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Test your basic knowledge |
DMBOK
Start Test
Study First
Subjects
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certifications
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dmbok
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
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Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Expert technical custodians of data assets
Reference and Master Data Management
Data Model/Design quality management
Metadata Management Functions
Data Management Professionals role
2. Information mgt - Enterprise Information mgt - Enterprise Data mgt - Data Resource mgt - Information Resource mgt - Information Asset mgt
Affiliation Relationship
Data asset valuation
Data Management Synonyms
Data Strategy
3. Process - Tools - and Techniques for Organizing - Categorizing and Structuring access to Information Content
Metadata for unstructured data types
Knowledge management
Data Quality expectations
Content Management
4. High level perspective on a subject area of importance to the business.
Conceptual Data Models
Data Management Services(GAR MQD IP)
Data security guiding principles
AAAA
5. Data specifically constructed for query and analysis
Content Mgt Functions
Kimball DW Approach
Data Access Services
Master Data
6. Plan - Specify - Enable - Create - Use - Retrieve - Purge
Rules defined by Data Governance (PSP MBN DR )
Detailed Data Design
Asset
Data Lifecycle complete
7. Write everything down - Keep everything - Automate - Purpose (Why?) for each task - Don't panic - Business interest - Collaborate
Data governance programScope elements
Data Stewards
Data Ops Mgt - Guiding Principles
DOLAP
8. Improve data Quality and Integration... Provide onsolidated 360 degree view of information about important business entities (Party - Product - Location - Financial Structure).
Detailed Data Design
Reference Data Metadata may include...
Kimball DW Approach
Drivers for Reference and Master Data Management
9. Technology specific - denormalized for performance - Surrogate keys - Indexing - Views -
Party master data
Data governance programScope elements
Logical Data Model
Physical Data Models
10. Data Strategy and Policies - Standards and Architecture - Regulatory Compliance - Issue management - PROJECTS - Valuation - Communication
Asset
Knowledge management
Data Quality tools
Data governance programScope elements
11. Sarbanes-Oxley - financial reporting and auditing - HIPPA - privacy and security of health information - Basel II - Solvency II - PCI-DSS - Payment Card Industry Data Security Standards
Regulatory Compliance examples
Metadata Architecture types
Data Management Shared responsibility
Data Quality Management Functions
12. SOA - ETL - Replication - Message Brokers
Data Access Services
Ten Functions of Data Management
Document vs. Content
Information
13. Policies - Procedures - Standards - Issues - Projects - Services - Quality Data and Info - Recognized Data Value
Reference Data Metadata may include...
Data Management Professionals role
Logical Data Model
Data Governance Deliverables (PPS IP SQV)
14. Security - DB Recovery and Retention - Access and Use of Externally Sourced Data - Sharingdata internally and externally - DW/BI policies
Data Quality expectations
Strategic goals of data management
Data Management Professionals role
Enterprise Data Warehouse
15. Source Systems - Staging Area - Data Presentation Area/DW - Data Access Tools
Data Quality Management Functions
Data Quality tools
Procedural DBA
Kimball key components
16. G ADO SQ RIDM - Governance - Architecture - Development - Operations - Security - Quality - Reference/Master Data Mgt - DW/Business Intelligence - Document and Content Management - Metadata Management.
Data Management Functions
Data Management Synonyms
Kimball DW Approach
Causes for Performance problems
17. RAS - ICIM - DR [Requirements - Architecture - Standards] - [Implement Managed Metadata Environment Capture Metadata - Integrate Metadata - Metrics on Metadata[ - [Deliver Metadata - Report on Metadata]
Metadata Management Functions
Conceptual Data Models
Data Stewardship
Knowledge management
18. CRUD matrices that map data responsibilities across bus process - applications - roles - and organizations. - RACI matrix with clearn accountability and ownership.
ROLAP
Data Ops Mgt has 2 Subfunctions
Data Lifecycle Simple
Data Security in an outsourced wolrd
19. Data Architect - Business Process Analyst- Chief Knowledge Officer (CKO) - IT Auditor - Government and Regulatory Bodies
Data Quality Management lifecycle
Party master data
Examples of individual roles participating in Data Mgt
Data Model/Design quality management
20. Responsible Trustee of data - Understand and Comply with Regulations- Define data security Reqts Collaboratively - ID detailed application security reqts in each app dev project - Every user acct. has password - Use Role Groups- Formally track/approv
Data Quality tools
Data Management Functions
Data security guiding principles
Information
21. Data in context. Business meaning - Format of data presentation - Timeframe - Relevance of data for a given usage.
Data Strategy Deliverables
Business Intelligence
Data Warehouse primary components
Information
22. 1. Integrated Decision Support Database 2. All the software used to collect - cleanse - transform - store data
Data Development Activities (MDQI)
Data Quality Dimensions
Data Warehouse primary components
AAAA
23. Any file or record
Detailed Data Design
Components of Data Strategy (VCP GMO RIRS)
Document
Data Governance (EAC DMA)
24. PPTIER Profiling - Parsing/Standardization - Transformation - Identity Resolution and Mapping - Enhancement - Reporting
Data Quality tools
Business Intelligence
Data
Physical Data Models
25. 1. Data Mgt Service orgs (EIM COE) 2. Data Governance Council 3. Data Stewardship Steering Committee 4. Data Stewardship Teams 5. Data Governance Office
Physical Data Models
Data Ops Mgt - Guiding Principles
Types of Data Management Organizations
HOLAP
26. Meaning and purpose of each reference data value domain - Reference tables and databases where the reference data appears. - Source of the data in each table. - Version currently available. - When data was last updated. - How the data in each table i
Data Ops Mgt has 2 Subfunctions
Reference Data Metadata may include...
Data Management Shared responsibility
Examples of individual roles participating in Data Mgt
27. Responsible for development and support of procedural logic controlled and executed by the DBMS. Triggers - sprocs - functions.
Inmon DW Approach
Procedural DBA
Reference Data Management
Regulatory Compliance examples
28. Responsibility for a Specific Database(s) in all of its environments - rather than database System administration.
Data governance like real Government
Goals of DMBOK
Types of Data Management Organizations
Application DBA
29. Understand info Needs of enterprise and its stakeholders. - Capture - store - protect - and ensure integrity of Data Assets. - Continually improve Quality of data and information. - Ensure Privacy and Confidentiality - Maximize Effective use and VALU
Regulatory Compliance examples
Hierarchical Relationships
Strategic goals of data management
Data asset valuation
30. Formal accountability for business responsibilities ensuring effective control and use of data assets.
Data Stewardship
Physical Data Models
To share consistent Reference and Master data - orgs need to understand...
Goals of DMBOK
31. Stored in multidimensional data store
Reference and Master Data Management
MOLAP
Data Quality Dimensions
ROLAP
32. Information in perspective - integrated into a viewpoint based on the recognition of Patterns - trnends - assumptions - etc.
Causes for Performance problems
Data Stewardship
Knowledge
Reference Data Management
33. Short statements of Management Intent and fundamental Rules governing creation - acquisition - integrity - security - quality - and use of data and information. Describe WHATs - and What NOTs; do not describe HOWs.
Causes for Performance problems
Data Policies
Data asset valuation
DMBOK Recurring Themes
34. 1. Data and info are valuable enterprise ASSETs 2. Manage data/info carefully - like any other asset - by ensuring Quality - Security - Integrity - Protection - Availability - Understanding - and Effective Use. 3. Share responsibility between busines
Data Quality Management Functions
Data Development Activities (MDQI)
Guiding Principles of data management
Data Governance Deliverables (PPS IP SQV)
35. Data stored in Relational DB store
Data Quality Management Functions
Data asset valuation
Application DBA
ROLAP
36. (GADO SQ RIDM) 1. Governance 2. Architecture Management 3. Development 4. Operations Management 5. Security Management 6. Quality Management 7. Reference/Master Data Management 8. Data Warehousing/Business Intelligence 9. Document and Content Manage
Ten Functions of Data Management
Inmon DW Approach
Data asset valuation
Data Lifecycle Simple
37. Ongoing Reconciliation and Maintenance of reference and master data.
Master Data
Data Management Functions
Data Governance (EAC DMA)
Reference and Master Data Management
38. ETL Source to target mappings
Data Management Shared responsibility
Data Integration Services
Data Development Activities (MDQI)
Physical Data Models
39. BTPD Business (Definitions - rules - data lineage - quality statements - report lists - etc.) - Targetd at Business - Technical and operational (Information about SYSTEMS. DBs - column names - files - etls - etc) - Targeted at IT Operations users' n
Types of Metadata
Data Stewards
Data Ops Mgt has 2 Subfunctions
Semantic Modeling
40. DSA - Descriptive metadata (Catalog information - thesauri keyword terms) - Structural metadata (Dublin core - field structures - XML schema) - ADMINISTRATIVE metadata (Source - integration/update schedule - access rights - page relationships)
Drivers for Reference and Master Data Management
Metadata for unstructured data types
Data Management Shared responsibility
ROLAP
41. Type of model that represents a set of concepts and their relationships within a domain.
Data Quality tools
Data Management Shared responsibility
Ontology
Content Management
42. Vision - business case - guiding principles - long-term goal of Data Management - Measures of success - SMART program Objectives - descriptions of Roles - description of INITIATIVES (projects) - ROADMAP - boundaries of SCOPE.
Data Operations Mgt
Components of Data Strategy (VCP GMO RIRS)
Data Management Functions
Data Management
43. Document mgt- not concerned with insides of the file. - Content mgt - looks at inside of file and tries to identify the content.
Data governance like real Government
Reference Data Management
Master Data
Document vs. Content
44. 1. Modeling - Analysis - Design (Reqts - Conc - Log - Phys Models) 2. Detailed Data Design (Phys DBs - Info Products - Access - Integration Services) 3. Quality Management (Modeling/Design Standards - Review Models - Versioning/Integration of Models)
Data Development Activities (MDQI)
Data Quality expectations
DM Function Context Diagram overview (DG - ISP - T - DCM)
Asset
45. Modeling and design standards
Data Model/Design quality management
Reference Data Management
Data Governance (EAC DMA)
Inmon DW Approach
46. Virtual OLAP cube available as proprietary function of a classic relational database
DOLAP
Data Stewards
Data Governance (EAC DMA)
Data Lifecycle Simple
47. Control COST of data mgt. - Promote wider understanding of value of data assets. - Manage info consistently across enterprise - Align data mgt efforts and technology with Business Needs.
Physical Data Models
Non-strategic goals of data management
Data Quality Management lifecycle
Data Lifecycle Simple
48. Control over defined domain values - i.e. Vocabularies.
Reference Data Management
Data Operations Mgt
Data Integration Services
Metadata Management Functions
49. ODS - Current-valued - volatile data for operational reporting needs - DW - Historical - non-volatile data for single source of integrated data for corporation - DM - DSS for a department analytic need
Common Activity Groups for DM Functions (PDCO)
MOLAP
Inmon ODS - DW - DM distinction
Data asset valuation
50. Knowledge modeling. Ontology is a semantic model that describes Knowledge.
Enterprise Data Warehouse
Semantic Modeling
Data
Data Quality expectations