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Enterprise Data World 2010 – Adopting the DMBOK2
Agenda
The Birth of a DMO at TELUS
TELUS DMO Functions
DMO Guidance
DMBOK functions and TELUS Priorities
Adoption Obstacles
Future Considerations
Enterprise Data World 2010 – Adopting the DMBOK4
Timeline
Late 2008 – Data Management team created as a ‘mashup’ of DA, DBA and BI groups.
Early 2009 – DMBOK published by DAMA. Review of TELUS Data Strategy and Data Management functions conducted by Data Management team.
April 2009 – EDW 2009, TELUS purchases a copy of DMBOK.
Jun 2009 –DAMA DMBOK adopted as the framework of reference for a TELUS Data Management Organization (DMO)
Enterprise Data World 2010 – Adopting the DMBOK5
Data Management Organization (DMO)
Making TELUS ‘Smarter’
‘Smarter’ means: ensuring TELUS has the information it needs to operate, thrive and compete
More focus on:• Understanding our current assets
• Cleaning up the “pollution”
• Data Governance (long term, enterprise view) –preventing further “pollution”
• Getting information into the hands of decision makers
Enterprise Data World 2010 – Adopting the DMBOK6
Data Governance
Governance is not the same as Management, but should co-ordinate management activities.
Governance occurs through successful execution of co-ordinated management functions and aligned processes.
How mature is our current Governance? Where should we be as a target?
What are the functional priorities?
Enterprise Data World 2010 – Adopting the DMBOK7
Data Governance Maturity Model
From “The Data Asset”, Tony Fisher, Wiley and Sons, 2009
Enterprise Data World 2010 – Adopting the DMBOK9
Organizational Review
DA, DBA, and BI functions are mature and formalized as separate teams, but need to become integrated under a Data Management mandate.
What does that process model look like? What other functions need to be included?
How do we organize the DMO to functionally integrate what we are currently doing with what we need to add to the functional mix?
Is there something published that we can adopt and adapt to?
Enterprise Data World 2010 – Adopting the DMBOK10
TELUS DMO Functions – at creation
DA, DBA, and BI functions considered core competencies of the new TELUS DMO
Master Data Management, Metadata Management, and Data Quality dispersed across many areas, but understood to be ‘developing’ competencies of the TELUS DMO.
Content Management not clearly understood as a DMO priority, but seen as the logical place to manage metadata and taxonomies for unstructured and semi-structured content.
DA team to continue in a ‘dotted line’ relationship with IT Architecture to maintain alignment with Application and Technology domains.
Enterprise Data World 2010 – Adopting the DMBOK12
Burton Group12
The Data Management Organization: Key to Effective Data Management v 1.0, 4 May 2009, Author(s): Noreen Kendle
Data Management is viewed as a governing body, responsible for Modeling activities, and connected to other Data related IT functions
The Burton model involves Data Architecture, Policies, Practices, and Processes and is used to support and protect an organization’s data assets
The TELUS DMO also has direct responsibility for Business Intelligence and Database Management. The Burton model is useful for Data Architecture and Strategy, but a broader Functional framework is needed
See also: 2010 Planning Guide: Data Management Strategies v 1.0, 3 September 2009, Author(s): Lyn Robison
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Forrester
Forrester provides a rich perspective for Data Management functions such as Master Data Management, Data Warehousing/Business Intelligence, Data Quality and Enterprise Data Integration.
An overall framework for Data Management, however, doesn’t appear to exist.
For Data Governance, see “Data Governance: What Works And What Doesn‘t by Rob Karel with J. Paul Kirby, Boris Evelson , September 10, 2007”
Seriously consider joining the Information and Knowledge Management Professional channel.
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Gartner
The Gartner Data Management and Integration Vendor Guide, April 2009, Regina Casonato, Mark A. Beyer, Ted Friedman
Limited to Structured Data Assets
Provides guidance to the large Vendor landscape in four areas:
Data Quality Tools
Data Integration Tools
Database Management Systems
Data Warehouse DBMS’s
Also has a list of “Cool” vendors
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DMBOK Activities
Appendix 9 of the DMBOK lists all of the Data Management activities by Management Function
I think John’s comment was “This is exactly what I’ve been looking for!”
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TELUS DMO and DMBOK9 separate management functions surrounding Data Governance
Currently covered by TELUS DMO: Data Architecture, Data Development, Database Operations, Data Warehousing/Business Intelligence
Data Security managed in partnership with Corporate Security
Areas for DMO organizational enhancement: Data Quality, Metadata, and MDM
Still not sure what to do about Document and Content Management, but everything else seems to fit
Do our activities match DMBOK activities?
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Metadata Management at TELUSThe Data Management Organization (or DMO) at TELUS, is the group responsible for managing the Data Assets of the enterprise. The Metadata associated with this governance of Data Assets should also be managed by us and integrated with appropriate discipline.
Metadata the DMO manages reasonably well:• Data 'at rest' (published) and where movement is managed• Inclusive of Database specifications, data models, business intelligence
frameworks and components, data mapping and transformation
Metadata for which the DMO needs to develop management processes:• KPI's, Common Business Vocabulary, Reporting, Operational Metadata for DW-
BIM, MDM, Data Quality functions, Business Process Workflow, SOA,
Things we don’t currently manage (although we should participate and govern):• ERP, Configuration Management, Content Management
Things where the lines are blurred• BPM, Unstructured data, embedded metadata (data truly 'in motion')• Web 2.0, Mashups, Enterprise Search, Text Analytics
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TELUS Metadata Strategy“A metadata strategy is a statement of direction in Metadata Management by the Enterprise” – DAMA-DMBOK
Metadata Management has three basic enterprise organizational models1)Centralized: All metadata is captured, managed and disseminated from a
corporate repository. Sometimes called the 'uber' repository.2)Federated: Metadata is managed within defined 'domains' or 'zones'. Governance
mechanisms across the zones are defined and a Metadata Integration Plan is developed to manage metadata movement between the federated domains.
3)Localized: All metadata locations are responsible for managing and governing their own metadata independent of each other. Interface agreements are developed on a discovery basis as the needs of IT projects execute.
TELUS currently operates under a Localized model, but desires to operate under a Federated model. This Federated model is not a DMBOK model
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Federation and DMBOK Metadata ArchitectureThe DMBOK describes three approaches to Metadata Architecture (section 11)1. Centralized – use of a single Metadata Repository that contains copies of
Metadata from identified, relevant sources for the domain under management2. Distributed – no persistent repository. A metadata retrieval engine uses metadata
virtualization technologies to access metadata from local sources in real time.3. Hybrid – persistent repository used for “user-added” metadata as enhancements
to metadata are retrieved from source in real time through virtualization.
The DMBOK does not specifically define a federated approach to Metadata Management with respect to the organization of Metadata Management Domains
Within the TELUS DMO Domain the Centralized Metadata Architecture as described in section 11, will apply (as opposed to Distributed or Hybrid). Should this be an Enterprise approach applying to all other domains? (recommended).
Should support “Repository to Repository” co-operation with the DMO Domain playing the role of an Integration Hub for the Enterprise.
Enterprise Data World 2010 – Adopting the DMBOK25
Data Quality Process
Data Quality Processes are usually a variation of the Deming model for Quality improvement (Plan, Do, Study, Act). The DMBOK proposes a similar “Deming-like” Data Quality cycle
Plan - for the assessment of the current state and identify key metrics for measuring data quality.
Deploy - processes for measuring and improving the quality of data.
Monitor - and measure the levels in relation to the defined business expectations.
Act - to resolve any identified issues to improve data quality and better meet business expectations.
Larry English has a new book out. “Information Quality Applied”, Oct 2009, Wiley
Enterprise Data World 2010 – Adopting the DMBOK26
Gartner - on Data Quality
TELUS has existing relationships with numerous vendors including all of the ones found in the upper right portion of this ‘magic quadrant’
If those relationships don’t currently include appropriate ‘tooling’ for Data Quality, what would it take to include it?
An enhanced relationship with SAS now includes DataFlux Enterprise Data Quality offerings for use in improving Data Quality at TELUS.
Enterprise Data World 2010 – Adopting the DMBOK27
DataFluxData Profiling and Discovery – uncovers the structure, completeness and suitability of data within data resources, cataloging and analyzing metadata to discover metadata relationships. dfPower Profile is the DataFlux data profiling tool, dfPower Explorer is the DataFlux tool for metadata analysis. Real-Time Data Quality - create data services that can standardize, correct and integrate data as it arrives in your IT systems. The DataFlux Integration Server allows you to extend business rules for data quality and data integration throughout the IT environment. dfPower Quality provides matching technology, transformation routines and identification logic. Data Enrichment - dfPower Verify gives you the functionality to create complete and usable address information, and enrich that data with geographic, demographic, product hierarchy or other internal or external data sources.Data Monitoring - dfPower Monitor can provide real-time business rules monitoring for your data, detecting when data exceeds pre-set limits and allowing you to immediately recognize and correct issues before the quality of your data declines.
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DataFlux Methodology
DataFlux has a published Analyze-Improve-Control methodology that leverages their Integration Platform. Also looks very Deming-ish.
Profiling – The Analyze bit
Quality – Step 1 of Improve
Integration – Step 2 of Improve
Enrichment – Step 3 of Improve
Monitoring – The Control bit
This methodology is being adopted and tailored for TELUS use as part of our DQM pilot in 2010.
Enterprise Data World 2010 – Adopting the DMBOK29
DQM and MDM
“Data quality and MDM are inextricably linked, because the net purpose of MDM initiatives is to deliver a single source of truth on one or more master data domains containing accurate, complete, timely and consistent data. Without early, systematic attention to high levels of data quality (plus the right data quality tools and solid data governance to resolve the issues that inevitably come up) your master data hub will simply be a fast, automated way to shoot yourself in the foot.” – Dan Power, March 2009, Information Management Magazine
MDM initiatives and their resulting Data Stores (MDM hubs) at TELUS require Data Quality processes to be successful. Currently, this is not co-ordinated under a Data Quality Management function of the DMO. This is an undesirable gap in Data Governance. A critical success factor for a DMO Data Quality program is the ability to close this gap
Enterprise Data World 2010 – Adopting the DMBOK31
Economic Meltdown
2009 was not an easy year to expand into new functional areas. Timelines needed some adjustment
Do we really need to buy new tools or can our existing infrastructure and technology choices be used for growth areas?
Look at re-negotiating deals and strengthening current vendor relationships
Enterprise Data World 2010 – Adopting the DMBOK32
Organizational Impact
It is harder to Govern that which you do not also Manage.
TELUS has 3 VP’s of Systems Development
Business Units have considerable autonomy. SaaS is becoming a mega-trend.
A “Solutions for Data Management” team doesn’t exist. Is this an evolution of the SBI team or a ‘matrix’ of many teams?
It is likely to be both. See bullet 1
Enterprise Data World 2010 – Adopting the DMBOK33
Funding
TELUS prioritizes projects that have high ROI. Funding pool is reduced considerably by mandatory items and market priorities.
Making TELUS smarter will require funded effort. The business case for DMO initiatives will be analyzed.
Data Management Solutions may not attain the priority and visibility needed to obtain desired funding.
Infrastructure Improvement vs. new Capital Asset vs. Operational Expense
Enterprise Data World 2010 – Adopting the DMBOK35
Data Federation
Look to other sources (Forrester’s “Information Fabric” for example) for guidance managing solutions and technologies that use Data Federation and Data Virtualization
Building Data Services for a SOA delivery will also likely require use of these technologies and some form of Data Integration Management
SaaS, Hosted Solutions and “BI in the Cloud” will accelerate the need.
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Data Integration Management
There is no distinct function for this in the DMBOK. It is assumed that a landscape of Transactional Data, Master Data Stores, and Reference Data Stores is transformed into integrated data when moved to a Data Warehouse in a managed fashion.
Data Warehousing (and ERP for that matter) creates integrated data through the population of a homogenized data store.
Most enterprises, however, must deal with a dispersed application landscape of heterogeneous data stores
Enterprise Data World 2010 – Adopting the DMBOK37
Semantic Technologies
The ‘Cool’ vendors on Gartner’s 2009 DM&I list
Think of this as Metadata on steroids
There are some interesting presentations here at EDW. I intend to educate myself further.
How will we add this to the mix? Perhaps as an extension of Metadata Management, as part of the missing Data Integration Management function or as something new.
Maybe all three.