Test your basic knowledge |

Subjects : certifications, dmbok
Instructions:
  • Answer 50 questions in 15 minutes.
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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. Stored in multidimensional data store






2. Often formed between vocabulary terms - either as a KIND-OF or a PART-OF relationship.






3. Technology specific - denormalized for performance - Surrogate keys - Indexing - Views -






4. 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)






5. Centralized - gather and store centrally - periodic batch updates - Distributed - Query it in realtime from source - Hybrid - Header/common info stored centrally - more detailed info gathered in realtime from source






6. More detailed than Conceptual Data Model - adding: Normalization - Abstraction - Still technology independent.






7. GADR PTO "Gatter Riptoe" - Goals/Principles - Activities - Deliverables - Roles - Practices - Technology - Org/Culture






8. Improve data Quality and Integration... Provide onsolidated 360 degree view of information about important business entities (Party - Product - Location - Financial Structure).






9. Control over defined domain values - i.e. Vocabularies.






10. Expert technical custodians of data assets






11. Information in perspective - integrated into a viewpoint based on the recognition of Patterns - trnends - assumptions - etc.






12. Plan - Specify - Enable - Create - Use - Retrieve - Purge






13. Database Support and Data Technology Management






14. Establishment and maintenance of Relationships between master data records.






15. 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.






16. Responsibility for a Specific Database(s) in all of its environments - rather than database System administration.






17. 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






18. 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.






19. PIBRA Plan - Implement Doc/Record Mgt System - Backup - Retain - Audit






20. Centralized Data Warehouse designed to serve the BI needs of the entire organization. Adheres to the Enterprise Data Model (EDM).






21. 1. Data Mgt Service orgs (EIM COE) 2. Data Governance Council 3. Data Stewardship Steering Committee 4. Data Stewardship Teams 5. Data Governance Office






22. FDPPOS - Functions - Definitions - Principles - Practices - Organization - Scope






23. Virtual OLAP cube available as proprietary function of a classic relational database






24. Authentication - User is who they say they are. - Authorization - List of privileges that a user has to data - Access - Enable privileges in a timely manner - Auditing - Review security actions and user activity to ensure compliance






25. Formal accountability for business responsibilities ensuring effective control and use of data assets.






26. PPPDMA Plan - assess scope of known issues - Deploy - profile the data - and employ inspections and monitors - Monitor - actively monitor data quality against defined business rules - Act - Take action to address and resolve emerging issues






27. CRUD matrices that map data responsibilities across bus process - applications - roles - and organizations. - RACI matrix with clearn accountability and ownership.






28. Query - analysis and reporting off of the DW.






29. Policies - Procedures - Standards - Issues - Projects - Services - Quality Data and Info - Recognized Data Value






30. 1. Integrated Decision Support Database 2. All the software used to collect - cleanse - transform - store data






31. Location REFERENCE data includes geopolitical data - countries - states - provinces - counties...Location MASTER data includes business party addresses - geographic positioning coordinates - etc.






32. WHO needs WHAT info? - What data is available from different sources? - How does data from different sources DIFFER? - How can inconsistencies be RECONCILED? - How should most valid values be SHARED effectively and efficiently?






33. 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






34. RAS - ICIM - DR [Requirements - Architecture - Standards] - [Implement Managed Metadata Environment Capture Metadata - Integrate Metadata - Metrics on Metadata[ - [Deliver Metadata - Report on Metadata]






35. (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






36. Type of model that represents a set of concepts and their relationships within a domain.






37. State names - codes - MedDRA code - WHO Drug Code






38. ERP






39. 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






40. The Exercise of Authority and Control over the Management of Data Assets.






41. A high-level course of action to achieve data goals. Usually a data management program strategy.






42. FFHN Flat - No relationship among controlled set of categories (e.g. List of Countries) - Facet - Star - attributes of an object (Metadata) - Hierarchical - TREE structure (Geography) - Network - Hierarchy And Facet (Thesaurus)






43. Data Strategy and Policies - Standards and Architecture - Regulatory Compliance - Issue management - PROJECTS - Valuation - Communication






44. LEGISLATIVE branch - Policies and standards - JUDICIAL branch - Issue management - EXECUTIVE branch - administration - services - and compliance






45. Customer - CRM Employee/workforce - HRM






46. (ARPM Bit Mikes PP) ARPM (Awareness - Requirements - Profile - Metrics) - BTS (Business Rules - Test requirements - Service levels) - PP (Measure/monitor - Issues - Clean - Procedures - Performance)






47. Knowledge modeling. Ontology is a semantic model that describes Knowledge.






48. PLM - Product lifecycle management systems - enable cross-process cost and legal agreements tracking as product concepts evolve from one idea to many potential products under different names and potentially different licensing agreements.






49. Document mgt- not concerned with insides of the file. - Content mgt - looks at inside of file and tries to identify the content.






50. Source Systems - Staging Area - Data Presentation Area/DW - Data Access Tools