data administration
DESCRIPTION
Data Administration. Bad administration, to be sure, can destroy good policy; but good administration can never save bad policy Adlai Stevenson, 1952. Data administration. Data are the lifeblood of organizations Data need to be managed - PowerPoint PPT PresentationTRANSCRIPT
Data Administration
Bad administration, to be sure, can destroy good policy; but good
administration can never save bad policy
Adlai Stevenson, 1952
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Data administration
Data are the lifeblood of organizationsData need to be managedData administration is concerned with the management of organizational memories
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Data are generated by stakeholders
EmployeesCustomersShareholdersInvestorsSuppliersGovernment
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Data management problems
RedundancyInconsistent representationsMultiple definitions of data itemsEssential data missingInaccurate or incomplete dataUncaptured dataData that cannot be located
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Goals of data management
Enable users to access the data they need in the most suitable formatMaintain data integrity
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Management of the database environment
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Components of the database environment
DatabasesUser interfaceData dictionaryExternal databases
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Data administrationSystem
Environment wide management issuesPlanningData standards and policyData integrityResolving data conflictsManaging the DBMSData dictionaryBenchmarking
ProjectDefining user requirementsData modelingTraining and consultingMonitoring integrity and usageChange management
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Data administration functions and roles
A function is a set of activities to be performedIndividuals are assigned roles to perform certain activitiesData administration functions may be performed by a:
Data administratorData administration staffDatabase developmentDatabase consultantDatabase analyst
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Data steward
Responsible for managing all corporate data for a critical business entity or productCuts across functional boundariesAligns data management with organizational goals
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Database use levels
PersonalWorkgroupOrganizationalMore users means greater complexity
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Personal databases
Notebook computersPersonal digital assistants (PDAs)Personal information managers (PIMs)Cell phonesMusic players (iPod)Information appliances
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Workgroup and organizational databases
Shared by many peopleGreater complexityRequire more planning and co-ordination than personal databases
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System level data administration
PlanningDevelopment of data standards and policiesData integrityData conflict resolutionManaging the DBMSEstablishing and maintaining the Data DictionarySelection of hardware and softwareBenchmarkingManaging external databasesInternal marketing
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KonflikthåndteringEksempel: De som sitter i kassa blir bedt om å spørre etter bydel og registrere bydel, antatt alder og kjønn på den som kjøper, slik at markedsføring kan skreddersysProblem: De som sitter i kassa gjør en dårlig jobb – registrering mangler eller er feil i mange tilfeller Diskusjon: Hvordan kan problemet løses
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Selection of hardware and software
How many users will simultaneously access the database? Will the database need to be geographically distributed? What is the maximum size of the database? How many transactions per second can the DBMS handle? What kind of support for on-line transaction processing is available? What are the initial and ongoing costs of using the product?What is the extent of training required, will it be provided, and what are the associated costs?
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Benchmarking
TPC-CBenchmarking of TPS
TPC-HBenchmarking of ad-hoc decision support
TPC-RBenchmarking of standard decision support
TPC-WBenchmarking of Web sites
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Project level data administration functions
Meeting the needs of individual applications and usersSupport and development of a specific database system
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Systems Development Life Cycle
Application Development Life Cycle (ADLC)
Database Development Life Cycle (DDLC)
Project planning Project planning
Requirements definition Requirements definition
Application design Database design
Application construction
Application testing Database testing
Application implementation Database implementation
Operations Database usage
Maintenance Database evolution
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Strategies for system development
Database and applications developed independentlyApplications developed for existing databasesDatabase and application development proceed simultaneously
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Development roles
Database Development Phase
Database Developer
Data Administrator
User
Project planning Does Consults Provides information
Requirements definition
Does Consults Provides requirements
Database design Does Consults
Data integrity
Validates data models
Database testing System and user testing
Consults
Data integrity
Does user testing
Database implementation
System related activities
Consults
Data integrity
Does user activities
Database usage Consults Data integrity monitoring
Uses
Database evolution Does Change control Provides additional requirements
Database developmen
t cycle
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Data administration interfaces
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Data administration interfaces
ManagementSets the agenda and goals
UsersSeek satisfaction of goals
DevelopmentCo-operation
Computer operationsEstablishing and monitoring procedures for operating databases
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Data administration toolsDatabase development phase
Data Dictionary (DD) Database Management System (DBMS)
Performance monitoring
Case tools
1. Project planning Document Data mapDesign aid
Estimation tools
2. Requirements definition
Document Design aid DocumentDesign aid
3. Database design DocumentDesign aidData mapSchema generator
DocumentDesign aidData map
4.Database testing Data mapDesign aidSchema generator
Define, create, test, data integrity
Impact analysis Test data generatorDesign aid
5.Database implementation
DocumentChange control
Data integrityImplement Design
MonitorTune
6. Database use Document Data mapSchema generatorChange control
Provide tools for retrieval and updateEnforce integrity controls and procedures
Monitor Tune
7. Database evolution DocumentData mapChange control
Redefine Impact analysis
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Data dictionaryAll columns – name, type, format, validation, constraintsAll relationships All databasesAll tablesAll indexesAll users and their authorisationsAll programs that access the database and what they access – SQL queries...
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Use of the data dictionary
Documentation supportData mapsDesign aidSchema generationChange control
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Data integrationLack of data integration is a common problemExamples
Different identifiers for the same instance of an entityThe same data stored in multiple systemsRelated data stored in different databasesDifferent methods of calculation for the same business indicator in different systems
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Data integrationRed division Blue division
partnumber(code for green widget)
27 27
customerid(code for UPS)
53 53
Definition of salesdate
The date the customer signs the
order
The date the customer signs the
order
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Lack of data integrationRed division Blue division
partnumber(code for green widget)
27 10056
customerid(code for UPS)
53 613
Definition of salesdate
The date the customer signs the
order
The date the
customer receives the
order
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Goals of data integrationA standard meaning and format for all data elementsA standard format for each and every data elementA standard coding systemA standard measurement systemA single corporate data model for each major business entity
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Data integration strategiesEnvironmental
turbulenceHigh
Low Moderate
LowModerate High
Low High
Unit interdependence
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Organizing the data administration function
Creation of the functionSelecting staff and assigning rolesLocating the function
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Data administration reporting to the CIO
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Data administration reporting to Support Services
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Matrix structure for data administration
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Data administration as a staff function
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Decentralized data administration
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Conclusion
Data administration is Growing in complexityCritical to the success of most organizationsGenerally underrated in importance