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  1. 2. Part V: Data Administration Chapter 13: Data and Database Administration Chapter 14: Data Warehouse
  2. 3. Chapter 13: Data and Database Administration Data Administrator Database Administrator Modeling and Planning Enterprise Data Data Security Backup Concurrent Access Data Quality
  3. 4. Data Administrator <ul><li>Custodian of the organization’s data </li></ul><ul><li>Develops procedures to protect and control data resource </li></ul><ul><li>Maintains corporate-wide data definitions and standards </li></ul><ul><li>Functional responsibilities: planning, analysis, design, implementation, maintenance, protection </li></ul><ul><li>Should be a respected, senior-level middle manager </li></ul><ul><li>Requires a high level of managerial and technical skills </li></ul>
  4. 5. Database Administrator <ul><li>Responsible for physical database design and technical issues </li></ul><ul><li>Carries through the standards and procedures established by data administrator </li></ul><ul><li>Broad technical background </li></ul><ul><li>Managerial skills are also critical </li></ul>
  5. 6. Corporate Data Management <ul><li>Functions: </li></ul><ul><ul><li>data policies, procedures, and standards </li></ul></ul><ul><ul><li>planning </li></ul></ul><ul><ul><li>data conflict resolution </li></ul></ul><ul><ul><li>internal marketing </li></ul></ul><ul><ul><li>managing the data repository </li></ul></ul><ul><ul><li>selection of hardware and software </li></ul></ul><ul><ul><li>managing data security, privacy, and integrity </li></ul></ul><ul><ul><li>data backup and recovery </li></ul></ul>
  6. 7. Modeling Enterprise Data <ul><li>Enterprise architecture: “that set of descriptive representations that are relevant for describing an enterprise such that it can be produced to management’s requirements and maintained over the period of its useful life.” </li></ul><ul><li>The conceptual data model must mesh with … </li></ul><ul><ul><li>business process model </li></ul></ul><ul><ul><li>business network logistics </li></ul></ul><ul><ul><li>work flow models </li></ul></ul><ul><ul><li>enterprise master schedule </li></ul></ul><ul><ul><li>enterprise business plan </li></ul></ul>
  7. 8. Planning for Databases <ul><li>What data will be included? </li></ul><ul><li>What processes will the system perform? </li></ul><ul><li>What business locations will the system affect? </li></ul><ul><li>What work units and people will be affected by the system? </li></ul><ul><li>How will the system fit with significant business effects? </li></ul>
  8. 9. Managing Data Security <ul><li>Threats to data security </li></ul><ul><ul><li>accidental: human, software, hardware error </li></ul></ul><ul><ul><li>theft and fraud </li></ul></ul><ul><ul><li>loss of privacy or confidentiality </li></ul></ul><ul><ul><li>loss of data integrity </li></ul></ul><ul><ul><li>loss of availability </li></ul></ul><ul><li>Data security plan </li></ul><ul><ul><li>limit access (4 methods) </li></ul></ul><ul><ul><li>conceal data </li></ul></ul><ul><ul><li>facilitate recovery </li></ul></ul>
  9. 10. Security: Views <ul><li>Presents only data to which a user needs access </li></ul><ul><li>Always shows current data </li></ul><ul><li>More sophisticated security measures are normally required </li></ul>
  10. 11. Security: Authorization Rules <ul><li>Restrict access to data </li></ul><ul><li>Restrict actions that may be taken </li></ul><ul><li>Authorization tables for subjects (users) </li></ul><ul><li>Authorization tables for objects (data) </li></ul>
  11. 12. Security: User-Defined Procedures <ul><li>For example, a series of questions </li></ul>Security: Encryption Security: Authentication Schemes
  12. 13. Database Recovery <ul><li>Backup facilities </li></ul><ul><ul><li>static data … dynamic data … incremental backup </li></ul></ul><ul><li>Journalizing facilities </li></ul><ul><ul><li>transaction log … before-image … after-image </li></ul></ul><ul><li>Checkpoint facility </li></ul><ul><ul><li>provides known state from which recovery can be done </li></ul></ul><ul><li>Recovery manager </li></ul>
  13. 14. Recovery and Restart Procedures <ul><li>Switch (mirrored database) </li></ul><ul><li>Restore/Rerun: reprocess transactions </li></ul><ul><li>Transaction integrity </li></ul><ul><ul><li>commit or abort </li></ul></ul><ul><ul><li>backward recovery – rollback – undo transactions </li></ul></ul><ul><ul><li>forward recovery -- rollforward – apply transactions </li></ul></ul>
  14. 15. Concurrent Access <ul><li>Pessimistic: locking </li></ul><ul><li>Optimistic: versioning </li></ul><ul><li>Reading </li></ul><ul><ul><li>no concurrency issues </li></ul></ul><ul><li>Writing </li></ul><ul><ul><li>incompatible updates </li></ul></ul><ul><ul><li>inaccurate data read by another </li></ul></ul>
  15. 16. Locking Mechanisms <ul><li>Locking level (granularity) </li></ul><ul><ul><li>database … table … block/page … record … field </li></ul></ul><ul><ul><li>shared locks </li></ul></ul><ul><ul><li>exclusive locks </li></ul></ul><ul><li>Deadlocks </li></ul><ul><ul><li>prevention by lock all at start </li></ul></ul><ul><ul><li>two-phase: lock all, then release </li></ul></ul><ul><ul><li>resolution: backout transactions </li></ul></ul>
  16. 17. Versioning <ul><li>Only one user may make changes </li></ul><ul><li>Other users restricted from changing, must restart </li></ul>
  17. 18. Managing Data Quality <ul><li>Security policy and disaster recovery </li></ul><ul><li>Personnel controls </li></ul><ul><li>Physical access controls </li></ul><ul><li>Maintenance controls </li></ul><ul><li>Data protection and privacy </li></ul>
  18. 19. Chapter 14: Data Warehouse Data Warehouse Architecture Data Characteristics Reconciled Data Layer Data Transformation Derived Data Layer User Interface
  19. 20. Two Types of Processing <ul><li>Operational processing </li></ul><ul><ul><li>captures, stores, and manipulates data to support daily operations </li></ul></ul><ul><li>Informational processing </li></ul><ul><ul><li>analysis of summarized data to support decision making </li></ul></ul><ul><li>Data warehouses </li></ul><ul><ul><li>consolidate and integrate information from many different sources and arrange it in a meaningful format for making accurate business decisions </li></ul></ul>
  20. 21. Data Warehouse Architectures <ul><li>Two-level architecture </li></ul><ul><ul><li>source files … read-only data warehouse </li></ul></ul><ul><li>Three-level architecture </li></ul><ul><ul><li>source files … enterprise data warehouse (reconciled data) … data mart (derived data) </li></ul></ul>
  21. 22. Data Characteristics <ul><li>Status vs. event data </li></ul><ul><ul><li>balance vs. transaction </li></ul></ul><ul><li>Transient vs. periodic data </li></ul><ul><ul><li>current balance vs. balance history </li></ul></ul>
  22. 23. Reconciled Data Layer <ul><li>Used to build data warehouse </li></ul><ul><li>Characteristics of reconciled data </li></ul><ul><ul><li>detailed </li></ul></ul><ul><ul><li>historical </li></ul></ul><ul><ul><li>normalized </li></ul></ul><ul><ul><li>comprehensive </li></ul></ul><ul><ul><li>quality controlled </li></ul></ul><ul><li>Capture  Scrub  Transform  Load </li></ul>
  23. 24. Derived Data Layer <ul><li>Data that have been selected, formatted, and aggregated </li></ul><ul><li>Star schema </li></ul><ul><ul><li>dimension table: “demographic data” </li></ul></ul><ul><ul><li>fact table: “associative data” – often summarized </li></ul></ul>
  24. 25. User Interface <ul><li>Traditional query and reporting tools </li></ul><ul><li>On-line analytical processing (OLAP) </li></ul><ul><ul><li>cube slicing </li></ul></ul><ul><ul><li>drill-down </li></ul></ul><ul><li>Data mining </li></ul><ul><ul><li>explanatory </li></ul></ul><ul><ul><li>confirmatory </li></ul></ul><ul><ul><li>exploratory </li></ul></ul><ul><li>Data visualization </li></ul>