NON- Invasive Workable Enterprise Data

Governance

By Bhaven Chavanbhaven2001@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.

Objectives ..Problem

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

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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

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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.

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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.

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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

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Enterprise Information Management Framework ..Solution

Org

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Pro

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Org

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cco

un

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, & C

om

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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 AppsOperational Reporting

Digital Products

Analytical/BI

Au

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Bu

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ess

Met

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Ente

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Inte

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& B

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Information Life Cycle Management

Dat

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Pro

filin

g

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Technology and InfrastructureInformation Integrity – Privacy, Security, Control

Business Environment, Drivers, Goals, Priorities

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

Org

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n P

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ams,

Pro

ject

s, A

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s

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

ConventionsMaster (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?

Ente

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se D

ata

Pla

tfo

rm:

Big

Dat

a In

itia

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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 ConsistencyBUSINESS: 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 SecurityBUSINESS: 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

Enterprise Data Strategy and Design Framework …Solution

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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

Strategy

Solutions

BRM-Business

Reference Model

DRM- Data

Reference Model

ARM-Application

Reference Model

SRM- Security

Reference Model

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Universal Data Layer- Architectural framework Sample for Discussion..

Dimensional Data Layer

TIME

Asset - Party

Product/Version Level

Format Level

Reference Data Layer

Prime

RDS

SeriesSeasonEpisode

Product

Version

FormatParty

GenreSynopsis

BlurbTitle

Synopsis

Award

Plot

Genre

RDS DIM

Asset Core

Asset Derived

Asset Party

Time

Broadcast

C2/Rights

Lowest GrainOperational/Analytical

UDL

Linear Schedule

Non-Linear Schedule

Ad-hoc

Available

NewIf needed /Future/Unknown

UDL Information Data HubUniversal 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_catgAsset Burst &

Category

Mobile

B2B/B2C

Self Service

Big Data Analytics

UDL

OthersAffiliate

Device

Available-Not used in UDL

Additional AssetsBundle

Promo

WIP

Rating/Advisory/CC

Party

Soap

Promo

Bundle

TowerRestrictions

ProdQry

Tactical

Higher GrainAnalytical UDL

Information

Data

DataData

Data Integration

OthersAffiliate/Device

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RDS Lifecycle Phase

Concept

Definition and Decision Processes

Discover Need

Idea generation

Initial Assesment

Preliminaryreview

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

Confidential | 2016

Workable Data Governance Operating model of Roles & Responsibilities

TBD

Q&A

Confidential | 2016

Confidential | 2016