Chapter 14. Outline. Database Support for Decision Making. Data and Database Administration

Transcription

1 Chapter 14 Data and Database Administration McGraw-Hill/Irwin Copyright 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Outline Organizational context Tools of database administration Processes for database specialists Overview of processing environments 14-2 Database Support for Decision Making Management Hierarchy Top (strategic) Middle (tactical) Lower (operational) External data sources and summarized, tactical databases Summarized, integrated operational databases Individual operational databases Operational databases

2 Decision Making Examples Level Example Decisions Data Requirements Top Identify new markets and products; plan growth; reallocate resources across divisions Middle Choose suppliers; forecast sales, inventory, and cash; revise staffing levels; prepare budgets Lower Schedule employees; correct order delays; find production bottlenecks; monitor resource usage Economic and technology forecasts; news summaries; industry reports; medium term performance reports Historical trends; supplier performance; critical path analysis; short term and medium term plans Problem reports; exception reports; employee schedules; daily production results; inventory levels 14-4 Information Life Cycle Usage Acquisition Dissemination Storage Protection Formatting Processing 14-5 Knowledge Management Technology Human information processing Organization dynamics

3 Database Specialists Data administrator Middle or upper management Broad view of information resources Database administrator (DBA) Support role Emphasis on individual databases and DBMSs 14-7 Responsibilities of Specialists Data administrator Develops enterprise data model Establishes inter database standards Negotiates contractual terms Database administrator Performs database development tasks Consults on application development Evaluates DBMS capabilities and features 14-8 Database Administration Tools Security Integrity Management of stored procedures and triggers Data dictionary access

4 Database Access Control Authorization rules DBA Authentication, access requests Database security system Users Data dictionary Discretionary Access Control Assign access rights or privileges to users Specify ability to read, write, and delete specified parts of a database Use views for fine level of control Use groups to reduce the number of authorization rules SQL Statements for Security I CREATE ROLE ISFaculty CREATE ROLE ISAdministrator WITH ADMIN CURRENT_ROLE CREATE ROLE ISAdvisor

5 SQL Statements for Security II GRANT SELECT ON ISStudentGPA TO ISFaculty, ISAdvisor, ISAdministrator GRANT UPDATE ON ISStudentGPA.StdGPA TO ISAdministrator REVOKE SELECT ON ISStudentGPA FROM ISFaculty RESTRICT GRANT ISAdministrator TO Smith WITH GRANT OPTION; Common SQL Privileges Privilege Explanation SELECT UPDATE INSERT DELETE TRIGGER Query the object; cannot be specified for individual columns Modify the value; can be specified for individual columns Add a new row; can be specified for individual columns Delete a row; cannot be specified for individual columns Create a trigger on the specified table REFERENCES Reference columns of the given table in integrity constraints EXECUTE Execute the stored procedure Oracle Security Statements CREATE USER statement Predefined roles CONNECT RESOURCE DBA System versus object privileges

6 Access Security Tools Mandatory Access Control Less flexible security approach for highly sensitive and static databases Assign classification levels to database objects Assign clearance levels to users Access granted if a user's clearance level provides access to the classification level of a database object Encryption Encoding data to obscure its meaning Plaintext Ciphertext Encryption key

7 SQL Domains Limited ability to define new domains CREATE DOMAIN statement CREATE DOMAIN StudentClass AS CHAR(2) CHECK(VALUE IN ('FR','SO','JR','SR') ) Distinct type CREATE DISTINCT TYPE USD AS DECIMAL(10,2); SQL Assertions Supports complex constraints Constraint specified through a SELECT statement Enforcement can be inefficient Stored procedures and form events are alternatives Assertion Example CREATE ASSERTION FullTimeEnrollment CHECK (NOT EXISTS ( SELECT Enrollment.RegNo FROM Registration, Offering, Enrollment, Course WHERE Offering.OfferNo =Enrollment.OfferNo AND Offering.CourseNo = Course.CourseNo AND Offering.RegNo = Registration.RegNo AND RegStatus = 'F' GROUP BY Enrollment.RegNo HAVING SUM(CrsUnits) >= 9 ) )

8 CHECK Constraints Use when a constraint involves columns of the same table Part of CREATE TABLE statement Easy to write Efficient to enforce CHECK Constraints Example CREATE TABLE Student ( CONSTRAINT ValidGPA CHECK ( StdGPA BETWEEN 0 AND 4 ), CONSTRAINT MajorDeclared CHECK ( StdClass IN ('FR','SO') OR StdMajor IS NOT NULL ) ) Coding Practice Concerns Documentation Parameter usage Content of triggers and stored procedures

9 Management of Dependencies Referenced tables, views, and procedures Access plans for SQL statements DBMS support incomplete Obsolete statistics Remotely stored procedures No automatic recompilation after deletion Managing Trigger Complexity Coding guidelines to minimize interaction Trigger analysis tools Additional testing for interacting triggers Metadata Define the source, use, value, and meaning of data Stored in a data dictionary DBMS data dictionary to track objects managed by the DBMS Information resource dictionary to track objects relating to information systems development

10 Catalog Tables Most DBMSs provide a large collection Definition Schema and Information Schema in SQL:2003 Modify using data definition and control statements Use SELECT statement to retrieve from catalog tables Integrity of catalog tables is crucial Sample Oracle Catalog Tables Table Name Contents USER_CATALOG USER_OBJECTS USER_TABLES Contains basic data about each table and view defined by a user. Contains data about each object (functions, procedures, indexes, triggers, assertions, etc.) defined by a user. This table contains the time created and the last time changed for each object. Contains extended data about each table such as space allocation and statistical summaries. USER_TAB_COLUMNS Contains basic and extended data for each column such as the column name, the table reference, the data type, and a statistical summary. USER_VIEWS Contains the SQL statement defining each view Information Resource Dictionary CASE tool 1 CASE tool 2... CASE tool n Metadata import IRDS Metadata export DBMS IRD

11 Processes for Database Specialists Data planning DBMS selection and evaluation Goals of Data Planning Evaluate current information systems with respect to the goals and objectives of the organization Determine the scope and the timing of developing new information systems and utilizing of new information technology Identify opportunities to apply information technology for competitive advantage Planning Models Enterprise models Business goals and objectives Data Align information systems with business environment Processes Organization

12 Level of Detail in Models Model Data Process Organization Data-process interaction Process-organization interaction Data-organization Levels of Detail Subject model (initial level), entity model (detailed level) Functional areas and business processes (initial level), activity model (detailed level) Role definitions and role relationships Matrix and diagrams showing data requirements of processes Matrix and diagrams showing role responsibilities Matrix and diagrams showing usage of data by roles DBMS Selection Detailed process Requires knowledge of organization goals and DBMS features Systematic approach is important High switching cost if wrong choice Selection Process Phases Analyze requirements Determine weights Score candidate systems Ranked candidates

13 Analytic Hierarchy Process Multi-criteria decision making tool Supports systematic assignment of weights and scores to candidate DBMSs Uses pairwise comparisons Rating Values for Comparisons Ranking Value of A ij Meaning Requirements i and j are equally important. Requirement i is slightly more important than requirement j. Requirement i is significantly more important than requirement j. Requirement i is very significantly more important than requirement j. Requirement i is absolutely more important than requirement j Analytic Hierarchy Process Details Assign importance weights to pairwise combinations of requirement groups and requirement categories Combine and normalize importance weights Score candidate DBMSs for each requirement Combine and normalize scores Combine importance weights and DBMS scores

14 Final Selection Factors Benchmarks and trial usage Contractual terms Vendor expectations Benchmarking Workload to evaluate the performance of a system or product A good benchmark should be relevant, portable, scalable, and understandable. Standard, domain-specific benchmarks by TPC TCP Benchmarks Reasonable estimates about a DBMS in a specific hardware/software environment Total system performance and cost measures Audits to ensure unbiased results

15 Current TCP Benchmarks TPC-C: order entry benchmark TPC-App: business to business transactions TPC-H: decision support ad hoc queries TPC-W: Ecommerce benchmark Managing Database Environments Transaction processing Data warehouse processing Distributed processing Object data management Responsibilities of Database Specialists Application development Database infrastructure and architectures Performance monitoring Enterprise data model development Contingency planning

16 Summary Two roles for managing information resources Tools for security, integrity, rule processing, stored procedures, and data dictionary manipulation Processes for data planning and DBMS selection Context for studying other Part 7 chapters