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Business Intelligence for the Chief Data Officer
Don Soulsby
Sandhill Consultants
Aug 20, 2014
DAMA - CHICAGO
Who we are:
Sandhill Consultants • Sandhill is a global
company servicing the data, process modeling community in its varied needs. – Educators & Architects – Standards Framework – Onsite & Web Based-
Training – Services – Reference Material, Guides – Technical Support
Don Soulsby • Enterprise Architect Practice
Leader • Data/Process modeler • Information Management
Product Manager • EA, DW, BI, Metadata
Consultant • Industry Speaker
2
The New Cx Executives
CDO – Chief Data Officer
Organizations, Processes Come and Go, Data Persists
CDO
• A chief data officer (CDO) is a corporate officer responsible for enterprise-wide governance and utilisation of information as an asset, via data processing, analysis, data mining information trading and other means.
• The Chief Data Officer has a significant measure of business responsibility for determining what kinds of information the enterprise will choose to capture, retain and exploit and for what purposes
This is your world
2013 CDO facts
5 Facts About Chief Data Officers, by Mark Raskino Member of the Gartner Blog Network, November 6, 2013
CDO Fact #1 There are over 100 chief data officers (carrying that actual job title) – serving in large enterprises today. That’s more than double the number we counted in 2012.
CDO Fact #2 Banking, Government and Insurance are the top 3 industries for Chief Data Officers – in that order. However we are now seeing other industries rising.
CDO Fact #3 65% of Chief Data Officers are in the United States. 20%
are in the UK. There are now CDOs in over a dozen countries.
CDO Fact #4 Over 25% Of all Chief Data Officers are in New York or DC. It’s a regulatory catalyzed trend – at least in the early stages.
CDO Fact #5 Over 25% of Chief Data Officers are women. In case you are wondering - that’s almost twice as high as for CIOs (13%)
Data Governance
• ‘The act or process of directing, leading and assuring that information is managed effectively as an enterprise resource, including resolving information conflicts, across the enterprise.’
Larry English
Trust and Traceability
Compliance
ALL DATA, Great and Small
Do Executives Trust Data or Intuition in Decision-Making?
By Bob ViolinoJUN 9, 2014 3:44pm ET
“Doveryay, No Proveryay”, “Trust yes, but verify."
TRUST
Firm reliance on the integrity, ability, or character of a person
or thing
Custody; care.
Something committed into the care of another; charge.
TRUST in IT context
• Gatekeeping o eTrust, Security,
Intrusion detection
• Stewardship o “Ownership” vs
Information Resource Meaning/Quality
• Governance o Information
Accountability http://blogs.gartner.com/doug-laney/batman-on-big-data/
Building TRUST through Food Assurance
“ Public confidence has been shaken in recent times by food scares and associated media sensationalism. In particular this is made us, as both consumers and participants in supply chain, uncertain of ‘who’ or ‘how’ to have trust in the food chain. “
- R.N.Baines & W.P.Davies
Royal Agricultural College
Cirencester, Glousteshire, UK
THIS FISH
FROM
FIN
TO
FORK
Many to Many Problem
Many Sources Many Uses
Many to Many Solution
Many Sources Many Uses
Enterprise Data
Warehouse
Data Management Maturity Model
METADATA
OVERSIGHT
Information Flow
$$
$$
Business Information
IT Information
META
DATA
Information Delivery
Data Mart
Analysis Cube
Business Intelligence
Unstructured
Applications
ERP Data
Data Warehouse
ETL BI Analytics
Unstructured
Applications
ERP Data
Data Modeling
Metadata Repository
DMM – Categories, Components
Data Management
Strategy
Data Management
Strategy
Communications
Data Management
Function
Business Case
Funding
Data
Governance
Governance Management
Business Glossary
Metadata Management
Data
Quality
DQ Strategy
Data Profiling
DQ Assessment
Data Cleansing
Data
Operations
Data Requirements
Definition
Data Lifecycle Management
Provider Management
Platform & Architecture
Architectural Approach
Architectural Standards
Data Management
Platform
Data Integration
Historical Data, Archiving
Metadata - Information
UNDERSTANDIBILITY
• Synonyms, Homonyms, Artifacts
BI for IT
Data Collection Data Delivery
Metadata Repository
Metadata Maturity Model
Level 1
• Performed
Level 2
• Managed
Level 3
• Defined
Level 4
• Measured
Level 5
• Optimized
• metadata documentation is developed, stored and accessible.
• metadata management process defined
• capture data interdependencies.
• impact analysis on potential data changes
• metadata categories, properties, and standards
• metadata management strategy
• phased implementation plan
• centralizes metadata management efforts
• data governance approves change
• measures and, metrics
• architecture validation
• root cause analysis
• performance prediction models
• improvement objectives
• planned data changes continuous improvement
• integrated meta-model
• uniform data types and data definitions
• metadata repository exchange data standards
• historical measurement of objectives
• quantitative objectives
• statistical analysis of processes
Metadata Management
• PURPOSE
Establish the processes and infrastructure for specifying and extending clear and organized information about the data assets under management, fostering and supporting data sharing, ensuring compliant use of data, improving responsiveness to business changes, and reducing data related risks.
Introduction
Effective metadata management, and build out of the organization’s metadata catalogue facilitates, supports and contributes to achievement of critical data management activities and objectives, such as:
• Data architecture • Data requirements • Data lineage • Data integration • Data provenance • Data standards
Model Driven Change Management
Business Domain
Technology Domain
Logical Data Model
Middle Out
Human
Oriented
Computer
Oriented
Reverse
Engineering Physical Data Model
Forward
Engineering
Conceptual Data Model
TAXONOMY
DATABASE
Model Management
Not Just Data
Business Dynamics Model
System Dynamics Model
Function Dynamics Model
Application Database Change
PROCESS
Conceptual Data Model
TO BE
Logical Data Model – TO BE
Data Delivery Model
Business Change
DATA
Logical Data Model – AS IS
Reverse Engineered
Physical Model
Conceptual Data Mode
AS IS (?)
• Graphical data linage across multiple models
• Design Layers
• Data Movement
• Domains
Data Lineage
Reporting & Publishing
Asset Management
Management of an organization's assets, both physical assets, called "tangible", and non-physical, "intangible" assets.
• Physical asset management • Infrastructure asset management • Fixed assets management • IT asset management • Digital asset management
Managing Data as an Asset
• Asset Lifecycle o Planning
o Procurement
o Deployment
o Management & Maintenance
o Disposition
• Asset Valuation o Capital Cost
o Expense
o Depreciation
o Salvage Value
The Rise of Management by the Numbers
While glancing out the window…
Return on Assets = Net Income
Total Assets
Inventory Turnover = Cost of Sales
Avg. Inventory
Measurement
Enterprise Modelling Set of Standards
"You can't manage, what you can't measure.
Measure = Observation Standard
Development &
Operations
How Does EM-SOS! Work
Glossaries
Corporate Policies
EM-SOS!
Design
Standards
Design Processes Forms & Reports
Business Requirements
Design
Templates
Conceptual
Logical
Physical
Models
Databases
Apps
Reusable Object Repository
Data
Management
Life Cycle &
Procedures
Metrics & Measurement
Social Media - Metadata
Study exposes social media sites that delete photographs’ metadata.
http://www.embeddedmetadata.org/social-media-test-results.php
[shuǐtóu] [bù] [qīngshuǐ] [wěi] [hún]
Thank You!
“ If upstream is dirty,
downstream will be muddy”
Donald J. Soulsby Enterprise Architecture Practice Leader
Sandhill Consultants [email protected]
How Sandhill Can Help
People
Place
Product
Process
Tools & Technologies Sandhill Training
Standards & Best Practices Sandhill EMSOStm
Security Architecture
Application Architecture
Enterprise Modeling
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