLOGY: How are upstream and
downstream customer refresh
dependencies managed?
Data Quality
BUSINESS: Does the
customer data have
business value? Are data
quality controls in place?
TECHNOLOGY: What are
the customer data
cleansing protocols? How
is customer data persisted?
Data Consistency
BUSINESS: Are new parties created across systems
following standardized conventions on a consistent
basis?
TECHNOLOGY: Are customer related tables using
consistent naming conventions, default values,
truncate/load procedures, etc.
Data Security
BUSINESS: Can Creative Services access film production
parties? Can Program Planning access contract licensor
parties?
TECHNOLOGY: Does customer info require encryption
protocols and protection from unauthorized access?
Audit
BUSINESS: Does
customer related data
need to comply with
Sarbox requirements?
TECHNOLOGY: Does
customer related data
require trace or logging
tables, Sarbox rules, etc.?
Information Lifecycle Management

9. Enterprise Data Strategy and Design Framework …Solution
Confidential | 2016
ARM & SRMDRMBRM
End to End Process
Business Process
Detailed Process
Use Stories
Enterprise Data
Subject Areas &
Data Flows
Conceptual data
Model
Logical Data Model
Data Specifications
Major/Minor
System portfolio
System inventory &
process alignment
System Interface
Interface
Specifications
Enterprise Services
and functions
Explicit services &
system specifications
Service
Configuration details
Service Customization
Requirements
Enterprise
Strategy
Enterprise
Design
Segment
Architecture
Solution
Architecture
Business Artifacts Data Artifacts Application Artifacts Technology Artifacts
FEA Reference
Model
Zachman
Principles
S
t
r
a
t
e
g
y
S
o
l
u
t
i
o
n
s
 BRM-
Business
Reference Model
 DRM- Data
Reference Model
 ARM-
Application
Reference Model
 SRM- Security
Reference Model

10. Confidential | 2016
Universal Data Layer- Architectural framework Sample for Discussion..
Dimensional Data Layer
TIME
Asset - Party
Product/Version
Level
Format Level
Reference Data Layer
Prime
RDS
Series
Season
Episode
Product
Version
Format
Party
Genre
Synopsis
Blurb
Title
Synopsis
Award
Plot
Genre
RDS DIM
Asset Core
Asset Derived
Asset Party
Time
Broadcast
C2/Rights
Lowest Grain
Operational/Analytical
UDL
Linear
Schedule
Non-Linear
Schedule
Ad-hoc
Available
New
If needed /Future/Unknown
UDL Information Data Hub
Universal Data Layer Presentation LayerRDS (Reference Data Store)
Asset Core PBL
Asset Episode
Party
Linear/Non-Linear
Service,
Channel,Brand
Language, Org
Territory
Service Media
Service Media
Prime MindRpt
Comment
Offering Sup Role
and Role Group
Burst
Category
Asset_burst_catg
Asset Burst &
Category
Mobile
B2B/B2C
Self Service
Big Data
Analytics
UDL
Others
Affiliate
Device
Available-Not used in UDL
Additional Assets
Bundle
Promo
WIP
Rating/Advisory/CC
Party
Soap
Promo
Bundle
Tower
Restrictions
ProdQry
Tactical
Higher Grain
Analytical UDL
Information
Data
Data
Data
Data Integration
Others
Affiliate/Device

11. Confidential | 2016
RDS Lifecycle
Phase
Concept
Definition and Decision Processes
Discover Need
Idea generation
Initial Assesment
Preliminary
review
In Depth Assesment
Detailed Review
text Prioritization
Rank against
others ideas
text Allocate Resources
Identify funding and
manage resources
text
text = Major Decision Point
NOTE: Phases process activities can be iterative, skipped, or
sequential
Environment Scanning,
Needs Assessment,
Scoping, and Prioritization
Buy, Build, or Integrate
Release
Operate and Manage
Project Lifecycle Process
Kick Off/
Initiate
Plan
Identify
Requirements &
Schedules
Design
Determine Solution
Architecture
text Implement
Build, Buy, or
Integrate Solution
text Release
Provision and Launch
Test text
High Level Project
Scoping
Validate
Production Support & Service Management Process
Service Management (e.g. customer relationship management, Customer Support, Lifecycle management)
Incident and Problem Management (e.g. Monitoring, Troubleshooting, Resolution, Root cause analysis)
Availability Management (e.g. Reliability, Capacity, Business Continuity, Security)
Configuration, Change & Release Mgmt. (e.g. Asset tracking, Upgrades, Change Control reviews)
Replace or Retire
Retire / Introduce Process
Validate Need Research Options
Research replace
or retire options
Provision and Launch
Determine Approach text
Verify need to
Retire / Introduce
Created Date:10/20/2014 Last Changed Date: 10/30/2014 By: Data Architect
Execution Strategy Framework (How?)…Solution

12. Confidential | 2016
Workable Data Governance Operating model of Roles & Responsibilities
TBD

13. Q&A
Confidential | 2016

14. Confidential | 2016