DMBoK 2
& other frameworks
DAMA Australia November 2013
CHRISTOPHER BRADLEY (DAMA CDMP FELLOW)
P / 1
@InfoRacer
+44 7973 184475 (mobile)
+44 1225 923000 (office)
Chris.Bradley@DMAdvisors.co.uk
Information Management, Life & Petrol
http://infomanagementlifeandpetrol.blogspot.com
uk.linkedin.com/in/christophermichaelbradley/
Christopher Bradley
I N F O R M AT I O N M A N A G E M E N T S T R AT E G I S T
P / 2
Christopher Bradley
Chris has 36 years of Information Management experience &
is a leading Independent Information Management strategy
advisor.
He is an author & examiner for CDMP, a Fellow of the
Chartered Institute of Management Consulting (now IC) a
member of the MPO, and SME Director of the DM Board.
In the Information Management field, Chris works with
prominent organizations including Alba Leasing, HSBC,
Celgene, GSK, Pfizer, Icon, Quintiles, Total, Barclays, ANZ, GSK,
Shell, BP, Statoil, Riyad Bank & Aramco. He addresses
challenges faced by large organisations in the areas of Data
Governance, Master Data Management, Information
Management Strategy, Data Quality, Metadata Management
and Business Intelligence.
A recognised thought-leader in Information Management
Chris is the author of numerous papers, books, including
sections of DMBoK 2.0, a columnist, a frequent contributor
to industry publications and member of several IM
standards authorities.
He is President of DAMA UK, DAMA- I DMBOK 2 author.
In April 2016 he became the inaugural CDMP Fellow, and
received the DAMA lifetime professional
achievement award.
He leads an experts channel on the influential
BeyeNETWORK, is a sought after speaker at major
international conferences, and is the co-author of “Data
Modelling For The Business – A Handbook for aligning
the business with IT using high-level data models”. He
also blogs frequently on Information Management (and
motorsport).
P / 3
P / 4
Recent Presentations
MDM DG Europe: May 2016 London; “Data Governance by Stealth”
Webinar: May 2016; “Data Modelling is not JUST for DBMS design”
Enterprise Data World: April 2016 San Diego; “DAMA CDMP Workshop”
DAMA Webinar: April 2016; “Data Integration & Interoperability” Disciplines of the DAMA
DMBoK”
DAMA Webinar: March 2016; “Document & Content Management” Disciplines of the DAMA
DMBoK”
DAMA Webinar: February 2016; “Data Operations Management” Disciplines of the DAMA
DMBoK”
Oil & Gas Data Management Conference: February 2016, London; “Developing An Information
Strategy To Align With In-Flight Business Programs”
DAMA Webinar: January 2016; “Data Governance” Disciplines of the DAMA DMBoK”
DAMA Webinar: December 2015; “Information Lifecycle Management” Disciplines of the DAMA
DMBoK”
DAMA Webinar: November 2015; “MetaData Management” Disciplines of the DAMA DMBoK”
Enterprise Data & BI Europe (IRM): November 2015, London; “Is the Data Asset really different?”
& “CDMP Examination Preparation” & “Data Management Room 101”
DAMA Webinar: October 2015; “Data Risk & Security” Disciplines of the DAMA DMBoK”
DAMA Webinar: September 2015; “Data Warehousing & Business Intelligence” Disciplines of the
DAMA DMBoK”
DAMA Webinar: August 2015; “Data Quality Management” Disciplines of the DAMA DMBoK”
BCS & DAMA Seminar: June 2015; “Is the Data Asset really different?”
DAMA Webinar: June 2015; “Data Modelling” Disciplines of the DAMA DMBoK”
PRISME Pharmaceutical Congress: May 2015, Basel, CH; “Building & exploiting a Pharmaceutical
Industry consensus data model”
MDM DG Europe (IRM): May 2015, London; “CDMP Examination Preparation” & “Data Governance By
Stealth?, Can you ‘sell’ Data Governance if the stakeholders don’t get it?”
DAMA Webinar: April 2015; “Master & Reference Data Management” Disciplines of the DMBoK”
Enterprise Data World: April 2015, Washington DC USA; “Data Modelling For The Business” and
“Evaluating Information Management Tools”
DAMA Webinar: February 2015; “An Introduction to the Information Disciplines of the DMBoK”
Dataversity Webinar: February 2015; “How to successfully introduce Master & Reference data
management”
Petroleum Information Management Summit 2015: February 2015, Berlin DE,
“How to succeed with MDM and Data Governance”
Riyadh Information Exchange: May 2013, Riyadh, Saudi Arabia; “Big Data – What’s the big fuss?”
Enterprise Data World: (Wilshire Conferences), May 2013, San Diego, USA, “Data and Process Blueprinting – A
practical approach for rapidly optimising Information Assets”
Data Governance & MDM Europe: (IRM Conferences), April 2013, London, “Selecting the Optimum Business
approach for MDM success…. Case study with Statoil”
E&P Information Management: (SMI Conference), February 2013, London,
“Case Study, Using Data Virtualisation for Real Time BI & Analytics”
E&P Data Governance: (DMBoard / DG Events), January 2013, Marrakech, Morocco, “Establishing a successful
Data Governance program”
Big Data 2: (Whitehall), December 2012, London, “The Pillars of successful knowledge management”
Financial Information Management Association (FIMA): (WBR), November 2012, London; “Data Strategy as a
Business Enabler”
Data Modeling Zone: (Technics), November 2012, Baltimore USA; “Data Modelling for the business”
Data Management & Information Quality Europe: (IRM), November 2012, London; “All you need to know to
prepare for DAMA CDMP professional certification”
ECIM Exploration & Production: September 2012, Haugesund, Norway:
“Enhancing communication through the use of industry standard models; case study in E&P using WITSML”
Preparing the Business for MDM success: Threadneedles Executive breakfast briefing series, July 2012, London
Big Data – What’s the big fuss?: (Whitehall), Big Data & Analytics, June 2012, London,
Enterprise Data World International: (DAMA / Wilshire), May 2012, Atlanta GA,
“A Model Driven Data Governance Framework For MDM - Statoil Case Study”
“When Two Worlds Collide – Data and Process Architecture Synergies” (rated best workshop in conference);
“Petrochemical Information Management utilising PPDM in an Enterprise Information Architecture”
Data Governance & MDM Europe: (DAMA / IRM), April 2012, London,
“A Model Driven Data Governance Framework For MDM - Statoil Case Study”
AAPG Exploration & Production Data Management: April 2012, Dead Sea Jordan; “A Process For Introducing
Data Governance into Large Enterprises”
PWC & Iron Mountain Corporate Information Management: March 2012, Madrid; “Information Management &
Regulatory Compliance”
DAMA Scandinavia: March 2012, Stockholm,
“Reducing Complexity in Information Management” (rated best presentation in conference)
Ovum IT Governance & Planning: March 2012, London; “Data Governance – An Essential Part of IT
Governance”
American Express Global Technology Conference: November 2011, UK,
“All An Enterprise Architect Needs To Know About Information Management”
FIMA Europe (Financial Information Management):, November 2011, London; “Confronting The Complexities
Of Financial Regulation With A Customer Centric Approach; Applying a Master Data Management And Data
Governance Process In Clydesdale Bank “
Data Management & Information Quality Europe: (DAMA / IRM), November 2011, London, “Assessing &
Improving Information Management Effectiveness – Cambridge University Press Case Study”; “Too Good To Be
True? – The Truth About Open Source BI”
ECIM Exploration & Production: September 12th 14th 2011, Haugesund, Norway: “The Role Of Data
Virtualisation In Your EIM Strategy”
Enterprise Data & Business Intelligence 2014: (IRM), November 2014, London, UK “Data Modelling 101”
Enterprise Data World International: (DAMA / Wilshire), April 2011, Chicago IL; “How Do You Want Yours
Served? – The Role Of Data Virtualisation And Open Source BI”
Enterprise Data World: (DataVersity), May 2014, Austin, Texas, “MDM Architectures & How to identify the right Subject
Area & tooling for your MDM strategy”
Data Governance & MDM Europe: (DAMA / IRM), March 2011, London; “Clinical Information Data
Governance”
E&P Information Management Dubai: (DMBoard),17-19 March 2014, Dubai, UAE “Master Data Management
Fundamentals, Architectures & Identify the starting Data Subject Areas”
Data Management & Information Management Europe: (DAMA / IRM), November 2010, London,
“How Do You Get A Business Person To Read A Data Model?
DAMA Australia: (DAMA-A),18-21 November 2013, Melbourne, Australia “DAMA DMBoK 2.0”, “Information
Management Fundamentals” 1 day workshop”
DAMA Scandinavia: October 26th-27th 2010, Stockholm, “Incorporating ERP Systems Into Your Overall Models
& Information Architecture” (rated best presentation in conference)
Data Management & Information Quality Europe: (IRM Conferences), 4-6 November 2013, London, UK; “Data
Modelling Fundamentals” ½ day workshop: “Myths, Fairy Tales & The Single View” Seminar; “Imaginative
Innovation - A Look to the Future” DAMA Panel Discussion
BPM Europe: (IRM), September 27th – 29th 2010, London; “Learning to Love BPMN 2.0”
Information Management in Pharmaceuticals: September 15th 2010, London,
“Clinical Information Management – Are We The Cobblers Children?”
Recent Publications
“Data Modelling For The Business – A Handbook for aligning the business with IT using high-level data models”; Technics
Publishing;
ISBN 978-0-9771400-7-7; http://www.amazon.com/Data-Modeling-Business-Handbook-High-Level
Book:
Book:
“DAMA Data Management Body Of Knowledge 2.0” ; Technics Publishing;
Article:
Back to the future for Data management? September 2015
Article:
Is the “Data Asset” really different? July 2015
Article:
A visit to the vet & a BA flight reminded me about Data Governance; June 2015
White Paper:
“Information is at the heart of ALL Architecture disciplines”,; March 2014
White Paper:
“Are you ready for Big Data ?”, November 2013
Article:
The Bookbinder, the Librarian & a Data Governance story ; July 2013
Article:
Data Governance is about Hearts and Minds, not Technology January 2013
White Paper:
“The fundamentals of Information Management”, January 2013
White Paper:
“Knowledge Management – From justification to delivery”, December 2012
Article:
“Chief INFORMATION Officer? Not really” Article, November 2012
White Paper:
“Running a successful Knowledge Management Practice” November 2012
White Paper:
“Big Data Projects are not one man shows” June 2012
Article:
ISBN TBD
“IPL & Statoil’s innovative approach to Master Data Management in Statoil”, Oil IT Journal, May 2012
White Paper:
“Data Modelling is NOT just for DBMS’s” April 2012
Article:
“Data Governance in the Financial Services Sector” FSTech Magazine, April 2012
Article:
“Data Governance, an essential component of IT Governance" March 2012
Article:
“Leveraging a Model Driven approach to Master Data Management in Statoil”, Oil IT Journal, February 2012
Article:
“How Data Virtualization Helps Data Integration Strategies” BeyeNETWORK (December 2011)
Article:
“Approaches & Selection Criteria For organizations approaching data integration programmes” TechTarget (November 2011)
Article:
Big Data – Same Problems? BeyeNETWORK and TechTarget. (July 2011)
Article
“10 easy steps to evaluate Data Modelling tools” Information Management, (March 2010)
Article
“How Do You Want Your Data Served?” Conspectus Magazine (February 2010)
Article
“How do you want yours served (data that is)” (BeyeNETWORK January 2010)
Article
“Seven deadly sins of data modelling” (BeyeNETWORK October 2009)
Article
“Data Modelling is NOT just for DBMS’s” Part 1 BeyeNETWORK July 2009 and Part 2 BeyeNETWORK August 2009
Web Channel:
Article:
BeyeNETWORK “Chris Bradley Expert Channel” Information Asset Management
http://www.b-eye-network.co.uk/channels/1554/
“Preventing a Data Disaster” February 2009, Database Marketing Magazine
P / 6
Training, Mentoring, and Executive Workshops
We offer a number of training courses for practitioners and management, and custom-built, training & awareness
seminars can also be delivered.
The following training courses are available:
•
•
•
•
•
•
•
Information Management Fundamentals – 4 (or 5) day introductory course covering all of the components of Information
Management as defined in the DAMA Body of Knowledge (DMBoK) & the forthcoming changes in DMBoK 2.0
Data Modelling Fundamentals – 3 day intermediate course introducing students to data modelling, its purpose, the different types
of models and how to construct and read a data model.
Advanced Data Modeling – 3 day advanced course for students with data modelling experience to understand the human centric
aspects of data modelling to enable them to build quality models that meet business needs.
IM Fundamentals & Practitioner Courses – A series of 1 day (foundation) and 2 day (practitioner) classes to give practitioners a solid
background in a specific Information Management topics. The 2 day practitioner workshops explore more detail on the
implementation aspects of the particular Information Management discipline
•
Data Modelling Foundation (1 day only)
•
Data Governance Foundation & Practitioner
•
Master & Reference Data Foundation & Practitioner
•
Data Quality Management Foundation & Practitioner
•
Data Warehouse & Business Intelligence Foundation & Practitioner
•
Data Integration Foundation & Practitioner
Executive Workshops – ½ and 1 day executive workshop(s) designed to give non-technical managers a basic understanding of a
various Information Management topics and their importance to the organisation.
CDMP Certification – 3 day workshop “exam cram” designed to help attendees pass the DAMA CDMP certification. Sitting the live
examinations is included as part of the workshop.
Integrated Business Process, Data & Requirements Definition – 5 day intensive class to show students an integrated
requirements discovery and definition approach covering business process, different types of requirements modelling, and the critical
role of the conceptual data model.
P / 7
Data Management Training
P / 8
Multiple Levels of Training for Various Audiences
Level
Introductory
Information
Management
Foundation
(1 day)
Advanced / Deep Dive
Intermediate
Information Management Fundamentals
(4 or 5 days)
DAMA-I CDMP
Exam Cram &
Certification
(3 days)
Information
Management For
The Business
(½ and 1 day)
The “client Way” Information Management Mentoring
Data Modelling
Foundation
(1 day)
Data Modelling Fundamentals
(3 days)
Advanced Data Modelling
(3 days)
Integrated Business Process, Data Requirements and
Discovery
(5 days)
Data Integration Implementation &
Practice (1 and 2 day)
Reference & Master Data Management
Implementation & Practice (1 and 2
day)
Data Governance Implementation &
Practice (1 and 2 day)
Data Quality Management
Implementation & Practice (1 and 2
day)
Data Warehouse & Business Intelligence
Implementation & Practice (1 and 2
day)
Information Management Fundamentals
Course Description:
A 4 (or 5)
day
course
covering
all
the
disciplines
of
Information
Management
as
defined
in
the
DAMA body of knowledge (DMBoK).
Taught by DAMA DMBoK(2.0) author
&
CDMP(Fellow)
this
provides
a
solid
foundation
across
the
complete Information Management
sCourse
p e c t Content:
rum.
Course Objectives:
To give participants
a solid grounding in all of the core
Information Management concepts.
Additionally it provides a foundation
for students considering DAMA CDMP
professional certification
Introduction to the DMBoK:
What is the DMBoK, its intended purpose and audience of the DMBoK.
Changes due
of the DMBoK with other frameworks (TOGAF / COBIT etc.). DAMA CDMP professional certification overview & CDMP exam coverage by DMBoK section.
in
DMBoK
2.0,
relationship
Data Governance: Why Data Governance is at the heart of successful IM. A typical DG reference model. DG roles & responsibilities, the role of the DGO & its relationship with the PMO.
How to get started with Data Governance.
Data Quality Management: The Dimensions of Data Quality, policies, procedures, metrics, technology and resources for ensuring Data Quality is measured and ultimately continually
improved. DQ reference model. Capabilities & functionality of tools to support Data Quality management.
Master & Reference Data Management: Differences between Reference & Master Data. Identification and management of Master Data across the enterprise. 4 generic MDM
architectures & their suitability in different cases. MDM maturity assessment to consider business procedures for MDM and the provision and appropriateness of MDM solutions per major
data subject area. How to incrementally implement MDM to align with business priorities.
Data Warehousing & BI Management: Provision of Business Intelligence (BI) to the enterprise and the manner in which data consumed by BI solutions and the resulting reports are
managed. Particularly important if the data is replicated into a Data Warehouse. Types of BI, DW and Analytics.
Data Modelling & Metadata Management: Provision of metadata repositories and the means of providing business user access and glossaries from these. The development, use and
exploitation of data models, ranging from Enterprise, through Conceptual to Logical, Physical and Dimensional. Maturity assessment to consider the way in which models are utilized in the
enterprise and their integration in the Software Development Life Cycle (SDLC).
Data Architecture Management: Approaches, plans, considerations and guidelines for provision of Data Integration and access. Consideration of P2P, ETL, CDC, Hub & Spoke, Serviceorientated Architecture (SOA), Data Virtualization and assessment of their suitability for the particular use cases.
Data Lifecycle Management: Proactive planning for the management of Data across its entire lifecycle from inception through, acquisition, provisioning, exploitation eventually to
destruction. This IM discipline and its maturity assessment determine how well this is planned for and accomplished.
Data Security & Privacy: Identification of threats and the adoption of defences to prevent unauthorized access, use or loss of data and particularly abuse of personal data. Exploration of
threat categories, defence mechanisms & approaches, and implications of security & privacy breaches.
Regulatory Compliance: The polices and assurance processes that the enterprise is required to meet. Adapting to the changing legal and regulatory requirements related to information
and data. Assessing the approach to regulatory compliance & understanding the sanctions of non-compliance.
Data Risk Management: Identification of risks (not just security) to data and its use, together with risk mitigation, controls and reporting.
Data Management Tools & Repository: Examination of the categories of tools supporting the IM disciplines. How to select the appropriate toolset. Discussion of an example policy for
use of specific technology to ensure consistency and interoperability across the enterprise.
Data Integration & Interoperability: A new discipline introduced into DMBoK 2.0. DI&I covers addresses the different types of Data Integration approaches ranging from P2p through
ETL to DV and EAI. The applicability of the different approaches, issues and implications of each will be discussed together with an outline of the technologies that support these styles of
integration.
P / 10
Data Modelling Fundamentals
Course
Course
Objectives:
Explain the
fundamental data modelling building
blocks.
Understand
the
differences
between relational and dimensional
models.
Describe the purpose of
Enterprise, Conceptual, Logical, and
Physical
data
models
Create
a
Conceptual
and
a
Logical
Data
model.
Understand
different
approaches for fact finding & how to
apply normalisation techniques.
Description:
A 3 day
intermediate
course
introducing
students
to
data
modelling,
its
purpose,
the
different
types
of
models, how to construct and read
a data model, and the wider use of
data models.
Course Content:
• What is Data Modeling and why does it matter? What is the
relationship between a data model and other types of models?
• What is a Conceptual Data model, why it’s important and the
pivotal role it plays in all architecture disciplines;
• The major differences between Enterprise, Conceptual, Logical,
Physical and Dimensional data models
• How to use high-level data models to communicate with business
people to get the core information you require to build robust
applications.
• What core information is needed to create a data model, how this
can be easily communicated to business people, and what visual
constructs to use to get their attention?
• Templates and guidelines for a step-by-step approach to
implementing a high-level data model in your organization
• Data vs MetaData; what’s the difference and why does it matter
• Approaches for creating a data model (Top Down, Bottom Up,
Middle out) and when to use them.
•
•
•
•
•
•
•
•
•
•
•
•
Data Modelling Basics; Entities, Attributes, Relationships Keys
How to identify Entities and Subtypes
Basic standards
Relationships: Cardinality, Optionality, Identifying,, Nonidentifying, recursive, and many-to-many
Rules for handling Super types, subtypes, many to many and
recursive relationships
Keys: Primary, Natural, Surrogate, Alternate, Inverted, Foreign
Attribute properties & attribute domains
Data Modelling Notations and tooling
Normalisation: 1st, 2nd and 3rd normal form and a brief overview
of other normal forms
A checklist for Data Model quality
Layout, presenting, and communication a data model to non
modellers
Why data modelling is NOT just for RDBMS’s (its relevance to Packages,
SOA, XML, Business Communication, Data Lineage and BI)
P / 11
Advanced Data Modelling
Course
Description:
A
3 day
advanced course for students with
data
modelling
experience
to
explore the human centric aspects
of conceptual data modelling, use
of patterns and other advanced
topics to enable them to build
quality
data
models
that
meet
business needs.
Course Content:
• Data modeling recap:
Modeling basics, major constructs,
identifying entities, model levels and linkage between them.
• Understanding the purpose of the model: Why is this being
created & what are we trying to accomplish with a model?
• Top down requirements capture: When is it appropriate, what are
the limitations.
• Bottom up requirements synthesis: When this works, where is it
appropriate. How do we cope with existing DBMS’s and systems.
• Middle out: Is this always the best approach for requirements?
• Interviews, Questionnaires, Workshops: How to select the fact
fining approach and when the are and are not appropriate.
• Why Information Architects need to understand Business
Processes since information is acted on by the processes.
• How to capture requirements for both Data and Process needs.
• Creating a Conceptual data model and Conceptual process
model.
• Improving communication between modellers and business
stakeholders, & how to use high-level data models to aid
communication (and when not to).
Course Objectives:
Understand and practice
different
requirements
gathering
approaches. Recognise the relationship
between process and data models and
practice capturing requirements for both.
Learn how and when to exploit standard
constructs
and
reference
models.
Understand
further
dimensional
data
modelling approaches and normalisation
techniques.
• Presenting data models to business users and how to conduct
feedback sessions. A data model quality checklist
• Checking the Data vs the MetaData; why does it matter?
• Use of standard data model constructs, and pattern models:
• Understanding the Bill of materials (BOM) construct. Where can it
be applied, why it’s one of the most powerful modelling
constructs.
• Party; Role; Relationship: Why mastering this construct can
provide phenomenal flexibility.
• Mastering Hierarchies:
Different approaches for modelling
hierarchies.
• Dimensional data modelling: Beyond the basics with conformed
dimensions, bridges, junk dimensions & factless facts.
• Data Modelling Notations and tooling
• Normalisation: Progressing beyond 3NF. 4NF, 5NF Boyce-Codd,
and why, and when to use them.
• Data modelling is NOT just for RDBMS’s: Case studies on other
uses.
P / 12
Data Modelling Foundation
Course Description: Part of the Information Management “Foundation” series: A 1
day foundation class in Data Modelling to give practitioners an overview of Data Modelling,
one of the most crucial of the Information Management disciplines.
Data Modeling Foundation (1 day):
• Overview of Data Modeling: What is Data Modelling, Why is Important, What areas are
impacted and influenced by Data models, what are the benefits and uses of data models.
• Levels and purposes of data models. What are the different types and why (and when) are they
appropriate.
• Data modelling basics, entities, attributes & relationships. The major constructs in data models.
• Identifying entities, model levels and linkage between them.
• Understanding the purpose of the model: Why is this being created & what are we trying to
accomplish with a model?
• Different approaches to capturing requirements for creation of data models.
• Why Information Architects need to understand Business Processes since information is acted
on by the processes.
• Creating a Conceptual data model.
• How to use high-level data models to communicate with business people.
• Why Data modeling is NOT just for RDBMS’s: How data models are important for Package
selection & implementation, DW/BI, Data Integration, SOA and Communication with the
business.
• Case studies on different uses of Data Models.
P / 13
Data Governance Foundation & Practitioner
Course Description: Part of the Information Management “Foundation” and ”Practitioner” series: The
class covering the need for Data Governance, its outcome, typical organization structures for Data
Governance, the roles responsibilities and activities involved in establishing successful Data Governance, and
metrics for measuring progress of a Data Governance initiative. The 2 day class explores a Framework for and
how to get started with Data Governance.
Data Governance Foundation
(1 day) & Practitioner (2 day):
• Introduction to Data Governance: What is Data Governance & why it matters.
• The relationship between Data Governance & the other Information disciplines
• Data Governance & IT Governance; is there a difference and why it matters.
• A pragmatic workable framework for Data Governance
• How to make the case for Data Governance and the issues faced when Data Governance is not
present.
• Starting a Data Governance Program: Establishing Data Governance, program establishment
and set up, developing the business case & foundation activities.
• The typical roles, responsibilities, organization structures and principles for successful Data
Governance.
• Keeping it going: Now its started; how do you sustain Data Governance.
Governance into Business As Usual activities and making it real
Baking Data
• The role of the Data Governance Office
• Data Governance metrics and their relationship with Data Quality
P / 14
Master & Reference Data Management Foundation &
Practitioner
Course Description: Part of the Information Management “Foundation” and “Practitioner” series: A 1 day
foundation class or 2 day practitioner class covering the different MDM architectures, genres, applications and
activities involved in running a successful Master Data Management initiative. The 2 day class explores how to
get started with Reference & MDM and outlines a successful framework for achieving MDM success.
Master & Reference Data Management Foundation
(1 day)
& Practitioner (2 day):
• What is Master Data Management, what is the difference between Master and Reference Data
and why it matters.
• What are the different types of MDM Architectures. These vary from a full central hub, through
hybrid to virtualised with many flavours and variants along the way.
• The applicability of different MDM architectural styles to differing business problems and why
identifying the correct architecture for your type and usage of Master Data is crucial.
• An Reference Architecture Model for Master & Reference Data Management and exploration of the
typical components and functions in the Reference Architecture.
• How to identify & select the right tooling for your environment and Master Data business needs.
• More MDM architecture considerations: Single domain and Multi domain MDM solutions, the advantages & disadvantages of each
and how to determine what's most appropriate for you.
• Implementation styles: Operational & Analytical MDM. The issues and implications associated with the different approaches and
why getting this right impacts future MDM success.
• How to build the case for a Master Data initiative.
• A proven approach for identifying the Data Subject Areas aligned to Business initiatives to start on your MDM program.
• How to create an incremental MDM implementation plan that wont break the bank.
P / 15
Data Quality Foundation & Practitioner
Course Description: Part of the Information Management “Foundation” and “Practitioner”
series: A 1 day foundation class or 2 day practitioner class covering the principles, processes and
activities involved in creating a Data Quality function. The 2 day class explores further detail on
how to get started with Data Quality & outlines 7 steps for achieving Data Quality success.
Data Quality Foundation
(1 day) & Practitioner (2 day):
• Examples of Data Quality issues and their implications: How could these have been avoided?
• What is Data Quality vs Data Quality Management and why does it matter?
• The DAMA Dimensions of Data Quality, plus alternative views on Data Quality Dimensions.
• The relationship between DQ Dimensions, DQ Measures & Metrics and their applicability.
• The benefits and impact of Data Quality.
• A workable framework for establishing Data Quality in your organization.
• The role and applicability of tools to support a Data Quality initiative.
• A reference architecture model for Data Quality tools, common functions & capabilities, differences, what to look out
for & a framework for selecting DQ tooling.
• Types & applicability of Data Quality Reporting
• The relationship between Data Quality and Data Governance & the other Information disciplines
• Data Quality metrics & their relationship with Data Governance.
• Starting and sustaining a Data Quality initiative: 7 steps for achieving Data Quality success, the activities & structures
required, & foundation activities
• The typical roles, responsibilities, organization structures and principles for successful Data Quality.
• Now its started; how do you sustain Data Quality. Baking DQ into Business As Usual activities and making it real
P / 16
Data Warehousing & Business Intelligence Foundation &
Practitioner
Course Description: Part of the Information Management “Foundation” and “Practitioner”
series: A 1 day foundation class or 2 day practitioner class covering the architectures,
technologies, applicability and activities surrounding Data Warehousing & Business Intelligence
(DW&BI). The 2 day class explores further detail on Dimensional Data Modelling together with
different Data Visualization and DW&BI architectural approaches.
Data Warehousing & Business Intelligence Foundation
& Practitioner (2 day):
(1 day)
• A reference model for Data Warehousing and Business Intelligence.
• Understand the differences between Business Intelligence, and Data Warehousing, both the
disciplines and the software environments.
• Explore the benefits and application of Business Intelligence
• Understand the architectures and key components of Business Intelligence and Data Warehousing
• Discover the differences between architecture styles including the Kimball & Inmon approaches.
• Learn how to create and apply a Dimensional Data model
• Determine how to assess your current DW&BI readiness using a Business Intelligence maturity model
• Explore different Data Visualization approaches.
• Gain an outline understanding of the different Data Integration approaches available for DW & BI initiatives.
• Understand the different reporting & analytics styles and the data and process implications.
• Understand the role and suitability of different technology approaches in addressing DW&BI need.
P / 17
Data Integration Foundation & Practitioner
Course Description: New for DMBoK 2.0: Part of the Information Management “Foundation” and
“Practitioner” series: A 1 day foundation class or 2 day practitioner class covering the considerations for Data
Integration, the different architectures available and their applicability. Discuss the technologies, and activities
involved in Data Integration and migration. The 2 day class also explores use cases of the differing Data
Integration architectures.
Data Integration Foundation
(1 day) & Practitioner (2 day):
• What are the business (and technology) issues that Data Integration is seeking to address.
• The different styles of Data Integration, their applicability and implications.
• Understand the role and applicability of a canonical model in Data Integration.
• Discuss different use cases of the various Data Integration architectures and approaches.
• Understand the issues and implications of using different Data Integration approaches including:
• Point to Point,
• Extract Transform & Load,
• Change Data Capture,
• Services Oriented Architecture,
• Data federation & Virtualisation.
• Understand the relationship of Data Integration with the other Information Management disciplines in DMBoK 2.0.
Note: Data Integration is a new “Knowledge Area” introduced for DMBoK 2.0
• Outline a process for undertaking Data Integration initiatives and the typical artefacts required.
P / 18
Executive Workshops
Course Description: ½ day and 1 day Executive workshop(s) designed to give non-technical
managers a basic understanding of a various Information Management topics and their importance
to the organization. The workshops introduce the Information Management topic, its drivers, benefits
and actions organizations should take to ensure Information is managed as a key asset.
Workshop Content:
Often, technical practitioners express frustration in not being able to convince non-technical management of the importance of
information management.
Likewise, executives do not need to be encumbered with distracting technical jargon.
These workshops are designed to present core Information Management fundamentals to non-technical stakeholders in an
easy-to-understand, practical manner. Case studies and real-world examples are used to provide context and rationale for the
need for Information Management. Topics include:
• Information Management: What is it & why is it important
• The core disciplines of Information management including:
• Data Modelling & why Conceptual Data Models are an essential business tool
• Data Quality Management
• Data Governance, the glue holding all Information Management activities together
• Big Data – what it is, and what it isn’t
• Master & Reference Data Management (MDM)
• Case studies illustrating what works & what to avoid
P / 19
CDMP Certification – Exam Cram
Course Description:
A 3 day
examination preparation course and
taking of examinations for students
who wish to attain the Certified Data
Management Professional
qualification.
Pre requisites:
There are 4 levels of accomplishment for the CDMP certification,
Associate, Practitioner and Master, and Fellow.
Associate Certificate pre requisites:
• 2 years relevant Data Professional work experience
• Pass rate for all 1 exam (DMCORE) is 60%
Practitioner Certificate pre requisites:
• 3-5 years relevant Data Professional work experience
• Pass rate for all 3 exams 70%
Mastery Certificate pre requisites:
• 10+ years relevant Data Professional work experience
• Pass rate for all 3 exams at 80% or better
Course Approach:
• Delivered over 3 days in an interactive workshop
• 3 live exams taken during the course – Students can leave this course
with a professional certification
• Pay exam fees only if you pass offer
• Optional 4th exam (at no additional cost) to improve score / resit
failed examination.
Course Objectives:
Gain familiarity with
the CDMP examination format, types of
questions and the most appropriate way
of answering them.
Understand and
revise
the
major
syllabus
points.
Practice
taking
the
examinations
to
pass the CDMP examinations and gain
recognition
for
your
professional
experience.
Course Content:
• Workshop examination preparation for each of the 3
examinations
• Data Management Core Exam
• 2 elective exams of the participants choosing based on
one of the following:
•
•
•
•
•
•
•
Data Warehousing
Business Intelligence & Analytics
Data & Information Quality
Data Governance and Stewardship
Data Modelling
Data Operations
Zachman Enterprise Architecture Framework * TBD
• Pay exam fees only if you pass
• An optional (at no additional cost) examination to improve
scores on one exam (e.g. to attain “Mastery”) or resit a
failed exam.
P / 20
Integrated Business Process, Data & Requirements Definition
Course Description: A 5 day intensive class to show students an integrated requirements discovery and
definition approach covering business process, different types of requirements modelling, and the critical role
of the conceptual data model.
Understanding Business processes is critical as it’s the
business processes where value is delivered. Appreciating how
to work with business processes is now a core skill for business
analysts, process and application architects, functional area
managers, and even corporate executives.
Additionally,
Information Architects need to understand Business Processes
since information is acted on by the processes. But too often,
teaching on the topic either floats around in generalities and
familiar case studies, or descends rapidly into technical details
and incomprehensible models. This workshop shows in a
practical way how to discover and scope a business process,
clarify its context, model its workflow with progressive detail,
and assess it, and transition to the design of a new process by
determining, verifying, and documenting its essential
characteristics.
Requirements Definition:
Use cases have offered great
promise as a requirements definition technique, but many
analysts get disappointing results. That’s because published
methods are often inconsistent, complex, or focused on internal
design. The requirements definition component of the
workshop clears up the confusion. It shows how to employ use
cases to discover external requirements – how users wish to
interact with an application – and how to use service
specifications to define internal requirements – the validation,
rules, and data manipulation performed behind the scenes.
Better yet, it shows in concrete terms how the two perspectives
interact, and demonstrates synergies with data modeling and
business process workflow modeling.
Conceptual Data Modelling: Information is at the heart of all architecture disciplines and Data modeling is critical to the design not
simply of quality databases, but is also essential to other requirements techniques. These include workflow modeling and requirements
modeling (use cases and services). This is because Data Modelling ensures a common understanding of the things – the entities – that
processes and applications deal with. This component of the workshop introduces entity-relationship modeling from a non-technical
perspective, provides tips and guidelines for the analyst, and explores contextual, conceptual, and detailed modeling techniques that
maximize user involvement.
P / 21
DMBoK 2.0
P / 22
DMBoK 2.0
INTRODUCTION
DMBOK(1) OVERVIEW
SUMMARY
P / 23
1. DMBoK
Overview
P / 24
What Is the DAMA-DMBOK Guide?
› The DAMA Guide to the Data Management Body
of Knowledge (DAMA-DMBOK Guide)
› A book published by DAMA-I, 406 pages (also on
CD & PDF)
› Available from TechnicsPublications.com or
Amazon.com
› Written and edited by DAMA members
› An integrated primer: “definitive introduction”
› Modeled after other BOK documents:
» PMBOK (Project Management Body of Knowledge)
» SWEBOK (Software Engineering Body of Knowledge)
» BABOK (Business Analysis Body of Knowledge)
» CITBOK (Canadian IT Body of Knowledge)
P / 25
What is the Framework Paper?
› A 13 page summary /
white paper outline of the
DAMA-DMBOK Guide
› From over 90 countries!
» USA
48%
» Unknown
18%
» Canada
7%
» Australia
6%
» UK
3%
› Published in English,
Chinese, Spanish and
French
» India
3%
» South Africa
3%
› Over 7000 Downloads
Worldwide To Date
» Brazil
1%
› Available on DAMA
Website since July 2006
› Version 2.1 Since Nov 2007
› Version 3.2 Since July 2009
› Averaging 50 Downloads
per Week
P / 26
DAMA-DMBOK Guide Goals
› To develop, build consensus and foster adoption for a generally accepted
view of data management.
› To provide standard definitions for data management functions, roles,
deliverables and other common terminology.
› To identify “guiding principles”.
› To introduce widely adopted practices, methods and techniques, without
references to products and vendors.
› To identify common organisational and cultural issues.
› To guide readers to additional resources.
Used with kind permission of DAMA-I
P / 27
DAMA-DMBOK Guide Audiences
› Data management
professionals
› IT professional colleagues
› Data stewards
› Managers and executives
› Knowledge workers
› Consultants
› Educators
› Researchers
Used with kind permission of DAMA-I
P / 28
DAMA-DMBOK Guide Uses
› Inform a diverse audience about data
management
› Assist organisations in their enterprise
data strategy
› Build consensus across the data
management community
› Basis for effectiveness & maturity
assessments
› Help all participants understand their
responsibilities
› Guide implementation & process
improvement efforts
› Point readers to additional sources of
knowledge
› Guide development of higher
education curriculum
› Help data management professionals
prepare for Certified Data
Management Professional (CDMP)
exams
› Suggest academic research topics
Used with kind permission of DAMA-I
P / 29
DAMA-DMBOK Deliverables
› The DAMA Guide to the Data Management Body of Knowledge (DAMADMBOK Guide) is available as of 2009
› The DAMA-DMBOK Framework overview paper is available for free
download at www.dama.org. in English, Spanish and Chinese and French
» Version 3 is available in English and French
» Version 2.1 is available in Spanish and Chinese
» Version 3 will be available in these languages soon
› The DAMA Dictionary of Data Management is published on CD and
AVAILABLE for purchase on amazon.com
» Version 1 is a baseline – over 800 terms defined
» Version 1.1 revision will serve as the Glossary for the DAMA-DMBOK Guide
» CD format enables easy reference
Used with kind permission of DAMA-I
P / 30
Overall Context Diagram
Used with kind permission of DAMA-I
P / 31
Version 3
10 Functions
100+ Activities
› Enterprise Data Modelling
› Value Chain Analysis
› Related Data Architecture
›
›
›
›
Specification
Analysis
Measurement
Improvement
DATA QUALITY
MANAGEMENT
›
›
›
›
Architecture
Integration
Control
META DATA
Delivery
DOCUMENT & CONTENT
MANAGEMENT
Acquisition & Storage
Backup & Recovery
Content Management
Retrieval
Retention
›
›
›
›
Analysis
Data modelling
Database Design
Implementation
DATA
DEVELOPMENT
DATA
GOVERNANCE
MANAGEMENT
›
›
›
›
›
›
›
›
›
DATA
ARCHITECTURE
MANAGEMENT
›
›
›
›
›
Strategy
Organisation & Roles
Policies & Standards
Issues
Valuation
DATA
WAREHOUSE
& BUSINESS
INTELLIGENCE
MANAGEMENT
Architecture
Implementation
Training & Support
Monitoring & Tuning
DATABASE
OPERATIONS
MANAGEMENT
Acquisition
Recovery
Tuning
Retention
Purging
DATA SECURITY
MANAGEMENT
REFERENCE &
MASTER DATA
MANAGEMENT
›
›
›
›
›
›
›
›
›
›
›
›
›
›
›
Standards
Classifications
Administration
Authentication
Auditing
External Codes
Internal Codes
Customer Data
Product Data
Dimension Management
Used with kind permission of DAMA-I
P / 32
ORGANIZATION & CULTURE
Environmental
Elements
•
•
•
•
•
•
Critical Success Factors
Reporting Structures
Management Metrics
Values, Beliefs, Expectations
Attitudes, Styles, Preferences
Rituals, Symbols, Heritage
TECHNOLOGY
•
•
•
•
ACTIVITIES
•
•
•
•
•
Tool Categories
Standards and Protocols
Section Criteria
Learning Curves
Phases, Tasks, Steps
Dependencies
Sequence and Flow
Use Case Scenarios
Trigger Events
GOALS &
PRINCIPLES
•
•
•
•
•
PRACTICES
& TECHNIQUES
Vision and Mission
Business Benefits
Strategic Goals
Specific Objectives
Guiding Principles
• Recognized Best Practices
• Common Approaches
• Alternative Techniques
ROLES &
RESPONSIBILITIES
•
•
•
•
DELIVERABLES
•
•
•
•
•
Inputs and Outputs
Information
Documents
Databases
Other Resources
Individual Roles
Organizational Roles
Business and IT Roles
Qualifications and Skills
Used with kind permission of DAMA-I
P / 33
The DAMA-DMBOK Guide
› 13 Chapters, over 400 pages
› Standard chapter format
» Introduction
» Concepts and Activities
» Covering each Environmental Element
» Summary
» Extensive bibliography – “Further Reading”
Used with kind permission of DAMA-I
P / 34
Consistent Recurring Themes
› Data Stewardship – Business Partnership
› Data Quality
› Data Integration
› Enterprise Perspective
› Cultural Change Leadership
“Enterprise Information
Management”
Used with kind permission of DAMA-I
P / 35
DAMA-DMBOK Development Process
1. The Dictionary defines common terms
2. The Framework outlines activities within each function
3. Primary contributors draft each chapter
» Following a standard format & defined development method
4. Review teams comment on draft chapters (over 120 volunteer reviewers)
5. Further reviews through focus group workshops
» DAMA chapter meetings
» DAMA conferences
6. DAMA-DMBOK editors refine draft chapters
7. Publishing editors review and refine the complete document
Used with kind permission of DAMA-I
P / 36
DAMA- DMBOK Chapters
Ch. 1 & 2
Introduction & Overview
Ch. 8
Reference & Master Data Mgmt.
Ch. 3
Data Governance
Ch. 9
DW & Bus. Intelligence Mgmt.
Ch. 4
Data Architecture Management
Ch. 10
Document & Content Mgmt.
Ch. 5
Data Development
Ch. 11
Meta Data Management
Ch. 6
Database Operations Mgmt.
Ch. 12
Data Quality Management
Ch. 7
Data Security Management
Ch. 13
Professional Development
Used with kind permission of DAMA-I
P / 37
Brief History
› DAMA Guide to the Data Management Body of Knowledge
(DAMA-DMBoK Guide) 2009
› March 2010 - DAMA-DMBOK hardcopy version
› 2011 – version 2 DAMA Dictionary of Data Management
› 2011 Japanese version
› 2012 Portuguese version
› 2012 Chinese version
› April 2012 –DAMA-DMBOK2 Framework
› Q2 2017 – DMBoK2 Publication expected
Used with kind permission of DAMA-I
P / 38
2. DMBoK 2.0
P / 39
Dictionary, Framework & Updates
1. The DAMA Guide to the Data Management Body of
Knowledge (DAMA-DMBOK Guide), 2009
2. Japanese 2011
3. Portuguese 2012
4. Chinese 2012
5. The DAMA-DMBOK Framework overview paper is available on
www.dama.org, in English, Spanish, Chinese and Japanese
6. The DAMA Dictionary of Data management, 2nd Edition 2011
(English)
P / 40
DMBoK 2.0 progress
› Framework available April 2012
» From foundation.president@dama.org
› In writing phase as of 2012
› Some review chapters for Q2, 2013
› Revised expected publication Q4, 2014
P / 41
Reinventing the wheel
2009 Data Management Functions
P / 42
Reinventing the wheel
2013 DMBoK 2.0 Knowledge Areas
P / 43
Environmental Elements
2009 Version:
Environmental Elements
2013 Version:
Environmental Elements
PEOPLE
ORGANIZATION
& CULTURE
ORGANIZATION
& CULTURE
ACTIVITIES
TOOLS
GOALS &
PRINCIPLES
PRACTICES &
TECHNIQUES
GOALS &
PRINCIPLES
DELIVERABLES
ROLES &
RESPONSIBILITIES
ACTIVITIES
TECHNOLOGY
PRACTICES &
TECHNIQUES
DELIVERABLES
ROLES &
RESPONSIBILITIES
PEOPLE
P / 44
Functional Framework
Environmental Elements:
Details under each area
PEOPLE
ORGANIZATION & CULTURE
•
•
•
•
•
•
Critical Success Factors
Reporting Structures
Management Metrics
Values, Beliefs, Expectations
Attitudes, Styles, Preferences
Rituals, Symbols, Heritage
TOOLS
ACTIVITIES
•
•
•
•
•
•
•
•
•
Tool Categories
Standards and Protocols
Section Criteria
Learning Curves
GOALS &
PRINCIPLES
•
•
•
•
•
PRACTICES &
TECHNIQUES
• Recognized Best Practices
• Common Approaches
• Alternative Techniques
Vision and Mission
Business Benefits
Strategic Goals
Specific Objectives
Guiding Principles
ROLES &
RESPONSIBILITIES
•
•
•
•
Phases, Tasks, Steps
Dependencies
Sequence and Flow
Use Case Scenarios
Trigger Events
DELIVERABLES
•
•
•
•
•
Inputs and Outputs
Information
Documents
Databases
Other Resources
Individual Roles
Organizational Roles
Business and IT Roles
Qualifications and Skills
PEOPLE
P / 45
Context Diagram (DMBoK 1) ….
P / 46
… Replaced with:
P / 47
Consistent recurring themes
› Data Stewardship – Business Partnership
› Data Quality
› Data Integration
› Enterprise Perspective
› Cultural Change Leadership
P / 48
Standard chapter format
Introduction
› Defining Key Terms
› Goals
› Context Diagram
Concepts and Activities
› Key Concepts and Guiding Principles
› Roles Performing Activities to Create
Deliverables
› Using Best Practices and Common
Techniques
› Using Technology
Summary
› Guiding Principles Recap
› Process Summary – Activities,
Deliverables, Roles
› Organisation and Cultural Issues
Recommended Reading
P / 49
Timeline
April 2012: Framework Finalised, Downloads on-going by public
April 2013: Reviews starting
Dec 2013:
Writing completed
2014:
Publishing cycle
Note: finalised framework is just a plan and outline – can and will change as writers react,
editors as well, to the product versus the plan.
Framework will be updated to reflect the DMBoK2 as published
P / 50
DMBoK 2.0 development
Legal – Authors waivers
Agreements developed and reviewed by
DAMA’s attorney:
› Contributor Copyright Waiver
› Contributor Confidentiality Agreement
› Reviewer Non-Disclosure
Development Process
› DMBOK Authors were approached
› New authors had to submit writing
samples
› Primary contributors drafted each chapter
» Standard format and development process:
authoring packages
› Review teams comment on draft chapters
› Further reviews through focus group
workshops (WEBEX)
› Formal review period (Google Apps)
P / 51
Chapter development
P / 52
3. DMBoK &
other
frameworks
DMBoK alignment with:
COBIT & TOGAF
P / 53
IT Governance
COBIT
STRATEGIC
ALIGNMENT
Monitoring and control of
all performances in terms
of their orientation towards
the corporate strategy.
PERFORMANCE
MANAGEMENT
Alignment of the business and IT
strategy with regard to the
definition as well as the review
of and improvement in IT’s
contribution to value.
VALUE
DELIVERY
IT
Within their service cycle, IT
services in their entirety
bring a benefit in respect of
the corporate strategy and
generate added value for the
enterprise.
GOVERNANCE
Identification and analysis of
the risks in order to avoid
unpleasant surprises and to
gain a clear understanding of
the company’s risk preference.
RISK
MANAGEMENT
RESOURCE
MANAGEMENT
Efficient management of resources
such as applications, information,
infrastructure and people, as well as
optimization of the investment.
P / 54
An Overarching Management Framework
By aligning the various activities and providing an overarching management framework we can
› Identify the dependencies and
boundaries of the activities,
› Reduce the likelihood of
duplication,
› Increase the certainty of realising
the required capabilities, and
› Ensure tighter integration
across the organisation
P / 55
P / 56
The building blocks can be extended across other services
P / 57
Align Data Management process to TOGAF adoption
P / 58
Christopher Bradley
I N F O R M AT I O N M A N A G E M E N T S T R AT E G I S T
Chris.Bradley@DMAdvisors.co.uk
+44 7973 184475 (mobile) +44 1225 923000 (office)
@inforacer
uk.linkedin.com/in/christophermichaelbradley/
TRAINING
ADVISORY
infomanagementlifeandpetrol.blogspot.com
C O N S U LT I N G
C E R T I F I C AT I O N
P / 59