1. © 2009 Pearson Education, Inc. Publishing as Prentice Hall 1 UNIT 9: Data Management Modern Database Management 9 th Edition Jeffrey A. Hoffer, Mary B. Prescott, Heikki Topi

2. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 2 Traditional Administration Definitions Data Administration: A high-level function that is responsible for the overall management of data resources in an organization, including maintaining corporate-wide definitions and standards Data Administration: A high-level function that is responsible for the overall management of data resources in an organization, including maintaining corporate-wide definitions and standards Database Administration: A technical function that is responsible for physical database design and for dealing with technical issues such as security enforcement, database performance, and backup and recovery Database Administration: A technical function that is responsible for physical database design and for dealing with technical issues such as security enforcement, database performance, and backup and recovery

3. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 3 Traditional Data Administration Functions Data policies, procedures, standards Data policies, procedures, standards Planning Planning Data conflict (ownership) resolution Data conflict (ownership) resolution Managing the information repository Managing the information repository Internal marketing of DA concepts Internal marketing of DA concepts

4. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 4 Traditional Database Administration Functions Selection of DBMS and software tools Selection of DBMS and software tools Installing/upgrading DBMS Installing/upgrading DBMS Tuning database performance Tuning database performance Improving query processing performance Improving query processing performance Managing data security, privacy, and integrity Managing data security, privacy, and integrity Data backup and recovery Data backup and recovery

5. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 5 Evolving Approaches to Data Administration Blend data and database administration into one role Blend data and database administration into one role Fast-track development–monitoring development process (planning, analysis, design, implementation, maintenance) Fast-track development–monitoring development process (planning, analysis, design, implementation, maintenance) Procedural DBAs–managing quality of triggers and stored procedures Procedural DBAs–managing quality of triggers and stored procedures eDBA–managing Internet-enabled database applications eDBA–managing Internet-enabled database applications PDA DBA–data synchronization and personal database management PDA DBA–data synchronization and personal database management Data warehouse administration Data warehouse administration

6. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 6 Figure 13-2 Data modeling responsibilities

7. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 7 Database Security Database Security: Protection of the data against accidental or intentional loss, destruction, or misuse Database Security: Protection of the data against accidental or intentional loss, destruction, or misuse Increased difficulty due to Internet access and client/server technologies Increased difficulty due to Internet access and client/server technologies

8. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 8 Figure 13-3 Possible locations of data security threats

9. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Characteristics of Quality Data Uniqueness Uniqueness Accuracy Accuracy Consistency Consistency Completeness Completeness Timeliness Timeliness Currency Currency Conformance Conformance Referential integrity Referential integrity 9

10. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 10 Causes of poor data quality External data sources External data sources Lack of control over data quality Lack of control over data quality Redundant data storage and inconsistent metadata Redundant data storage and inconsistent metadata Proliferation of databases with uncontrolled redundancy and metadata Proliferation of databases with uncontrolled redundancy and metadata Data entry Data entry Poor data capture controls Poor data capture controls Lack of organizational commitment Lack of organizational commitment Do not recognize poor data quality as an organizational issue Do not recognize poor data quality as an organizational issue

11. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 11 Data quality improvement Perform data quality audit Perform data quality audit Improve data capture processes Improve data capture processes Establish data stewardship program Establish data stewardship program Apply total quality management (TQM) practices Apply total quality management (TQM) practices Apply modern DBMS technology Apply modern DBMS technology Estimate return on investment Estimate return on investment Start with a high-quality data model Start with a high-quality data model

12. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Improving Data Capture Processes Automate data entry as much as possible Automate data entry as much as possible Manual data entry should be selected from preset options Manual data entry should be selected from preset options Use trained operators when possible Use trained operators when possible Follow good user interface design principles Follow good user interface design principles Immediate data validation for entered data Immediate data validation for entered data 12

13. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Data Integration Data integration creates a unified view of business data Data integration creates a unified view of business data Other possibilities: Other possibilities: Application integration Application integration Business process integration Business process integration User interaction integration User interaction integration Any approach required changed data capture (CDC) Any approach required changed data capture (CDC) Indicates which data have changed since previous data integration activity Indicates which data have changed since previous data integration activity 13

14. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall Techniques for Data Integration Consolidation (ETL) Consolidation (ETL) Consolidating all data into a centralized database (like a data warehouse) Consolidating all data into a centralized database (like a data warehouse) Data federation (EII) Data federation (EII) Provides a virtual view of data without actually creating one centralized database Provides a virtual view of data without actually creating one centralized database Data propagation (EAI and ERD) Data propagation (EAI and ERD) Duplicate data across databases, with near real-time delay Duplicate data across databases, with near real-time delay 14

15. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 15 Threats to Data Security Accidental losses attributable to: Accidental losses attributable to: Human error Human error Software failure Software failure Hardware failure Hardware failure Theft and fraud Theft and fraud Improper data access: Improper data access: Loss of privacy (personal data) Loss of privacy (personal data) Loss of confidentiality (corporate data) Loss of confidentiality (corporate data) Loss of data integrity Loss of data integrity Loss of availability (through, e.g. sabotage) Loss of availability (through, e.g. sabotage)

16. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 16 Figure 13-4 Establishing Internet Security

17. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 17 Web Security Static HTML files are easy to secure Static HTML files are easy to secure Standard database access controls Standard database access controls Place Web files in protected directories on server Place Web files in protected directories on server Dynamic pages are harder Dynamic pages are harder Control of CGI scripts Control of CGI scripts User authentication User authentication Session security Session security SSL for encryption SSL for encryption Restrict number of users and open ports Restrict number of users and open ports Remove unnecessary programs Remove unnecessary programs

18. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 18 W3C Web Privacy Standard Platform for Privacy Protection (P3P) Platform for Privacy Protection (P3P) Addresses the following: Addresses the following: Who collects data Who collects data What data is collected and for what purpose What data is collected and for what purpose Who is data shared with Who is data shared with Can users control access to their data Can users control access to their data How are disputes resolved How are disputes resolved Policies for retaining data Policies for retaining data Where are policies kept and how can they be accessed Where are policies kept and how can they be accessed

19. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 19 Database Software Security Features Views or subschemas Views or subschemas Integrity controls Integrity controls Authorization rules Authorization rules User-defined procedures User-defined procedures Encryption Encryption Authentication schemes Authentication schemes Backup, journalizing, and checkpointing Backup, journalizing, and checkpointing

20. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 20 Views and Integrity Controls Views Views Subset of the database that is presented to one or more users Subset of the database that is presented to one or more users User can be given access privilege to view without allowing access privilege to underlying tables User can be given access privilege to view without allowing access privilege to underlying tables Integrity Controls Integrity Controls Protect data from unauthorized use Protect data from unauthorized use Domains–set allowable values Domains–set allowable values Assertions–enforce database conditions Assertions–enforce database conditions

21. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 21 Authorization Rules Controls incorporated in the data management system Controls incorporated in the data management system  Restrict:  Restrict: access to data access to data actions that people can take on data actions that people can take on data  Authorization matrix for:  Authorization matrix for: Subjects Subjects Objects Objects Actions Actions Constraints Constraints

22. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 22 Figure 13-5 Authorization matrix

23. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 23 Some DBMSs also provide capabilities for user- defined procedures to customize the authorization process Figure 13-6a Authorization table for subjects (salespeople) Figure 13-6b Authorization table for objects (orders) Figure 13-7 Oracle privileges Implementing authorization rules

24. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 24 Encryption – the coding or scrambling of data so that humans cannot read them Secure Sockets Layer (SSL) is a popular encryption scheme for TCP/IP connections Figure 13-8 Basic two-key encryption

25. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 25 Authentication Schemes Goal – obtain a positive identification of the user Goal – obtain a positive identification of the user Passwords: First line of defense Passwords: First line of defense Should be at least 8 characters long Should be at least 8 characters long Should combine alphabetic and numeric data Should combine alphabetic and numeric data Should not be complete words or personal information Should not be complete words or personal information Should be changed frequently Should be changed frequently

26. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 26 Authentication Schemes (cont.) Strong Authentication Strong Authentication Passwords are flawed: Passwords are flawed: Users share them with each other Users share them with each other They get written down, could be copied They get written down, could be copied Automatic logon scripts remove need to explicitly type them in Automatic logon scripts remove need to explicitly type them in Unencrypted passwords travel the Internet Unencrypted passwords travel the Internet Possible solutions: Possible solutions: Two factor–e.g. smart card plus PIN Two factor–e.g. smart card plus PIN Three factor–e.g. smart card, biometric, PIN Three factor–e.g. smart card, biometric, PIN Biometric devices–use of fingerprints, retinal scans, etc. for positive ID Biometric devices–use of fingerprints, retinal scans, etc. for positive ID Third-party mediated authentication–using secret keys, digital certificates Third-party mediated authentication–using secret keys, digital certificates

27. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 27 Security Policies and Procedures Personnel controls Personnel controls Hiring practices, employee monitoring, security training Hiring practices, employee monitoring, security training Physical access controls Physical access controls Equipment locking, check-out procedures, screen placement Equipment locking, check-out procedures, screen placement Maintenance controls Maintenance controls Maintenance agreements, access to source code, quality and availability standards Maintenance agreements, access to source code, quality and availability standards Data privacy controls Data privacy controls Adherence to privacy legislation, access rules Adherence to privacy legislation, access rules

28. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 28 Database Recovery  Mechanism for restoring a database quickly and accurately after loss or damage  Recovery facilities: Backup Facilities Backup Facilities Journalizing Facilities Journalizing Facilities Checkpoint Facility Checkpoint Facility Recovery Manager Recovery Manager

29. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 29 Back-up Facilities Automatic dump facility that produces backup copy of the entire database Automatic dump facility that produces backup copy of the entire database Periodic backup (e.g. nightly, weekly) Periodic backup (e.g. nightly, weekly) Cold backup–database is shut down during backup Cold backup–database is shut down during backup Hot backup–selected portion is shut down and backed up at a given time Hot backup–selected portion is shut down and backed up at a given time Backups stored in secure, off-site location Backups stored in secure, off-site location

30. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 30 Journalizing Facilities Audit trail of transactions and database updates Audit trail of transactions and database updates Transaction log–record of essential data for each transaction processed against the database Transaction log–record of essential data for each transaction processed against the database Database change log–images of updated data Database change log–images of updated data Before-image–copy before modification Before-image–copy before modification After-image–copy after modification After-image–copy after modification audit trail Produces an audit trail

31. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 31 Figure 13-9 Database audit trail From the backup and logs, databases can be restored in case of damage or loss

32. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 32 Recovery and Restart Procedures Disk Mirroring–switch between identical copies of databases Disk Mirroring–switch between identical copies of databases Restore/Rerun–reprocess transactions against the backup Restore/Rerun–reprocess transactions against the backup Transaction Integrity–commit or abort all transaction changes Transaction Integrity–commit or abort all transaction changes Backward Recovery (Rollback)–apply before images Backward Recovery (Rollback)–apply before images Forward Recovery (Roll Forward)–apply after images (preferable to restore/rerun) Forward Recovery (Roll Forward)–apply after images (preferable to restore/rerun)

33. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 33 Figure 13-10 Basic recovery techniques a) Rollback

34. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 34 Figure 13-10 Basic recovery techniques (cont.) b) Rollforward

35. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 35 Database Failure Responses Aborted transactions Aborted transactions Preferred recovery: rollback Preferred recovery: rollback Alternative: Rollforward to state just prior to abort Alternative: Rollforward to state just prior to abort Incorrect data Incorrect data Preferred recovery: rollback Preferred recovery: rollback Alternative 1: rerun transactions not including inaccurate data updates Alternative 1: rerun transactions not including inaccurate data updates Alternative 2: compensating transactions Alternative 2: compensating transactions System failure (database intact) System failure (database intact) Preferred recovery: switch to duplicate database Preferred recovery: switch to duplicate database Alternative 1: rollback Alternative 1: rollback Alternative 2: restart from checkpoint Alternative 2: restart from checkpoint Database destruction Database destruction Preferred recovery: switch to duplicate database Preferred recovery: switch to duplicate database Alternative 1: rollforward Alternative 1: rollforward Alternative 2: reprocess transactions Alternative 2: reprocess transactions

36. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 36 Data Dictionaries and Repositories Data dictionary Data dictionary Documents data elements of a database Documents data elements of a database System catalog System catalog System-created database that describes all database objects System-created database that describes all database objects Information Repository Information Repository Stores metadata describing data and data processing resources Stores metadata describing data and data processing resources Information Repository Dictionary System (IRDS) Information Repository Dictionary System (IRDS) Software tool managing/controlling access to information repository Software tool managing/controlling access to information repository

37. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 37 Figure 13-16 Three components of the repository system architecture A schema of the repository information Software that manages the repository objects Where repository objects are stored Source: adapted from Bernstein, 1996.

38. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 38 Data Availability Downtime is expensive Downtime is expensive How to ensure availability How to ensure availability Hardware failures–provide redundancy for fault tolerance Hardware failures–provide redundancy for fault tolerance Loss of data–database mirroring Loss of data–database mirroring Maintenance downtime–automated and non- disruptive maintenance utilities Maintenance downtime–automated and non- disruptive maintenance utilities Network problems–careful traffic monitoring, firewalls, and routers Network problems–careful traffic monitoring, firewalls, and routers

39. Chapter 13 © 2009 Pearson Education, Inc. Publishing as Prentice Hall 39 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall