turning bad habits into good practicesnces.ed.gov/forum/pdf/data_res_quality_ppt.pdfturning bad...
TRANSCRIPT
© 2005 by Michael H. Brackett
DRDRP.O. Box 151Lilliwaup, Washington 98555Voice 360 877 5507Fax [email protected]/mhbrackett
DATA RESOURCE QUALITY
TURNING BAD HABITSINTO GOOD PRACTICES
NATIONAL FORUM ON EDUCATION STATISTICSFEBRUARY 21, 2005
NEW ORLEANS
MICHAEL H. BRACKETT
CONSULTING DATA ARCHITECTDATA RESOURCE DESIGN & REMODELING
© 2005 by Michael H. Brackett
CONTENTS
CURRENT SITUATION
DATA RESOURCE CONCEPTS
HALTING DATA DISPARITY
RESOLVING DATA DISPARITY
CULTURAL CONSIDERATIONS
CONCLUSION
PRESENTER’S BIBLIOGRAPHY
© 2005 by Michael H. Brackett
CURRENT SITUATION
BUSINESS INFORMATION DEMANDAN ORGANIZATION’S CONTINUOUSLY INCREASING, CONSTANTLY CHANGING NEEDFOR CURRENT, ACCURATE, INTEGRATED INFORMATION, OFTEN ON SHORT NOTICE OR VERY SHORT NOTICE, TO SUPPORT ITS BUSINESS ACTIVITIES
CURRENT BUSINESS IMPACTTHIS BUSINESS INFORMATION DEMAND IS NOT BEING METPUBLIC & PRIVATE SECTOR BUSINESS IS IMPACTEDBUSINESS DECISIONS ARE LESS-INFORMEDCITIZENS & CUSTOMERS ARE IMPACTEDOPPORTUNITIES ARE MISSED
PROBLEMHIGH QUANTITIES OF DISPARATE DATA IN MOST ORGANIZATIONSDATA NOT THOROUGHLY UNDERSTOODDATA RESOURCE NOT FORMALLY MANAGEDDATA NOT READILY AVAILABLEDATA QUALITY LOW
BUSINESS INFORMATION DEMAND NOT BEING MET!
© 2005 by Michael H. Brackett
CURRENT SITUATION
DISPARATE DATA - A TRUISMDATA THAT ARE ESSENTIALLY NOT ALIKE, OR ARE DISTINCTLY DIFFERENT IN KIND, QUALITY, OR CHARACTER. THEY ARE UNEQUAL AND CANNOT BE READILY INTEGRATED TO ADEQUATELY MEET THE BUSINESS INFORMATION DEMAND.
BASIC DATA PROBLEMUNKNOWN DATA EXISTANCE
ORGANIZATION NOT AWARE OF ALL DATA AT ITS DISPOSALUSUALLY NOT EVEN INVENTORIED
UNKNOWN DATA MEANINGCONTENT AND MEANING OF DATA NOT FULLY KNOWNDATA NOT THOROUGHLY UNDERSTOOD
HIGH DATA REDUNDANCYDATA HIGHLY REDUNDANT AND INCONSISTENTAVERAGE REDUNDANCY FACTOR OF 10 FOR LARGE ORGANIZATIONS
HIGH DATA VARIABILITYDATA HIGHLY VARIABLE IN FORMAT AND CONTENTAVERAGE FACTOR OF 15 TO 20 FOR LARGE ORGANIZATIONS
THAT’S THE GOOD NEWS!
© 2005 by Michael H. Brackett
CURRENT SITUATION
DISPARATE DATA RESOURCEA DATA RESOURCE THAT IS SUBSTANTIALLY COMPOSED OF DISPARATE DATA THAT ARE DIS-INTEGRATED AND NOT SUBJECT ORIENTED. A STATE OF DISARRAY WHERE THE LOW QUALITY DOES NO, AND CANNOT, ADEQUATELY SUPPORT THE BUSINESS INFORMATION DEMAND.
DISPARATE DATA CYCLEA SELF-PERPETUATING CYCLE WHERE DISPARATE DATA CONTINUE TO BE PRODUCED AT AN EVER-INCREASING RATE BECAUSE PEOPLE DO NOT KNOW ABOUT EXISTING DATA OR DO NOT WANT TO USE EXISTING DATA.
THAT’S THE BAD NEWS!
Can't find dataDon't trust data
Can't access data
People uncertain about the data
People create their own data
Data not integratedData not
documented
© 2005 by Michael H. Brackett
CURRENT SITUATION
DISPARATE DATA SPIRALDISPARATE DATA INCREASING BY SEVERAL ORDERS OF MAGNITUDECREATING DISPARATE DATA FASTER THAN EVER BEFORESPREADING TO NON-TABULAR DATA AND DATA RESOURCE DATADISPARITY SPIRALING OUT OF CONTROLNO FORESEEABLE END IN SIGHT!
DATA RESOURCE DRIFTTHE NATURAL, STEADY DRIFT OF A DATA RESOURCE TOWARDS DISPARITY IF ITS DEVELOPMENT IS NOT PROPERLY MANAGED AND CONTROLLED.
THAT’S THE REALLY BAD NEWS!
Low QualityData Resource
High QualityData Resource
Data Resource
Diff
icul
t
Easiest
Natural Drift
© 2005 by Michael H. Brackett
CURRENT SITUATION
DATA DILEMMAORGANIZATIONS FACING REAL DILEMMA ABOUT THEIR DATA RESOURCEHIGH DEMAND FOR INTEGRATED DATA TO SUPPORT BUSINESS NEEDSCONTINUED RAPID PRODUCTION OF DISPARATE DATA
NO STATUS QUOTHERE IS NO STATUS QUO FOR DEVELOPING A HIGH-QUALITY DATA RESOURCENATURAL DRIFT TOWARD DISPARITY WILL CONTINUESITUATION WILL GET WORSE
A STATUS QUO LEADS TOORGANIZATIONAL FAILURE BY INFORMATION DEPRIVATION!
© 2005 by Michael H. Brackett
CURRENT SITUATION
MUST CONSCIOUSLY ALTER THE NATURAL DRIFTTOWARD HIGH-QUALITY DATA RESOURCEBREAK DISPARATE DATA CYCLESTOP THE SPIRALING DISPARITYCREATE A HIGH-QUALITY SHARABLE DATA RESOURCE
SILVER BULLETS JUST DO NOT EXISTOBJECTIVE: AN ATTEMPT TO ACHIEVE SOME GAIN WITHOUT ANY PAINRESULT: ENDURING CONSIDERABLE PAIN WITH MINIMAL GAIN
THERE ARE NO SILVER BULLETS!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
BUSINESS INTELLIGENCE VALUE CHAIN
I-ORGANIZATIONINTELLIGENT LEARNING ORGANIZATION - HUMAN RESOURCE REALMHUMAN RESOURCE REALM LINKS TECHNOLOGY REALM & BUSINESS REALMREQUIRES GOOD INFORMATION TO SUPPORT BUSINESS STRATEGIES & GOALSREQUIRES A HIGH-QUALITY SHARABLE DATA RESOURCE
MUST BEGIN WITH THE DATA RESOURCE!
DATA RESOURCEINFORMATION
KNOWLEDGE ENVIRONMENT
BUSINESS GOALS
BUSINESS INTELLIGENCEBUSINESS STRATEGIES
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
MANY PEOPLE STILL CONFUSE ‘DATA’ - ‘INFORMATION’ - ‘KNOWLEDGE’DATA
INDIVIDUAL FACTS OUT OF CONTEXT WITH LITTLE MEANING123.45
DATA IN CONTEXTINDIVIDUAL FACTS WITH MEANINGACCOUNT BALANCE AT NOON ON JANUARY 12, 2001
INFORMATIONSET OF DATA IN CONTEXTRELEVANT TO ONE OR MORE PEOPLEAT A POINT IN TIME OR FOR A PERIOD OF TIME
KNOWLEDGEINFORMATION RETAINED BY INDIVIDUALSCOMBINED WITH EXPERIENCE
DATA ARE THE FOUNDATION!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
QUALITY DEFINEDDATA RESOURCE QUALITYA MEASURE OF HOW WELL THE DATA RESOURCE SUPPORTS THE CURRENT AND THE FUTURE BUSINESS INFORMATION DEMAND
DATA QUALITYA SUBSET OF DATA RESOURCE QUALITY DEALING WITH DATA VALUES
ULTIMATE DATA RESOURCE QUALITYA DATA RESOURCE THAT IS STABLE ACROSS CHANGING BUSINESS AND CHANGING TECHNOLOGY SO IT CONTINUES TO SUPPORT THE CURRENT AND FUTURE BUSINESS INFORMATION DEMAND
INFORMATION QUALITYA MEASURE OF THE ABILITY TO GET THE RIGHT DATA, TO THE RIGHT PEOPLE, IN THE RIGHT PLACE, AT THE RIGHT TIME, IN THE RIGHT FORM, AT THE RIGHT COST, SO THEY CAN MAKE THE RIGHT DECISIONS, AND TAKE THE RIGHT ACTIONS.
INTELLIGENT LEARNING ORGANIZATION NEEDS A HIGH-QUALITY STABLE DATA RESOURCE!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
COMPARATE DATA VISIONCOMPARATE DATADATA THAT ARE ALIKE, SIMILAR IN KIND, QUALITY, AND CHARACTER, ARE EASILY UNDERSTOOD, AND CAN BE READILY INTEGRATED
COMPARATE DATA RESOURCESUBJECT ORIENTED, INTEGRATED, HIGH QUALITY, SHARABLE DATA RESOURCE THAT FULLY SUPPORTS THE CURRENT AND THE FUTURE BUSINESS INFORMATION DEMAND
ComparateData
Resource
DataResource
Guide
InformationSystem
BusinessInformation
Demand
DisparateData Resource
COMMON DATA ARCHITECTURE
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
COMPARATE DATA CYCLEA SELF-PERPETUATING CYCLE WHERE THE USE OF COMPARTE DATA IS CONTINUALLYREINFORCED BECAUSE PEOPLE UNDERSTAND AND TRUST THE DATA.
RESOLVE THE DATA DILEMMABRING STABILITY TO THE DATA RESOURCE TO TRANSCEND CHANGE
STOP THE NATURAL DRIFT OF A DATA RESOURCEBY HALTING THE DISPARATE DATA CYCLE
AND STARTING A COMPARATE DATA CYCLE!
People find, trust, and access data
Existing data resource readily
shared
New data created when necessary
New data integrated and documented
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
COMPARATE DATA RESOURCESUBJECT ORIENTED
BASED ON BUSINESS OBJECTS AND EVENTS IN THE REAL WORLDDATA SUBJECTS REPRESENT BUSINESS OBJECTS AND EVENTSDATA RESOURCE STRUCTURED BY DATA SUBJECTSALL CHARACTERISTICS ABOUT A DATA SUBJECT STORED WITH THE DATA SUBJECT
INTEGRATEDFULLY INTEGRATED WITHIN A COMMON DATA ARCHITECTUREONE ARCHITECTURE FOR THE ENTIRE DATA RESOURCEALL DATA MANAGED WITHIN THAT SINGLE ARCHITECTUREDATA PROPERLY DEPLOYED TO MEET BUSINESS NEEDS
SUPPORTED BY DATA RESOURCE GUIDECOMPREHENSIVE INDEX TO DATA RESOURCEA COMPLETE INTEGRATED UNDERSTANDING ABOUT THE DATA RESOURCE
INTEGRATEDACROSS ORGANIZATION UNITSACROSS BUSINESS ACTIVITIES
AN INTEGRATED DATA RESOURCE IS ONE VERSION OF TRUTH ABOUT THE BUSINESS!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
DATA ARCHITECTURE DEFINITION 1THE METHOD OF DESIGN AND CONSTRUCTION OF A DATA RESOURCE THAT ISBUSINESS DRIVEN,BASED ON REAL-WORLD SUBJECTS PERCEIVED BY THE ENTERPRISE,AND IMPLEMENTED INTO APPROPRIATE OPERATING ENVIRONMENTS.IT CONSISTS OF COMPONENTS THATPROVIDE A CONSISTENT FOUNDATION ACROSS ORGANIZATIONAL BOUNDARIESTO PROVIDE EASILY IDENTIFIABLE, READILY AVAILABLE HIGH-QUALITY DATATO SUPPORT THE BUSINESS INFORMATION DEMAND
DATA ARCHITECTURE DEFINITION 2THE COMPONENT OF THE DATA RESOURCE FRAMEWORK THATCONTAINS ALL THE ACTIVITIES, AND THE PRODUCTS OF THOSE ACTIVITIES, RELATED TO THE IDENTIFICATION, NAMING, DEFINITION, STRUCTURING, INTEGRITYACCURACY, EFFECTIVENESS, AND DOCUMENTATION OF THE DATA RESOURCE
DATA INTEGRATION REQUIRES A FORMAL DEFINITIONOF DATA ARCHTIECTURE!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
COMMON DATA ARCHITECTURECOMMON CONTEXT FOR
INVENTORYING ALL DATAUNDERSTANDING THE CONTENT AND MEANING OF DATAIMPROVING DATA QUALITYTRANSFORMING AND INTEGRATING DISPARATE DATADEFINING NEW DATAMANAGING DYNAMIC DATA DEPLOYMENT
EINSTEIN’S PRINCIPLEA PROBLEM CANNOT BE SOLVED WITH THE SAME LEVEL OF TECHNOLOGY USED TO CREATE THAT PROBLEMA HIGHER LEVEL OF TECHNOLOGY IS NEEDEDTHE COMMON DATA ARCHITECTURE IS THE HIGHER LEVEL OF TECHNOLOGY FOR UNDERSTANDING AND MANAGING DATA
DEVELOP CUSTOMIZED METHODONE SIZE FITS ALL METHODS DO NOT WORKCOMMON DATA ARCHITECTURE HAS CONCEPTS - PRINCIPLES - TECHNIQUESORGANIZATION HAS PROBLEMS - NEEDS - ENVIRONMENTCUSTOMIZE A METHOD TO SUIT ORGANIZATION
CUSTOMIZED METHOD HELPS RESOLVE THE DATA DILEMMA!
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
ENTERPRISE DATA ARCHITECTUREMANY DIFFERENT DEFINITIONSCONFLICTING AND CONFUSING
AN ENTERPRISE DATA ARCHITECTURE IS A SUBSET OF THE COMMON DATA ARCHITECTURE THAT REPRESENTS THE COMPARATE DATA RESOURCE.
IT REPRESENTS THE DESIRED ENTERPRISE-WIDE DATA ARCHITECTURE FOR AN ORGANIZATION.
IT IS THE PATTERN FOR BUILDING THE COMPARATE DATA RESOURCE FROM THE DISPARATE DATA
THE ENTERPRISE DATA ARCHITECTURE REPERESENTSTHE COMPARATE DATA RESOURCE!
COMMON DATA ARCHITECTURE
Disparate Data Resource Comparate Data Resource
Enterprise Data Architecture
© 2005 by Michael H. Brackett
DATA RESOURCE CONCEPTS
ACHIEVING AN INTEGRATED DATA RESOURCEPHASE 1 - HALT THE CREATION OF DISPARATE DATA
ESTABLISH A COMMON DATA ARCHITECTUREDEVELOP NEW DATA WITHIN THAT COMMON DATA ARCHITECTUREPROACTIVE PHASEPREVENTS FURTHER DATA DISPARITYMUST BE DONE FIRST
PHASE 2 - RESOLVE THE EXISTING DATA DISPARITYTRANSITION DISPARATE DATA TO A COMPARATE DATA RESOURCEFORMAL DATA TRANSFORMATION WITHIN A COMMON DATA ARCHITECTUREREACTIVE PHASERESOLVES DISPARATE DATAMUST BE DONE AFTER PHASE 1
DATA INTEGRATION BEGINS BYSTOPPING FURTHER DATA DISPARITY
AND THEN RESOLVING EXISTING DISPARITY!
© 2005 by Michael H. Brackett
DATA NAMES
FORMAL DATA NAMESDATA NAMES THAT READILY AND UNIQUELY IDENTIFY A FACT OR GROUP OF FACTSIN THE DATA RESOURCE. THEY ARE DEVELOPED WITHIN A FORMAL DATA NAMING TAXONOMY AND ARE ABBREVIATED WHEN NECESSARY WITH A FORMAL SET OFABBREVIATIONS AND A FORMAL ABBREVIATION ALGORITHM.
GOOD PRACTICESFORMAL DATA NAMING TAXONOMY
MAKES DATA NAMING EQUIVALENT TO ANIMALS, PLANTS, MINERALS, CHEMICALS
DATA NAMING VOCABULARYEXPAND CLASS WORD CONCEPT TO ALL COMPONENTS OF THE DATA NAMING TAXONOMYSET OF COMMON WORDS FOR EACH COMPONENT OF DATA NAMING TAXONOMYPROVIDE COMMON MEANING ACROSS DATA NAMES
PRIMARY DATA NAMETHE FORMAL DATA NAME THAT IS FULLY SPELLED OUT, REAL WORLD, UNABBREVIATED,UNTRUNCATED, BUSINESS NAME OF THE DATA THAT HAS NO SPECIAL CHARACTERSOR LENGTH LIMITATIONS.
MUST BE UNIQUE AND MEANINGFUL TO THE BUSINESSALL OTHER DATA NAMES ARE ALIASES OF THE PRIMARY DATA NAME
© 2005 by Michael H. Brackett
DATA NAMES
DATA NAME WORD ABBREVIATIONSPRIMARY DATA NAMES MUST BE FORMALLY ABBREVIATED TO MEET LENGTH RESTRICTIONSDATA NAME WORD ABBREVIATIONS
DATA NAME ABBREVIATION ALGORITHMA FORMAL PROCEDURE FOR ABBREVIATING PRIMARY DATA NAMES USING ABBREVIATIONS VARIETY OF DIFFERENT ALGORITHMSCAN HAVE MORE THAN ONE ABBREVIATION ALGORITHMTHE NUMBER OF ALGORITHMS IS NOT IMPORTANT - THE FORMALITY IS
© 2005 by Michael H. Brackett
DATA DEFINITIONS
COMPREHENSIVE DATA DEFINITIONSFORMAL DATA DEFINITIONS THAT PROVIDE A COMPLETE, MEANINGFUL, EASILY READ,READILY UNDERSTOOD DEFINITION THAT THOROUGHLY EXPLAINS THE CONTENT ANDMEANING OF THE DATA.
GOOD PRACTICESMEANINGFUL DATA DEFINITIONS
CONTENT AND MEANING WITH RESPECT TO THE BUSINESSNOT WHERE DATA STORED, HOW DATA USED, OR WHERE DATA CAPTUREDSIMILARITIES AND DIFFERENCES WITH CLOSELY RELATED DATAHISTORY IF PERTINENT TO THE MEANING - NOT AN AUDIT TRAIL OF DEFINITIONSWHAT IS AND IS NOT INCLUDEDINCLUDE BUSINESS CLIENTS
THOROUGH DATA DEFINITIONSNO LENGTH LIMITATIONSAPPROPRIATE BUSINESS TERMINOLOGYSTRONG DENOTATIVE MEANING - LIMIT CONNOTATIVE MEANING1 TO3 PARAGRAPHS OF 2 TO 3 SENTENCES EACH
CORRECT DATA DEFINITIONSCURRENT WITH THE BUSINESSROUTINELY REVIEWED AND ENHANCEDEVOLVE AS THE BUSINESS EVOLVES
© 2005 by Michael H. Brackett
DATA STRUCTURES
PROPER DATA STRUCTURESA DATA STRUCTURE THAT PROVIDES A SUITABLE REPRESENTATION OF THE BUSINESS,AND DATA SUPPORTING THE BUINESS, THAT IS RELEVANT TO THE INTENDED AUDIENCE.
GOOD PRACTICESDATA STRUCTURE COMPONENTS
ENTITY - RELATION DIAGRAMSHOWS THE DATA SUBJECTS AND THE RELATIONS BETWEEN THEMLIKE THE FLOOR PLAN OF A HOUSEDOES NOT SHOW DETAIL WITHIN EACH DATA SUBJECTSYMBOLS FOLLOW SEMIOTIC THEORY
DATA ATTRIBUTE STRUCTURESHOWS DATA ATTRIBUTES IN A DATA SUBJECTSHOWS ROLES DATA ATTRIBUTES PLAY
© 2005 by Michael H. Brackett
DATA STRUCTURES
PRINCIPLESTECHNICALLY CORRECT & CULTURALLY ACCEPTABLE
TECHNICALLY CORRECT IS LIKE BUILDING CODESCULTURALLY ACCEPTABLE IS LIKE AESTHETICS
STRUCTURALLY STABLE & BUSINESS FLEXIBLEARCHITECTURE REMAINS STABLE AS BUSINESS CHANGESSUPPORTS BUSINESS PROCESS IMPROVEMENTENCOURAGES BUSINESS IMPROVEMENT
TURNING POINT BETWEEN PREDOMINANTLY DISPARATE ANDPREDOMINANTLY COMPARATE DATA RESOURCE!
© 2005 by Michael H. Brackett
DATA INTEGRITY RULES
PRECISE DATA INTEGRITY RULESA DATA INTEGRITY RULE THAT PRECISELY SPECIFIES THE CRITERIA FORHIGH-QUALITY DATA VALUES AND REDUCES OR ELIMINATES DATA ERRORS.
GOOD PRACTICESDATA RULE CONCEPT
SUBSET OF BUSINESS RULES ACCORDING TO THE ZACHMAN FRAMEWORKDEALS WITH THE DATA COLUMN OF THE FRAMEWORKALLOWS PRECISE SPECIFICATION FOR QUALITY IMPROVEMENT
A DATA DEFINITION IS NOT A DATA RULEA DEFINITION IS, BY DEFINITION, A DEFINITION
PROBLEM MAKING DEFINITION A RULEIMPACTS A COMPREHENSIVE DEFINITIONSLEADS TO ONE- LINE PHRASES WITH ADDITIONAL EXPLANATIONADDITIONAL EXPLANATION OFTEN NOT PROVIDEDREVERSION TO LEGACY DATA DEFINITIONS
A DATA DEFINITION IS NOT A DATA RULE!
© 2005 by Michael H. Brackett
DATA INTEGRITY RULES
DATA INTEGRITY RULE NAMESFORMAL NAME ACCORDING TO DATA NAMING TAXONOMY & VOCABULARYUSES THE ! NOTATION CUSTOMER. NAME CHANGE!REQUIRES NORMALIZATION OF DATA RULES
DATA RULE IS NORMALIZEDTO THE DATA RESOURCE COMPONENT IT REPRESENTSOR ON WHICH IT TAKES ACTION
DATA INTEGRITY RULE NOTATIONACCEPTABLE AND UNDERSTANDABLE TO BUSINESS CLIENTSBASED ON MATHEMATICAL AND LOGIC NOTATION WHERE PRACTICALNOTATION READILY AVAILABLE ON STANDARD KEYBOARD
DATA INTEGRITY RULE TYPESDATA VALUECONDITIONAL DATA VALUEDATA STRUCTURECONDITIONAL DATA STRUCTUREDATE DERIVATIONDATE RETENTION
© 2005 by Michael H. Brackett
DATA INTEGRITY RULES
DATA INTEGRITY RULE ENFORCEMENTONE SET OF DATA INTEGRITY RULESAPPLY TO ALL DATA ENTERING DATA RESOURCEAPPLY AS CLOSE TO CAPTURE AS POSSIBLEVIOLATIONS ACTIONS DEFINEDVIOLATION NOTIFICATION NOTIFICATION DEFINEDDEFAULT VALUES SPECIFIED
PROACTIVE DATA QUALITY MANAGEMENT - SELF CORRECTING PROCESSRAPID DATA ERROR IDENTIFICATIONAPPLY TO ENTIRE DATA RESOURCEDEFAULT VALUES DOCUMENTED WHEN INSERTED
© 2005 by Michael H. Brackett
DATA DOCUMENTATION
ROBUST DATA DOCUMENTATIONDOCUMENTATION ABOUT THE DATA RESOURCE THAT IS COMPLETE, CORRECT, CURRENT, UNDERSTANDABLE, NON-REDUNDANT, READILY AVAILABLE, AND KNOWN TO EXIST.
GOOD PRACTICESDATA RESOURCE DATA CONCEPT
THE TERM META-DATA MISUSED AND ABUSED TO THE POINT THAT ITS MEANING IS UNCLEAR
META-DATA FIASCO UNFOLDINGMETA-META-DATA, META-META-META-DATA, ETC.
DATA RESOURCE DATA IS A MUCH BETTER TERMANY DATA NECESSARY FOR THOROUGHLY UNDERSTANDING, FORMALLY MANAGING, AND FULLY UTILIZING THE DATA RESOURCE TO SUPPORT THE BUSINESS INFORMATION DEMAND
DESIGNED AND MANAGED THE SAME AS ANY OTHER DATA - FINANCIAL DATA, CUSTOMER DATA, JUSTICE DATA, HUMAN RESOURCE DATA
SEGMENT OF THE ORGANIZATION’S DATA RESOURCE THE SAME AS ANY OTHER DATA
PART OF THE COMMON DATA ARCHITECTURE
DATA RESOURCE DATA DOCUMENT THE ENTIRE DATA RESOURCE!
© 2005 by Michael H. Brackett
DATA DOCUMENTATION
DATA RESOURCE DATA ASPECTSSEMANTIC DATA RESOURCE DATABUSINESS ASPECTTHE MEANING OF THE DATAHELP PEOPLE UNDERSTAND AND USE THE DATA RESOURCERELATIVELY DIFFICULT TO CAPTURE AND MAINTAIN
TECHNICAL DATA RESOURCE DATAPHYSICAL ASPECTPARAMETERS ABOUT THE DATA STORAGE AND DATA MANIPULATIONDATA ABOUT BUILDING, MANAGING, AND MAINTAINING DATABASESRELATIVELY EASY TO CAPTURE AND MAINTAIN
DATA RESOURCE DATA MUST INCLUDE BOTH SEMANTIC DATA AND TECHNICAL DATA!
© 2005 by Michael H. Brackett
DATA DOCUMENTATION
COMPLETE DATA DOCUMENTATIONINCLUDE SEMANTIC AND TECHNICAL DATA RESOURCE DATAINCLUDE ENTIRE SCOPE OF THE DATA RESOURCEINCLUDE ALL DATA RESOURCE COMPONENTS
CURRENT DATA DOCUMENTATIONDOCUMENTATION KEPT CURRENT WITH THE BUSINESSADEQUATELY REPRESENT HISTORICAL CHANGES IN THE BUSIENSS / DATA RESOURCE
UNDERSTANDABLE DATA DOCUMENTATIONUNDERSTANDABLE TO ALL AUDIENCESCORRECT DETAIL FOR INTENDED AUDIENCEAPPROPRIATE PRESENTATION
NON-REDUNDANT DATA DOCUMENTATIONONE SINGLE VERSION OF THE TRUTH FOR THE DATA RESOURCEDEVELOP WITHIN A COMMON DATA ARCHITECTURESAME CONCEPTS, PRINCIPLES, TECHNIQUES FOR DEVELOPING BUSINESS DATA
READILY AVAILABLEREADILY AVAILABLE TO ALL AUDIENCES - BUSINESS & TECHNICALEASILY ACCESSIBLE THROUGH BUSINESS APPLICATIONS
© 2005 by Michael H. Brackett
DATA DOCUMENTATION
KNOWN TO EXISTALL AUDIENCES MUST KNOW DATA DOCUMENTATION EXISTSCONSTANTLY MAKE PEOPLE AWARE THAT DATA DOCUMENTATION EXISTS
ANCILLARY DATA DOCUMENTATIONDATA SUBJECT THESAURUS - BUSINESS TERMS POINT TO DATA SUBJECTKEYWORD IN CONTEXT & KEY TERM OUT OF CONTEXT
BUSINESS GLOSSARYLIST OF TERMS AND ABBREVIATIONS USED IN THE BUSINESSBUSINSS TERMS AND ABBREVIATIONS OFTEN AS DISPARATE AS THE DATAHELPS PEOPLE UNDERSTAND THE BUSINESS AND FOCUS ON PREFERRED TERMS
© 2005 by Michael H. Brackett
DATA ORIENTATION
REASONABLE DATA ORIENTATIONA DATA ORIENTATION THAT IS PRIMARILY TOWARD THE BUSINESS AND SUPPORT OFBOTH THE CURRENT AND FUTURE BUSINESS INFORMATION DEMAND.
GOOD PRACTICESBUSINESS SUBJECT ORIENTATION
PRIMARY ORIENTATION TOWARD BUSINESS SUBJECTSBUSINESS OBJECTS AND BUSINESS EVENTS IN REAL WORLD
BUSINESS CLIENT ORIENTATIONDIRECT BUSINESS CLIENT INVOLVEMENT FOR BUSINESS KNOWLEDGECANNOT EXCLUDE BUSINESS KNOWLEDGECANNOT HAVE BUSINESS CLIENTS DRIVE DATABASE DESIGNFIND RIGHT MIX OF BUSINESS KNOWLEDGE AND TECHNICAL SKILLS
COOPERATIVE DEVELOPMENT OF A HIGH-QUALITY DATA RESOURCE!
FIVE-TIER CONCEPTBUILDS ON THE THREE-TIER CONCEPTADDS AN ANALYTICAL TIER AND A PREDICTIVE TIER
© 2005 by Michael H. Brackett
DATA ORIENTATION
DATA NORMALIZATIONEXPANDED PERSPECTIVEBRINGING DATA INTO NORMAL FORM FOR THE INTENDED PURPOSEOPERATIONAL DATA NORMALIZATIONANALYTICAL DATA NORMALIZATIONPREDICTIVE DATA NORMALIZATION
SINGLE ARCHITECTURE ORIENTATIONONE INTEGRATED ORGANIZATION-WIDE DATA ARCHITECTUREONE ARCHITECTURE FOR ALL FIVE TIERS AND ALL FIVE SCHEMACOMMON DATA ARCHITECTURE CONCEPT
SINGLE FACT ORIENTATIONSINGLE FACT DATA ATTRIBUTEBIRTH DATE & REASON FOR NO BIRTH DATE
SINGLE VALUE DATA ATTRIBUTESINGLE NAME PER DATA ATTRIBUTE
DATA ATTRIBUTE NORMALIZATIONSINGLE FACT OR GROUP OF CLOSELY RELATED FACTSSINGLE VALUE
© 2005 by Michael H. Brackett
DATA AVAILABILITY
ACCEPTABLE DATA AVAILABILITYENSURE THAT THE DATA ARE AVAILABLE TO MEET THE BUSINESS INFORMATION DEMANDWHILE PROPERLY PROTECTING AND SECURING THOSE DATA.
GOOD PRACTICESADEQUATE DATA ACCESSIBILITY
BALANCE BETWEEN TOO SECURE OR NOT SECURE ENOUGHPROTECTION FROM UNAUTHORIZED ACCESS, ALTERATION, OR DESTRUCTION
ADEQUATE DATA PROTECTIONREASONABLE PROTECTION AGAINST REASONABLE FAILURESREGULAR BACKUPS DEPENDING ON CRITICAL NATURE OF DATAPROCEDURES TO CONTINUE BUSINESS DURING FAILURE
ADEQUATE DATA RECOVERYRECOVER FROM FAILURE AS QUICKLY AND COMPLETELY AS POSSIBLEPROCEDURES TO BRING DATA RESOURCE CURRENT WITH THE BUSINESS
PROTECTED PRIVACY AND CONFIDENTIALITYPROTECT PERSON / ORGANIZATION’S RIGHT TO PRIVACY / CONFIDENTIALITYCONSTANTLY TRACK CURRENT LAWS AND REGULATIONS
APPROPRIATE DATA USEONGOING REVIEW OF THE USE OF DATA
© 2005 by Michael H. Brackett
DATA RESPONSIBILITY
ADEQUATE DATA RESPONSIBILITYDEFINE FORMAL RESPONSIBILITIES FOR MANAGING A SHARED DATA RESOURCE.
GOOD PRACTICESAUTHORIZED DATA STEWARDSHIP
DATA STEWARD - A PERSON WHO WATCHES OVER THE DATA AND ISRESPONSIBLE FOR THE WELFARE OF THE DATA RESOURCE AND ITS SUPPORTTO THE BUSINESS INFORMATION DEMAND
STRATEGIC LEVEL (EXECUTIVE LEVEL)LEGAL / FINANCIAL RESPONSIBILITY FOR A MAJOR SEGMENT OF THE DATA RESOURCESETS DIRECTIONS, ESTABLISHES PRIORITIES, COMMITS RESOURCESCOLLECTIVELY MANAGE THE ORGANIZATION’S DATA RESOURCE
DETAIL LEVEL (KNOWLEDGE WORKER)KNOWLEDGEABLE ABOUT THE DATA BY REASON OF INTIMIATE FAMILIARITY WITH DATAARCHITECTURAL RESPONSIBILITYDEVELOPS DATA ARCHITECTURE AND DATA RESOURCE DATANO DECISION MAKING AUTHORITY
TACTICAL LEVEL (LIAISON)LARGE 0R MULTI-NATIONAL ORGANIZATIONS FACE DATA GLOBALIZATION ISSUESNEED ADDITIONAL LEVEL OF STEWARDSHIPREPRESENT UNIQUENESS OF INDIVIDUAL DEPARTMENTS OR COUNTYS
© 2005 by Michael H. Brackett
DATA RESPONSIBILITY
REASONABLE MANAGEMENT PROCEDURESDEVELOPED BY DATA STEWARDSEQUIVALENT TO FINANCIAL, HUMAN RESOURCE, PROPERTY MANAGEMENTMUST BE REASONABLE - ENCOURAGE PARTICIPATIONMUST BE READILY AVAILABLE AND UNDERSTANDABLE
PROCEDURES YOU WOULD LIKE TO SEE IF YOU WERE ON THE RECEIVING END.
CENTRALIZED CONTROLRESULT FROM DATA STEWARDS AND MANAGEMENT PROCEDURESSINGLE COMMON DATA ARCHITECTURE WITH LOCAL IMPLEMENTATIONNOT A SINGLE ‘DATABASE IN THE SKY’
REVERSE OF TRADITIONAL APPROACHMANDATE CENTRALIZED CONTROLESTABLISH PROCEDURESSTEWARDS TO ENFORCE PROCEDURES
BEGIN THINKING GLOBALLY AND ACTING LOCALLY!
© 2005 by Michael H. Brackett
DATA VISION
EXPANDED DATA VISIONAN INTELLIGENT FORESIGHT ABOUT THE DATA RESOURCE THAT INCLUDES THE SCOPEOF THE DATA RESOURCE, ITS DEVELOPMENT DIRECTION, AND A PLANNIG HORIZON.
GOOD PRACTICESWIDER SCOPE
MUST ULTIMATELY INCLUDE ALL DATA AT AN ORGANIZATION’S DISPOSAL
NON-CRITICAL DATAHAVE SOME BUSINESS USEFULNESS - MUST ULTIMATELY BE MANAGED
NON-TABULAR DATADATA MEGATYPE - MAJOR GROUPING OF DATA BASED ON OVERALL STRUCTURE AND PHYSICAL MANGEMENT, SUCH AS SPATIAL, IMAGE, TEXTUAL, ETC.
BASE DATA TYPE - SPECIFIC FORM OF DATA WITHIN A DATA MEGATYPESUCH AS DATE, TEXT, INTEGER, ETC.
DISTINCT DATA TYPE - DATA UNIT OR STYLE WITHIN A BASE DATA TYPESUCH AS METERS / YARDS / INCHES OR POUNDS / MARKS / US DOLLARS
TABULAR / NON-TABULAR DATA OFTEN CONFUSED WITHSTRUCTURED / UNSTRUCTURED DATA!
© 2005 by Michael H. Brackett
DATA VISION
HISTORICAL DATAPROPERLY MANAGE TEMPORAL OR ‘TIME RELATIONAL’ DATA
OPERATIONAL DATA - SUBJECT ORIENTED, INTEGRATED, TIME CURRENT, VOLATILE DATAIN SUPPORT OF DAILY OPERATIONS AND OPERATIONAL DECISIONS.
EVALUATIONAL DATA - SUBJECT ORIENTED, INTEGRATED, TIME VARIANT, NON-VOLATILE DATAIN SUPPORT OF MANAGEMENT DECISION MAKING.
NON-AUTOMATED DATAINCLUDE IN SAME PRIORITIZATION AS AUTOMATED DATAOPENS UP WHOLE NEW HIDDEN DATA RESOURCE
REASONABLE DEVELOPMENT DIRECTIONPRIMARILY ON BUSINESS DIRECTION SECONDARILY ON DATABASE MANAGEMENT SYSTEM DIRECTION
REALISTIC PLANNING HORIZON
CHALLENGING YET ACHIEVABLESTRETCH THE IMAGINATION BUT NOT BE UNREALISTICMUST BE UNDERSTANDABLE AND ACHIEVABLEDIFFERENT HORIZONS FOR DIFFERENT AUDIENCES
COOPERATIVE ESTABLISHMENTESTABLISHED AND ACCEPTED COLLECTIVELY BY THE STAKEHOLDERS
© 2005 by Michael H. Brackett
DATA RECOGNITION
APPROPRIATE DATA RECOGNITIONRECOGNIZE THAT DATA ARE A CRITICAL RESOURCE AND IMPROVE THE QUALITY OF THAT CRITICAL RESOURCE TO MEET THE BUSINESS INFORMATION DEMAND
GOOD PRACTICESTARGET VESTED INTEREST
HIGHEST LEVEL IN ORGANIZATION WITH VESTED INTEREST IN DATA RESOURCEWORK FROM THERE THROUGH THE ORGANIZATIONTHIS IS HIGHEST PROBABILITY OF SUCCESSLEVEL VARIES FROM ONE ORGANIZATION TO ANOTHER
DIRECT BUSINESS INVOLVEMENTDIRECT INVOLVEMENT OF KNOWLEDGEABLE PEOPLETHE GREATER THE LIMITATION OF BUSINESS -- THE GREATER THE CHANCE OF FAILURE
THE GREATER THE INVOLVEMENT OF BUSINESSTHE GREATER THE CHANCE OF SUCCESS!
TAP THE KNOWLEDGE BASEFIND PEOPLE WITH KNOWLEDGE OF THE DATA -- BUSINESS OR INFORMATION TECHNOLOGYUSE THEM AS DETAIL DATA STEWARDS OR CONTRIBUTORS
© 2005 by Michael H. Brackett
DATA RECOGNITION
START WITHIN CURRENT BUDGETCURRENT BUDGET INITIATIVES GET RECOGNIZEDSTART SMALL AND GROW AS THE RECOGNITION GROWS
INCREMENTALLY COST EFFECTIVE APPROACHLONG-TERM BENEFITS HAS LOST ITS MEANINGSHORT-TERM BENEFITS LOSING ITS MEANING
INCREMENTALLY COST EFFECTIVE -- LAY A SUCCESS ON THE TABLE, GET MORE RESOURCESLAY ANOTHER SUCCESS ON THE TABLE, AND SO ON.
PROOF POSITIVE PERSPECTIVEGO TO MANAGEMENT WITH A PROOF-POSITIVE PERSPECTIVEGAIN RESOURCES TO CONTINUE SUCCESSFAR BETTER THAN A ‘TRUST ME’ REQUEST FOR RESOURCES
THERE IS A HIGHER RISK -- BUT THE REWARDS FAR OUTWEIGH THE RISKS!
BE OPPORTUNISTICSEIZE EVERY OPPORTUNITY TO DELIVER THE MESSAGESIZE OF OPPORTUNITY NOT IMPORTANT -- GETTING THE MESSAGE OUT IS IMPORTANTAVOID EXCESSIVE PILOT STUDIES AND PROOF OF CONCEPTSAVOID PRECISE RIGID PLANS
© 2005 by Michael H. Brackett
DATA RECOGNITION
BUILD ON LESSONS LEARNEDEVERY PROJECT HAS SUCCESSES AND FAILURESSTOPPING DATA DISPARITY IS A DISCOVERY PROCESSMANAGEMENT MUST ACCEPT CONSTRUCTIVE FAILURES
NO BLAME - NO WHITEWASH ATTITUDETHE CURRENT SITUATION EXISTS -- THAT IS A FACTBLAME POLARIZES AND ALIENAGES PEOPLE -- DEFEATS THE INITIATIVECOVERING IT UP DELAYS ANY INITIATIVE FOR IMPROVEMENT
NO UNNECESSARY JUSTIFICATIONELIMINATE THE REQUIREMENT FOR EXTENSIVE JUSTIFICATION TO IMPROVE QUALITYTHE NEED FOR IMPROVED DATA RESOURCE QUALITY SHOULD BE A TRUISM
IF ANYTHNG -- A JUSTIFICATION SHOULD BE REQUIRED TO CONTINUERUINING THE QUALITY OF A CRITICAL RESOURCE!!
© 2005 by Michael H. Brackett
DATA RESOURCE TRANSITION
DATA RESOURCE TRANSITIONFORMALLY MOVING FROM A DISPARATE DATA RESOURCE TO A COMPARATE DATARESOURCE WITHIN THE COMMON DATA ARCHITECTURE
RESOLVES THE EXISTING DATA DISPARITYNOT A MIGRATION - IMPLIES WANDERING OR PERIODIC RETURN TO DISPARITYTRANSITION THROUGH FORMAL TRANSITION STATES
DATA RESOURCE TRANSITION PROCESSDISCOVERY PROCESSREQUIRES THOUGHT, ANALYSIS, INTUITION, PERCEPTION, AND SOME LUCKEVOLUTIONARY PROCESS DUE TO UNCERTAINTY
FORMALIZETHE UNDERSTANDING OF DISPARATE DATAINTEGRATE DISPARATE DATA
AVOID SUCK-AND-SQUIRT APPROACHESAVOID BRUTE-FORCE-PHYSICAL APPROACHES
DATA RESOURCE TRANSITION IS A FORMAL PROCESS!
© 2005 by Michael H. Brackett
DATA RESOURCE TRANSITION
DATA RESOURCE TRANSITION STATES
DISPARATE DATA RESOURCE - CURRENT STATEDATA NOT WELL UNDERSTOOD
FORMAL DATA RESOURCE - NECESSARY STATENECESSARY TO THOROUGHLY UNDERSTAND DISPARATE DATA
VIRTUAL DATA RESOURCE - DESIRED STATEREAL-TIME PRODUCTION TRANSFORMATION OF DISPARATE DATA
COMPARATE DATA RESOURCE - IDEAL STATEPERMANENT TRANSFORMATION OF DISPARATE DATA
Enterprise Data Resource
Common Data Architecture
DisparateData Resource
FormalData Resource
VirtualData Resource
ComparateData Resource
Understand DataWithin Common Context
Real-TimeTransformation
PermanentTransformation
© 2005 by Michael H. Brackett
FORMAL DATA RESOURCE
FORMAL DATA RESOURCEDATA INVENTORY
INVENTORY EXISTING DISPARATE DATARAISES AWARENESS OF THE DATA THAT EXISTSOLVES THE FIRST PROBLEM WITH DISPARATE DATA
DATA CROSS REFERENCECROSS-REFERENCE DISPARATE DATA TO COMMON DATA ARCHITECTUREPROVIDES AN UNDERSTANDING OF DISPARATE DATA IN A COMMON CONTEXTSOLVES THE SECOND PROBLEM WITH DISPARATE DATA
DATA VARIABILITYIDENTIFY DATA VARIABILITYDESIGNATE PREFERRED DATA VARIATIONSDEVELOP DATA TRANSLATION SCHEMESPREPARATION TO SOLVE THE THIRD PROBLEM WITH DISPARATE DATA
DATA REDUNDANCYIDENTIFY DATA REDUNDANCYDESIGNATE PREFERRED DATA SOURCESPREPARATION TO SOLVE THE FOURTH PROBLEM WITH DISPARATE DATA
DEVELOPING A FORMAL DATA RESOURCE IS NON-DESTRUCTIVE!
© 2005 by Michael H. Brackett
FORMAL DATA RESOURCE
ENTERPRISE DATA ARCHITECTUREREMEMBER - THE ENTERPRISE DATA ARCHITECTURE REPRESENTS THE COMPARATE DATA RESOURCE
THE PREFERRED DESIGNATIONS DEFINE THE COMPARATE DATA RESOURCEPREFERRED DATA SOURCESPREFERRED DATA VARIAITONSPREFERRED DATA INTEGRITY RULESDATA TRANSLATION SCHEMES
THESE SET THE STAGE FOR TRANSFORMING DISPARTE DATA TO COMPARATE DATA
THE PREFERRED DESIGNATIONS DEFINE THE ENTERPRISE DATA ARCHITECTURE!
© 2005 by Michael H. Brackett
DATA TRANSFORMATION
PROBLEMSMANY ORGANIZATIONS NOT FORMALLY INTEGRATING THEIR DATAUSUALLY INCOMPLETE / INCONSISTENT DATA INTEGRATIONIDENTIFYING A SINGLE SYSTEM OF REFERENCE USUALLY NOT VALIDUSING SUCK-AND-SQUIRT METHODS TO OBTAIN DATA USUALLY DON’T WORKUSING BRUTE-FORCE-PHYSICAL APPROACHESMORE THAN SIMPLE EXTRACT - TRANSFORM - LOADMORE THAN MINOR DATA CLEANISINGRESULT IS LOW-QUALITY DATA
APPROACHFORMAL DATA TRANSFORMATION WITHIN COMMON DATA ARCHITECTUREBASED ON FORMAL DATA RESOURCE - THOROUGH UNDERSTANDING OF DATAREQUIRES ROBUST DATA TRANSFORMATIONNOT A TRIVIAL TASK - BUT NOT IMPOSSIBLE EITHER IGNORED IN MANY METHODS
DATA INTEGRATION MUST BE BASED ON THE FORMAL DATA RESOURCE!
© 2005 by Michael H. Brackett
DATA TRANSFORMATION
VIRTUAL / COMPARATE DATA RESOURCEEXTRACT - THREE STEPS
IDENTIFYING AND EXTRACTING THE BEST DISPARATE DATA TO A DATA DEPOTISOLATED FROM SOURCE AND TARGET DATAPREPARATION FOR DATA TRANSFORMATION
TRANSFORM - FIVE STEPSTRANSFORMING THE DISPARATE DATA TO COMPARATE DATAUSING FORMAL DATA TRANSFORMATION RULESACTUALLY CHANGING THE DATA
LOAD - THREE STEPSEDITING THE COMPARATE DATALOADING THE COMPARATE DATA FROM A DATA DEPOTBUILDING THE COMPARATE DATA RESOURCE
© 2005 by Michael H. Brackett
DATA TRANSFORMATION
DATA TRANSFORMATION PROCESS
IdentifyTarget Data
IdentifySource Data
ExtractData
Data Reconstruction
DataTranslation
DataRecasting
DataIntegrity
DataLoading
DataReview
DataRestructuring
DataDerivation
Data Extract
Data Transform
Data Load
© 2005 by Michael H. Brackett
CULTURAL CONSIDERATIONS
A SHARABLE DATA RESOURCEGETTING PEOPLE TO INTERACT AND SHARE
AWARE OF EXISTING DATA
THOROUGHLY UNDERSTAND DATA
USE DATA TO SUPPORT THEIR BUSINESS ACTIVITIES
REAL DATA SHARING INCENTIVESMAKE EASY TO MEET BUSINESS NEEDSMAKE EASY TO CROSS ORGANIZATIONAL BOUNDARIES
WHEN THE PAIN OF NOT MEETING BUSINESS NEEDSEXCEEDS THE PAIN OF CROSSING ORGANIZATIONAL BOUNDARIES
PEOPLE WILL INTERACT AND SHARE!
© 2005 by Michael H. Brackett
CULTURAL CONSIDERATIONS
DATA SHARING - DATA QUALITY - DATA INTEGRATION CYCLEWHEN PEOPLE UNDERSTAND DATA - THEY SHARE THOSE DATAWHEN PEOPLE SHARE DATA - THE DATA QUALITY IMPROVESWHEN DATA QUALITY IMPROVES - THE DATA ARE INTEGRATEDAND THE CYCLE KEEPS GOING
THIS IS NOT ROCKET SCIENCE!
Data QualityImproves
People GetInvolved
Data IntegrationProgresses
Data SharingIncreases
Data AreUnderstood
© 2005 by Michael H. Brackett
CULTURAL CONSIDERATIONS
A PEOPLE ORIENTATIONUNCERTAINTY
HELP RESOLVE UNCERTAINTYREDUCE RESISTANCE TO CHANGEMANAGE EXPECTATIONS
WILLINGNESS TO CHANGEMOST PEOPLE WILLING TO CHANGETHEY JUST DON’T KNOW HOWCONCERNED ABOUT IMPACT TO BUSINESS
RESISTANCE TO CHANGEPEOPLE UNSURE OF NEW PARADIGMCOMFORTABLE WITH EXISTING PARADIGMCONCERNED ABOUT PAST CURE-ALL FAILURESNO TIME TO STOP THE BUSINESS TO CHANGE
SURFACE DIFFERENCESDOCUMENT DIFFERENT DEFINITIONSDON’T ATTEMPT TO RESOLVE DIFFERENCES
PEOPLE DON’T MIND CHANGING!PEOPLE DO MIND BEING CHANGED!
© 2005 by Michael H. Brackett
CULTURAL CONSIDERATIONS
A BUSINESS ORIENTATIONFOCUS ON THE BUSINENSS
BASED ON BUSINESS PLAN AND STRATEGIES
BASED ON ENTERPRISE’S PERCEPTION OF BUSINESS WORLD
CRITICAL AREA APPROACHIDENTIFY CRITICAL BUSINESS AREAS
DETERMINE DATA NEEDED FOR THOSE AREAS
IDENTIFY DATA THAT ALREADY EXIST
IDENTIFY DATA THAT NEED TO BE ACQUIRED
DEVELOP COMPARATE DATA FOR THOSE CRITICAL AREAS
CLIENT FOCUSED APPROACHORIENT THE PROCESS TO THE CLIENT’S WAY OF THINKING
DRAW THE CLIENT INTO THE PROCESS
TAP THE CLIENT’S KNOWLEDGE BASE
DIRECT CLIENT INVOLVEMENTINVOLVEMENT LEADS TO COMMITMENT
COMMITMENT LEADS TO ACCEPTANCE
ACCEPTANCE LEADS TO SUCCESS
© 2005 by Michael H. Brackett
CULTURAL CONSIDERATIONS
SUCCESS MOTIVATIONSUCCESS IS CONTAGIOUS
ORIENT TOWARD CONTINUED SUCCESSESTHRIVE ON LESSONS LEARNED
INCREMENTALLY COST EFFECTIVELONG TERM BENEFITS HAS LOST ITS PUNCH
SHORT TERM BENEFITS BEGINNING TO LOSE ITS PUNCH
INCREMENTALLY COST EFFECTIVE IS A GOOD TERM
AVOID MANDATESMANDATES DO NOT WORK
IMPLY COMPLIANCE, ENFORCEMENT, PUNISHMENT
CREATES A WIN-LOSE SITUATION
ESTABLISH GUIDELINES GAIN CONSENSUS AND ACCEPTANCE
EVOLVE WITH TECHNOLOGY
DESIRED APPROACHEASIEST ROUTE TO FOLLOWASSURE SUCCESS
CREATE WIN - WIN SITUATION!
© 2005 by Michael H. Brackett
CONCLUSION
ULTIMATE DATA RESOURCE QUALITY IS STABILITY ACROSSCHANGING BUSINESS STRATEGIES & INFORMATION NEEDSCHANGING TECHNOLOGY
STABILITY ACHIEVED BY ESTABLISHING A COMMON DATA ARCHITECTUREHALTING THE CONTINUED DATA DISPARITYRESOLVING EXISTING DATA DISPARITY
NO SILVER BULLETSATTEMPT TO ACHIEVE SOME GAIN WITHOUT ANY PAINUSUALLY ENDURE CONSIDERABLE PAIN WITH MINIMAL GAIN
DON’T DELAYNEED NO JUSTIFICATION TO IMPROVE DATA RESOURCE QUALITYCONCEPTS, PRINCIPLES, & TECHNIQUES ARE AVAILABLETHE SITUATION IS ONLY GETTING WORSE
© 2005 by Michael H. Brackett
PRESENTER’S BIBLIOGRAPHY
DEVELOPING DATA STRUCTURED INFORMATION SYSTEMSKEN ORR & ASSOCIATES, 1984
DEVELOPING DATA STRUCTURED DATABASESPRENTICE HALL, 1987
PRACTICAL DATA DESIGNPRENTICE HALL, 1990
DATA SHARING USING A COMMON DATA ARCHITECTUREJOHN WILEY & SONS, 1994
THE DATA WAREHOUSE CHALLENGE: TAMING DATA CHAOSJOHN WILEY & SONS, 1996
DATA RESOURCE QUALITY: TURNING BAD HABITS INTO GOOD PRACTICESADDISON WESLEY, 2000
DATA RESOURCE INTEGRATION: UNDERSTANDING & RESOLVING DATA DISPARITYIN PROGRESS, NO PUBLISHER OR DUE DATE
DATA RULES: KEY TO DATA RESOURCE QUALITYIN PROGRESS, NO PUBLISHER OR DUE DATE
CONSULT PRESENTER’S WEB PAGE FOR ADDITIONAL DETAILS