The Rise of the CDO in Today's Enterprise

@joe_Caserta #ChiefDataNY@joe_Caserta
The Rise of the CDO in Today’s Enterprise
Presented By:
Joe Caserta
Dec 7, 2016
@joe_Caserta
@casertaconcepts
Chief Data Officer Summit
New York City
#ChiefDataNY

@joe_Caserta #ChiefDataNY
Joe Caserta Timeline
Launched Big Data practice
Co-author, with Ralph Kimball, The Data
Warehouse ETL Toolkit (Wiley)
Data Analysis, Data Warehousing and Business
Intelligence since 1996
Began consulting database programing and data
modeling 25+ years hands-on experience building database
solutions
Founded Caserta Concepts in NYC
Web log analytics solution published in Intelligent
Enterprise magazine
Launched Data Science, Data Interaction and Cloud
practices
Laser focus on extending Data Analytics with Big Data
solutions
1986
2004
1996
2009
2001
2013
2012
2014
Dedicated to Data Governance Techniques on Big
Data (Innovation)
Awarded Top 20 Big Data Companies 2016
Top 20 Most Powerful
Big Data consulting firms
Launched Big Data Warehousing (BDW) Meetup NYC:
2,000+ Members
2016 Awarded Fastest Growing Big Data Companies
2016
Established best practices for big data ecosystem
implementations

About Caserta Concepts
– Consulting Data Innovation
– Award-winning company
– Internationally recognized work force
– Strategy, Architecture, Implementation, Governance
– Innovation Partner
– Strategic Consulting
– Advanced Architecture
– Build & Deploy
• Leader in Enterprise Data Solutions
– Big Data Analytics
– Data Warehousing
– Business Intelligence
Data Science
Cloud Computing
Data Governance

Caserta Client Portfolio
Retail/eCommerce
& Manufacturing
Finance, Healthcare
& Insurance
Digital Media/AdTech
Education & Services

Awards & Recognition
Top 10
Fastest Growing
Big Data Companies
2016

Why is Data So Important?

A Day in the Life of Data
Business: “I need to analyze some new data”
ü   IT collects requirements
ü   Creates normalized and/or dimensional data models
ü   Profiles and conforms and the data
ü   Sophisticated ETL programs and quality standards
ü   Loads it into data models
ü   Builds a BI semantic layer
ü   Creates dashboards and reports
IT: “You can access your data in 3-6 months to see if it has value!
– Onboarding new data is difficult!
– Rigid Structures and Data Governance
– Disconnected/removed from business

Houston, we have a Problem: Data Sprawl
• There is one application for every 5-10 employees generating copies of
the same files leading to massive amounts of duplicate idle data strewn
all across the enterprise.                   - Michael Vizard, ITBusinessEdge.com
• Employees spend 35% of their work time searching for information...
finding what they seek 50% of the time or less.
                                          - “ The High Cost of Not Finding Information,” IDC

The New Data Paradigm
OLD WAY:
• Structure Data  Ingest Data  Analyze Data
• Fully Governed
• Monolith
NEW WAY:
• Ingest Data  Analyze Data  Structure Data
• Just Enough Governance
• Dynamic
RECIPE:
• Data Officer & Data Organization
• Enterprise Data Lake
• Corporate Data Pyramid

Why a Chief Data Officer?
• Evangelize a data vision for the organization
• Support & enforce data governance policies via outreach, training & tools
• Monitor and enforce data quality in collaboration with data owners
• Monitor and enforce data security along with Legal/Security/Compliance
• Work with IT to develop/maintain an enterprise repository of strategic data
• Set standards for analytical reporting and generate data insights
• Provide a single point of accountability for data
initiatives and issues
• Innovate ways to use existing data
• Enrich and augment data by combining internal and
external sources
• Support efficient and agile analytics through training
and templates

The CDO: The Whole Brain Challenge
Front
Back
Analytics Oriented
• Data Science
• Research
Process Oriented
• Data Governance
• Compliance
Operations Oriented
• Shared Services
• Data Engineering
Revenue Oriented
• Revenue Goals
• Monetizing Data

Data Officer
•Create and evangelize vision,
strategy, and mission statement
•Create, communicate, and
enforce policies, procedures, and
processes
•Plan, prioritize, and project
manage data initiatives
•Prepare & maintain budget for
staff, infrastructure, services,
tools & training
•Innovate ways to use existing
data
•Enrich and augment data by
combining internal and external
sources
•Protection – ensuring data
privacy and security
•Upkeep – managing the health of
data under governance
Data Governance Lead
•Represent business interests
across departments
•Prioritize and manage data
requests and remediation efforts
•Identify pockets of business,
technical, and data expertise
•Socialize policies and support
programs
Data Stewards
•Receive, manage, prioritize and
track data quality issues
•Proactively lead data quality
monitoring of high value data
•Identify, train, and manage
critical data sources
•Ensure remediation efforts follow
change management policies
•Assist in management and
maintenance of master data
Data Librarian
•Track and manage data related
assets (sources, metadata,
business glossary, data lineage)
•Track and manage common
queries with embedded business
logic
•Track and manage canned reports
(to prevent duplication)
•Track and manage custom reports
(to prevent duplication)
•Track and manage standard
reports and dashboard templates
•Track internal and external data
and tool experts
•Socialize content being managed
with user community
•Manage the Data Governance
knowledge repository
Data Organization Roles

Chief Data Organization (Oversight)
Vertical Business Area
[Sales/Finance/Marketing/Operations/Customer Svc]
Product Owner
SCRUM Master
Development Team
Business Subject Matter Expertise
Data Librarian/Data Stewardship
Data Science/ Statistical Skills
Data Engineering / Architecture
Presentation/ BI Report Development Skills
Data Quality Assurance
DevOps
IT Organization
(Oversight)
Enterprise Data Architect
Solution Engineers
Data Integration Practice
User Experience Practice
QA Practice
Operations Practice
Advanced Analytics
Business Analysts
Data Analysts
Data Scientists
Statisticians
Data Engineers
Planning Organization
Project Managers
Data Organization
Data Gov Coordinator
Data Librarians
Data Stewards
It Takes a Village!

Unexpected Reaction to Change

Global economics
Intensity of competition
Reduce costs
Move to cross-functional teams
New executive leadership
Speed of technical change
Social trends and changes
Period of time in present role
Status & perks of office/dept under threat
No apparent reasons for proposed changes
Lack of understanding of proposed changes
Fear of inability to cope with new technology
Concern over job security
Forces for Change Forces Resisting Change
Status Quo
Moving the Status Quo
http://www.change-management-coach.com/force-field-analysis.html

Ingest Raw
Data
Organize, Define,
Complete
Munging, Blending
Machine Learning
Data Quality and Monitoring
    Metadata, ILM , Security
         Data Catalog
             Data Integration
Fully Governed ( trusted)
Arbitrary/Ad-hoc  Queries
and Reporting
Big
Data
Ware
house
Data Science Workspace
Data Lake – Integrated Sandbox
Landing Area – Source Data in “Full Fidelity”
Usage Pattern Data Governance
Metadata, ILM,
   Security
Corporate Data Pyramid (CDP)

Business Value
Cloud-based Data Lake
The Future is Now: Data Lake on the Cloud
18

Analyze
Persist
DeployIngest
Data Integration
Identity Resolution
Data Quality
Discovery / Exploration
Machine Learning
Models Development
Reports / Dashboards
Applications
APIs
Structured Data
Unstructured Data
SQL, NoSQL, Object Store
Find Share Collaborate
Data Engineer Data Scientist Business Analyst App Developer
Provides innovative and industry
leading technologies to be rapidly
applied to the business without
having to manage compatibility
and data complexity.
Technical Value
Provides an open framework
to reduce the number of
integration points and testing
environments to deliver
business solutions.

Cloud Market Share

Caution: Assembly Required
— Some of the most hopeful tools are brand new or in
incubation
— Enterprise big data implementations typically combine
products with custom built components
Tools
People, Processes and Business commitment are still critical!
Data Integration & Quality Data Catalog & Governance Emerging Solutions

CDO Success in Summary
• Self-service, reduce ongoing
dependency on IT
• Automate Workflows
Streamline Processes AutomationBusiness Definitions
• Identification of KPI’s
• Iterative Process – definitions
mature over time
• Tools provide user-centric
experience
• Data Discovery
• Data Profiling
• Workflows
• Data Quality
• Automated ILM
• CDO
• Data Governance Council
• Data Stewardship Team
• Business SME’s
• Data Scientists for Insights
Roles MetricsArchitecture
• Consolidated view of data
• Flexibility for future growth
• Viewable Everywhere
• Gauge overall governance of data
• Data Quality reporting
• Issue Tracking
Data Centric, Technology Enabled, Business Focused

Joe Caserta
President, Caserta Concepts
joe@casertaconcepts.com
@joe_Caserta
• Award-winning company
• Transformative Data Strategies
• Modern Data Engineering
• Advanced Architecture
• Innovation Partner
• Strategic Consulting
• Advanced Technical Design
• Build & Deploy Solutions
• BDW Meetup
• New York City
• 4,000 members
• Knowledge sharing
Data is not important, it’s what you do with it that’s important!
Thank You – Questions & (Hopefully) Answers

The Rise of the CDO in Today's Enterprise

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