Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes And their impacts for universities, Sponsored by Bob Dylan Key Business Intelligence Market Trends “There's a battle outside ragin’, It'll soon shake your windows and rattle your walls, For the times they are a-changin’…”
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Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
And their impacts for universities, Sponsored by Bob Dylan
Key Business Intelligence Market Trends
“There's a battle outside ragin’, It'll soon shake your windows and rattle your walls, For the times they are a-changin’…”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Agenda
• How data culture influences analytic results • Managing data quality issues: locally or
centrally? • Future market developments
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
A bit about me.... • Formerly, Director of Data Governance at UNSW • Advisory board member, QFire Software • 21 years Information Management & Business
Carphone Warehouse, Vodafone, Riyad Bank – Commonwealth Bank, NSW Roads & Maritime
Services, Centrelink, OATSIH, NSW Family & Community Services, CASA, AMSA, FaHCSIA, DAFF, Navy…
• Information-Management.com “Top 12 on Twitter” • Best supporting Actor, 2005 Barnet Drama Festival
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
How data culture affects analytic results, Sponsored by Thomas Edison
“The value of an idea lies in the using of it.”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Drivers for improved BI & Analytics…
Adoption of new information-processing technologies
Massive Open Online Courses (MOOCs)
Capabilities to meet unmet & changing business needs
International competition in the Education Market
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
…Universities are businesses
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
…we are at the dawn of a revolution.
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
“I object!” • “I don’t know what you’re going to do with my data once
you have it.” • “If I give you my data, you might then ask me to do some
extra work to meet your additional requirements.” • “You may not interpret the data in the same way that I do.” • “I’m an expert in this area, you’re not. The data is too
complex for you to understand.” • “It’s too difficult to get the data out of the system and I’d
need help from I.T.” • “I don’t have the budget to pay for your requirements.” • “I’d like to help but I’m just far too busy.” • “I know there are flaws in the data, but it’s good enough
for my needs. You might criticize me for the errors.” • “Management may ask additional questions and hold me
to account for the work I’m doing”.
“I’m not interested in preserving the status quo; I want to overthrow it.”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Information as a Service: “True Facts” Identify measurable and targeted Business Outcomes
Why do we need information? For whom? What will we do differently?
Establish DG Operating Model
Who is accountable? By what processes?
Execute Activities & Tasks
How do we deliver? Who does the work?
Confirm the Information Holdings & Gaps
What do we need to provide? (Content + Context)
Implement DG/IMCC Services Catalogue:
What core capabilities do we need? “When it is obvious that the goals cannot be reached, don't adjust the goals, adjust the action steps.”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Summary: outcomes of change of culture
• Stimulus to improve data quality • Consistency of data definitions • Openness and trust • Transparency & accountability • Opportunity value • Proactive publication and Open
Data vs. “Need to know” “Publish and be damned!”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Centralised or local Data Quality management? Sponsored by Henry Ford
“Quality means doing it right when no-one is looking.”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Some university examples (not UNSW!)
• Sample of problems found with student registration data include:
– Students more than 2000 years old – Students not yet born
• Course sections that took place before the college was established
• Course sections that ended before they started • Registration clerks who “make up” program, course, and
course section codes • Duplicate records, such as: -
• Students with more than one ID number. • Students registered in the same course section multiple times.
• Inappropriate application of demographic flags • Information provided by students but not recorded in
admin system
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
To centralise or not to centralise?
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Identifying Owner & Stewards
Typically, there are significantly more unconscious Owners and Stewards
All key stakeholders in the Assets driven by an
informal structure
Business pain is felt but has no means of consistent resolution
Conscious Owners and Stewards
Responsibilities blurred and lack of understanding of the relationship
and how it should work Owners are accountable for driving up
the level of consciousness
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Assigning Ownership & Stewardship: be careful!
Plan Construct,
Create, Acquire
Commission, Organise,
Store Access Use Assess Maintain Retire
• Rigorously evaluate the decision at the earliest stages of a proposal before investing in new or replacement assets.
• Manage the procurement whether it be a construction, purchase, lease or service
• Minimise the cost and risk of ownership with effective maintenance strategies and procedures.
• Manage operational costs.
• Evaluate the level of investment in assets to identify functional or physical obsolescence, financial viability, re-use opportunities and areas of unacceptable risk.
• Consult with stakeholders and plan for disposal of assets.
• Examine all options to achieve service delivery objectives and meet business requirements.
NB Risk Point: Owner of data acquisi2on process may not be the most appropriate
owner for the informa2on asset!
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Example: UNSW Approach Legal Ownership
UNSW
Data Governance Steering Committee
Data Governance Business Advisory Group
Sub-Groups per Information Domain
ManagementUNSW Director Data
Governance
Ownership
StewardshipData Steward(s)
Strategy
Operation
Data Owner
Convenes
Responsible
Chairs
Supports
Action Projects
Advisory & AssuranceAdvisory & Assurance
Advisory & AssuranceBusiness-As-Usual Processes
Process & Culture Change
Process & Culture Change
Process & Culture Change
Input Champion
Executive Team
UNSW IT Committee
Business Domain Owners Advisory Group
Data Governance Steering Committee
Business DomainsBusiness Domains
Business DomainsBusiness Domains
Business Domains Business DomainsDG Business Advisory Group
Data Owner (chair)Data Stewards
Information UsersAdvisors
Appropriate Project Managers
Investment Priorities
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Future market developments, Sponsored by Mahatma Gandhi
“The future depends on what you do today.”
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Analytics & BI > Predictive, not reactive
“The alchemists in their search for gold discovered many other things of greater value.”
• “Traditional” BI (reporting & ad-hoc analysis) is a bare-minimum foundation, not Nirvana!
• We need to be doing much more predictive & proactive analysis – Lead indicators & models – Data mining, statistical modelling – Textual analytics
• What questions do we want to answer? • What questions can we answer with the data
we’ve got? • What other data would we need? • What does data tell us we should be asking?
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
“Big Data” is a fact of life • Three, four, five, six “Vees”?! • A lot of data (Tb/day) • Streaming data (monitoring, flow-of-control and
alerting analytics) • Inference from semi-structured data (Twitter,
Facebook) • Synthesise insight from millions of pages of text • Programmatic analysis for specific scenarios (hard in
SQL) • A disruptive catalyst to put information at the top of
the organisational agenda • Not just about the data! Business scenarios are key • Beware the Vendors!
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
All of the data, all of the time • Granular, forensic history • Modern data management & analytics solutions can make “all
of the data, all of the time” a reality • The bigger challenge is that the business community is not
analytically skilled enough to navigate the data and draw meaning from it…
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Get on the Cloud
… but security, privacy considerations are heightened.
In principle, it’s just another place to store data….
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Visualisation: a picture paints a thousand words
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Don’t forget the foundations! EIM Framework: Enterprise Information Management Framework describes each aspect of an organisations information management state, provides a baseline of maturity against best practice and a framework of business transformation to your aspirational information management state. Provides linkage and balance between business,/IT, and human/technical aspects of EIM.
Information Governance
Information Security
Information Asset Mgmt
Metadata
Ownership & Stewardship
Information and IM Strategy and
Planning
Information and IM Quality Mgmt
Information Asset Classification
Intellectual Property
Reporting design AnalyticsInformation
Security Policy and Governance
Asset Management
Human Resources Security
Management
Knowledge Transfer
Data Mining
Data WarehousingBusiness Intelligence
Information IM Workforce
Management
Information and IM Risk Management
Registration
Data Modelling
Data management
Data Integration
Data Cleansing
Data Capture
Data Migration
Data De-duplication
Record Keeping
Knowledge Management
Information Asset Access and Use Management
Privacy Publishing
CopyrightPhysical and
Environmental Management
Communications and Operations Management
Information Security Incident
Management
Access Management
Information system
acquisition, development and
maintenance management
Compliance Management
Information and IM Policy, Principles and Architecture
Information and IM Governance Processes
Meta Knowledge
Search and Discovery
ExchangePricing
Licensing and Rights
Management
Assess and Accessibility
Redress Mechanisms Data Quality and Integrity
Data Conversion & Transformation
Record Management Archiving Conservation and Preservation
Record Creation and Capture
Digital Continuity
Collection Management
Retrieval and Access
Retention and Disposal
Business Continuity
Enterprise Informa4on Model IM Solu4ons and Technology IM Policies
Organisa4on and People Data Governance Informa4on Culture
IM Processes
Metadata Repository
Master Data Repositories UNSW Core Systems
Information Asset
Register
Physical Instantiations
Physical Layer
Logical Layer (Transition)
AnalyticalDB Models
Cubes
Conceptual Layer (Business)
Physical MessagesFormats
DWHDB
HRDB
Student Admin etc...
OperationalDB Models
Reference models
Data Subject AreasData Entities
Data Attributes
Information Concepts
Business Content Business Rules Data
Business Data Element
Domain Values
Endorsed Standards for Content
Business Constraints
Business Measures
Master data models
Classification Entity
Hierarchies
Mappings
Business Rules Definitions
Business Constraints
Business Measures
Core SystemsMDM
Metadata M
anagement Process
Information M
odel Managem
ent Process
Information Alliances: Data O
wnership & Stewardship Process
MDM Processes
Related Data Governance Processes
Application Logical Data
ModelsLogical
MessageSchemas
MDM Data Model
Systems Data Models
SOA/EP MessagesG/L
Application Logical Data
ModelsLogical
MessageSchemas
AnalyticalDB Models
Cubes
Physical MessagesFormats
OperationalDB Models
Business Glossary
Conceptual Model: Groupings & Relationships
Data Elements, Definitions, Aliases, and Security
Data Domains
Enterprise Information Model
Alan D. Duncan http://nformationaction.blogspot.com Tw: @Alan_D_Duncan Information Strategy | Data Governance | Analytics | Better Business Outcomes
Summary: Supporting Information Use Cases • Based on our current understanding of business needs, the following classes of
Information Use Case are identified • Detailed Requirements Analysis should be conducted on a project-by-project basis
to explore any detailed Use Cases within each class • Not all detailed Use Cases need to be defined ahead of time • Solutions should be flexible to accommodate new and changing Use Cases
Structured data
repor2ng
Strategic Intelligence and Data Mining
Publish content to a community
Execu2ve briefings
Educa2on, Training, Learning
Search for content previously created
Records Management, Compliance &
Audit
GIPA & Privacy
Responses
Ability to publish Filtering/screening/valida4on of what gets published