IMS1907 Database Systems Summer Semester 2004/2005 Lecture 13.2   Unit Review
Basic Concepts <ul><li>Central concepts for understanding database systems </li></ul><ul><ul><li>Database </li></ul></ul><...
Basic Concepts <ul><li>File processing systems vs DBMS </li></ul><ul><ul><li>data sharing </li></ul></ul><ul><ul><li>speed...
Basic Concepts <ul><li>The database system environment </li></ul><ul><ul><li>DBMS </li></ul></ul><ul><ul><li>database </li...
<ul><li>Personal Databases </li></ul><ul><li>Workgroup Databases </li></ul><ul><li>Department Databases </li></ul><ul><li>...
<ul><li>Need for new, specialised personnel </li></ul><ul><li>Installation cost and complexity </li></ul><ul><li>Maintenan...
<ul><li>Relational database systems organise the database as groups of related tables </li></ul><ul><ul><li>table or relat...
Database System Development <ul><li>Database development requires a focus on the information needs of a business </li></ul...
Database System Development <ul><li>Database systems planning </li></ul><ul><ul><li>the three steps in the IE Planning pha...
<ul><li>Enterprise modelling </li></ul>Database Development and the SDLC Conceptual data modelling Logical database design...
<ul><li>Enterprise modelling </li></ul><ul><ul><li>the organisational perspective </li></ul></ul><ul><li>Conceptual data m...
<ul><li>Physical database design and definition </li></ul><ul><ul><li>define database for specific DBMS used </li></ul></u...
<ul><li>Data modelling </li></ul><ul><li>Business rules </li></ul><ul><li>ER modelling </li></ul><ul><ul><li>entities or ‘...
<ul><li>Entities </li></ul><ul><ul><li>strong, weak </li></ul></ul><ul><li>Relationships </li></ul><ul><li>Associative ent...
<ul><li>Cardinality </li></ul><ul><ul><li>one-to-one, one-to-many, many-to-many </li></ul></ul><ul><li>Cardinality constra...
<ul><li>Detailed data modelling </li></ul><ul><li>Relational database theory </li></ul><ul><ul><li>considers data structur...
<ul><li>A well-structured relation </li></ul><ul><ul><li>is robust, stable and flexible </li></ul></ul><ul><ul><li>contain...
<ul><li>Representing entities and relationships as relations </li></ul><ul><li>Normalisation is a process for converting c...
<ul><li>First normal form (1NF) </li></ul><ul><ul><li>identify PK, identify and remove repeating groups </li></ul></ul><ul...
<ul><li>Has become de facto language for creating and querying relational databases </li></ul><ul><li>Benefits and disadva...
<ul><li>DDL </li></ul><ul><ul><li>CREATE statements </li></ul></ul><ul><ul><ul><li>database, table, view, …. </li></ul></u...
<ul><li>DML </li></ul><ul><ul><li>INSERT, LOAD DATA statements to populate tables </li></ul></ul><ul><ul><li>SHOW, DESCRIB...
<ul><li>DML </li></ul><ul><ul><li>matching patterns with LIKE </li></ul></ul><ul><ul><li>joining tables </li></ul></ul><ul...
<ul><li>Views </li></ul><ul><li>Schema </li></ul><ul><li>ANSI/SPARC three-schema architecture standard </li></ul><ul><ul><...
<ul><li>Data independence </li></ul><ul><ul><li>logical </li></ul></ul><ul><ul><li>physical </li></ul></ul><ul><li>Network...
Database Systems Performance Issues <ul><li>The ultimate measures of database performance are </li></ul><ul><ul><li>respon...
<ul><li>Guided by the nature of the data and its intended use </li></ul><ul><li>Tuning the database is often performed dur...
<ul><li>Data volume and usage analysis – workloads </li></ul><ul><li>Choice of data types </li></ul><ul><li>Designing phys...
Database Systems Performance <ul><li>Choosing an appropriate database architectures </li></ul><ul><ul><li>hierarchical dat...
<ul><li>Data is viewed as a corporate asset </li></ul><ul><li>As with any asset, management is essential to exploit the re...
Information Resource Management <ul><li>There are three major roles in information resource management </li></ul><ul><ul><...
Information Resource Management <ul><li>Ineffective data administration leads to poor data utilisation </li></ul><ul><li>N...
Final Exam <ul><li>3 hour exam, 10 minute reading time </li></ul><ul><li>Ten questions </li></ul><ul><ul><li>1 question co...
Exam Strategy <ul><li>Know the date, time and location of your exam – it’s your responsibility! </li></ul><ul><li>Know you...
Exam Strategy <ul><li>3 hour, 10 minute reading time, 100 marks </li></ul><ul><ul><li>you’ve got 180 minutes to earn 100 m...
Study Strategy <ul><li>Give yourself sufficient time for revision </li></ul><ul><ul><li>don’t wait till the day before the...
Upcoming SlideShare
Loading in …5
×

IMS1907 Database Systems Summer Semester 2004/2005

630 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
630
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
17
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

IMS1907 Database Systems Summer Semester 2004/2005

  1. 1. IMS1907 Database Systems Summer Semester 2004/2005 Lecture 13.2 Unit Review
  2. 2. Basic Concepts <ul><li>Central concepts for understanding database systems </li></ul><ul><ul><li>Database </li></ul></ul><ul><ul><li>Data </li></ul></ul><ul><ul><li>Information </li></ul></ul><ul><ul><li>Data vs Information </li></ul></ul><ul><ul><li>Metadata </li></ul></ul><ul><ul><li>DBMS </li></ul></ul>
  3. 3. Basic Concepts <ul><li>File processing systems vs DBMS </li></ul><ul><ul><li>data sharing </li></ul></ul><ul><ul><li>speed of access and retrieval </li></ul></ul><ul><ul><li>security </li></ul></ul><ul><ul><li>integrity, quality, consistency of data </li></ul></ul><ul><ul><li>data independence </li></ul></ul><ul><ul><li>maintenance, productivity </li></ul></ul><ul><ul><li>multiple users, complex data </li></ul></ul><ul><ul><li>backup and recovery </li></ul></ul>
  4. 4. Basic Concepts <ul><li>The database system environment </li></ul><ul><ul><li>DBMS </li></ul></ul><ul><ul><li>database </li></ul></ul><ul><ul><li>metadata (repository) </li></ul></ul><ul><ul><li>application software </li></ul></ul><ul><ul><li>CASE tools </li></ul></ul><ul><ul><li>user interfaces </li></ul></ul><ul><ul><li>users, developers, administrators </li></ul></ul>
  5. 5. <ul><li>Personal Databases </li></ul><ul><li>Workgroup Databases </li></ul><ul><li>Department Databases </li></ul><ul><li>Enterprise Databases </li></ul><ul><li>Internet, Intranet, and Extranet Databases </li></ul><ul><li>Data warehouses </li></ul>Types of Database Systems
  6. 6. <ul><li>Need for new, specialised personnel </li></ul><ul><li>Installation cost and complexity </li></ul><ul><li>Maintenance cost and complexity </li></ul><ul><li>Conversion costs from legacy systems </li></ul><ul><li>Critical need for explicit backup and recovery </li></ul><ul><li>Organisational conflict and change </li></ul>Costs and Risks of Database Systems
  7. 7. <ul><li>Relational database systems organise the database as groups of related tables </li></ul><ul><ul><li>table or relation </li></ul></ul><ul><ul><li>record </li></ul></ul><ul><ul><li>field </li></ul></ul><ul><ul><li>primary key </li></ul></ul><ul><ul><li>secondary key </li></ul></ul><ul><ul><li>foreign key </li></ul></ul><ul><ul><li>table structure </li></ul></ul><ul><li>Forms, reports, queries </li></ul>Relational DBMS Software
  8. 8. Database System Development <ul><li>Database development requires a focus on the information needs of a business </li></ul><ul><li>Information Engineering (IE) is a popular, data-oriented methodology used to develop database systems </li></ul><ul><ul><li>data are modelled in the organisational context, not in the usage, processing or technology context </li></ul></ul><ul><ul><li>business context changes slowly  stable databases </li></ul></ul><ul><ul><li>top-down planning </li></ul></ul>
  9. 9. Database System Development <ul><li>Database systems planning </li></ul><ul><ul><li>the three steps in the IE Planning phase </li></ul></ul><ul><ul><ul><li>identify strategic planning factors </li></ul></ul></ul><ul><ul><ul><li>identify corporate planning objects </li></ul></ul></ul><ul><ul><ul><li>develop an enterprise model </li></ul></ul></ul><ul><li>Enterprise data model </li></ul><ul><ul><li>needed for top-down plans and bottom-up requests </li></ul></ul><ul><ul><li>organisation-wide perspective </li></ul></ul>
  10. 10. <ul><li>Enterprise modelling </li></ul>Database Development and the SDLC Conceptual data modelling Logical database design Database implementation Physical database design and definition Database review Database maintenance Initiation Analysis Design Implementation Review Maintenance
  11. 11. <ul><li>Enterprise modelling </li></ul><ul><ul><li>the organisational perspective </li></ul></ul><ul><li>Conceptual data modelling </li></ul><ul><ul><li>scope identification, ER modelling </li></ul></ul><ul><li>Logical database design </li></ul><ul><ul><li>transform conceptual model into logical data model </li></ul></ul><ul><ul><li>start to specify logic for maintaining and querying database </li></ul></ul><ul><ul><li>populate repository </li></ul></ul>Database Development and the SDLC
  12. 12. <ul><li>Physical database design and definition </li></ul><ul><ul><li>define database for specific DBMS used </li></ul></ul><ul><ul><li>organisation of data, database processing programs </li></ul></ul><ul><li>Database implementation </li></ul><ul><ul><li>install database and processing programs </li></ul></ul><ul><ul><li>develop procedures, load data, turn on! </li></ul></ul><ul><li>Database maintenance </li></ul><ul><ul><li>tune and fix the database, keep it running and evolving </li></ul></ul><ul><li>Packaged data models – universal, industry specific </li></ul>Database Development and the SDLC
  13. 13. <ul><li>Data modelling </li></ul><ul><li>Business rules </li></ul><ul><li>ER modelling </li></ul><ul><ul><li>entities or ‘things of interest’ </li></ul></ul><ul><ul><li>relationships </li></ul></ul><ul><ul><li>properties or attributes </li></ul></ul><ul><ul><li>rules and constraints affecting integrity of entities </li></ul></ul>ER Modelling
  14. 14. <ul><li>Entities </li></ul><ul><ul><li>strong, weak </li></ul></ul><ul><li>Relationships </li></ul><ul><li>Associative entities </li></ul><ul><li>Attributes </li></ul><ul><ul><li>multi-valued, derived, composite </li></ul></ul><ul><li>Degree </li></ul><ul><ul><li>unary, binary, ternary, n-ary </li></ul></ul>ER Modelling
  15. 15. <ul><li>Cardinality </li></ul><ul><ul><li>one-to-one, one-to-many, many-to-many </li></ul></ul><ul><li>Cardinality constraints </li></ul><ul><ul><li>optional, mandatory </li></ul></ul><ul><li>Time dependent data </li></ul><ul><li>Entity types and sub-types </li></ul><ul><li>ER quality issues </li></ul>ER Modelling
  16. 16. <ul><li>Detailed data modelling </li></ul><ul><li>Relational database theory </li></ul><ul><ul><li>considers data structure, manipulation, integrity </li></ul></ul><ul><li>Relation </li></ul><ul><li>Primary key </li></ul><ul><li>Composite key </li></ul><ul><li>Foreign key </li></ul><ul><li>Integrity constraints </li></ul><ul><ul><li>domain constraints, entity integrity, referential integrity </li></ul></ul>Relational Database Theory
  17. 17. <ul><li>A well-structured relation </li></ul><ul><ul><li>is robust, stable and flexible </li></ul></ul><ul><ul><li>contains a minimum amount of redundancy </li></ul></ul><ul><ul><li>allows users to insert, modify, and delete rows in a table without errors or inconsistencies </li></ul></ul><ul><li>Three types of anomaly are possible </li></ul><ul><ul><li>insertion </li></ul></ul><ul><ul><li>deletion </li></ul></ul><ul><ul><li>modification </li></ul></ul>Relational Database Theory
  18. 18. <ul><li>Representing entities and relationships as relations </li></ul><ul><li>Normalisation is a process for converting complex data structures into simple, stable data structures in the form of relations </li></ul><ul><li>Functional dependency </li></ul><ul><li>Accomplished in stages, each of which corresponds to a “normal form” </li></ul>Normalisation
  19. 19. <ul><li>First normal form (1NF) </li></ul><ul><ul><li>identify PK, identify and remove repeating groups </li></ul></ul><ul><li>Second normal form (2NF) </li></ul><ul><ul><li>remove partial dependencies </li></ul></ul><ul><li>Third normal form (3NF) </li></ul><ul><ul><li>remove transitive dependencies </li></ul></ul><ul><li>Merging relations </li></ul><ul><li>Data structure diagrams (DSD) </li></ul>Normalisation
  20. 20. <ul><li>Has become de facto language for creating and querying relational databases </li></ul><ul><li>Benefits and disadvantages of SQL </li></ul><ul><li>The SQL environment </li></ul><ul><ul><li>catalog </li></ul></ul><ul><ul><li>schema </li></ul></ul><ul><ul><li>data definition language (DDL) </li></ul></ul><ul><ul><li>data manipulation language (DML) </li></ul></ul><ul><ul><li>data control language (DCL) </li></ul></ul><ul><ul><li>data types </li></ul></ul>Structured Query Language (SQL)
  21. 21. <ul><li>DDL </li></ul><ul><ul><li>CREATE statements </li></ul></ul><ul><ul><ul><li>database, table, view, …. </li></ul></ul></ul><ul><ul><ul><li>assigning constraints </li></ul></ul></ul><ul><ul><li>DROP statements </li></ul></ul><ul><ul><ul><li>database, table, view, …. </li></ul></ul></ul><ul><ul><li>ALTER statements </li></ul></ul><ul><ul><ul><li>database, table, view, column, …. </li></ul></ul></ul>Structured Query Language (SQL)
  22. 22. <ul><li>DML </li></ul><ul><ul><li>INSERT, LOAD DATA statements to populate tables </li></ul></ul><ul><ul><li>SHOW, DESCRIBE statements to view structures </li></ul></ul><ul><ul><li>retrieving data – queries </li></ul></ul><ul><ul><ul><li>SELECT …. FROM …. WHERE …. </li></ul></ul></ul><ul><ul><li>aggregate operators </li></ul></ul><ul><ul><ul><li>COUNT, SUM, AVG, MIN, MAX, DISTINCT </li></ul></ul></ul><ul><ul><ul><li>GROUP BY </li></ul></ul></ul><ul><ul><ul><li>ordering query results with ORDER BY </li></ul></ul></ul>Structured Query Language (SQL)
  23. 23. <ul><li>DML </li></ul><ul><ul><li>matching patterns with LIKE </li></ul></ul><ul><ul><li>joining tables </li></ul></ul><ul><ul><li>sub-queries </li></ul></ul><ul><ul><li>outer joins using LEFT JOIN </li></ul></ul><ul><ul><li>query format </li></ul></ul><ul><ul><li>How joins are processed </li></ul></ul><ul><ul><ul><li>Cartesian product </li></ul></ul></ul>Structured Query Language (SQL)
  24. 24. <ul><li>Views </li></ul><ul><li>Schema </li></ul><ul><li>ANSI/SPARC three-schema architecture standard </li></ul><ul><ul><li>external schema </li></ul></ul><ul><ul><ul><li>user views </li></ul></ul></ul><ul><ul><li>conceptual schema </li></ul></ul><ul><ul><ul><li>single, coherent definition of enterprise data </li></ul></ul></ul><ul><ul><li>internal schema </li></ul></ul><ul><ul><ul><li>physical storage structures </li></ul></ul></ul>Database Systems Architecture
  25. 25. <ul><li>Data independence </li></ul><ul><ul><li>logical </li></ul></ul><ul><ul><li>physical </li></ul></ul><ul><li>Network architecture </li></ul><ul><ul><li>client–server tiered architecture </li></ul></ul><ul><ul><li>distributed databases </li></ul></ul>Database Systems Architecture
  26. 26. Database Systems Performance Issues <ul><li>The ultimate measures of database performance are </li></ul><ul><ul><li>response time to queries </li></ul></ul><ul><ul><li>the speed of updates </li></ul></ul><ul><li>We also need to consider </li></ul><ul><ul><li>data accessibility, security, integrity </li></ul></ul><ul><ul><li>usability </li></ul></ul><ul><ul><li>recoverability </li></ul></ul><ul><li>Physical database design translates conceptual and external schemas into physical designs aimed at storing data in a way that provides adequate performance </li></ul>
  27. 27. <ul><li>Guided by the nature of the data and its intended use </li></ul><ul><li>Tuning the database is often performed during operation but good performance starts with a strong physical design </li></ul><ul><li>Critical decisions during physical design </li></ul><ul><ul><li>choice of storage format – data type </li></ul></ul><ul><ul><li>grouping of attributes into physical records </li></ul></ul><ul><ul><li>arranging similarly structured records in secondary memory </li></ul></ul><ul><ul><li>indexes, clusters, architectures </li></ul></ul><ul><ul><li>strategies for query handling based on indexes, records </li></ul></ul>Physical Database Design
  28. 28. <ul><li>Data volume and usage analysis – workloads </li></ul><ul><li>Choice of data types </li></ul><ul><li>Designing physical records </li></ul><ul><ul><li>page size, blocking factor </li></ul></ul><ul><li>Denormalisation </li></ul><ul><ul><li>combining attributes into a single table </li></ul></ul><ul><ul><li>partitioning a table into several physical records </li></ul></ul><ul><li>Physical file organisation </li></ul><ul><ul><li>sequential, indexed, hashed </li></ul></ul><ul><li>Clusters, indexes </li></ul><ul><li>Improving file access - RAID </li></ul>Physical Database Design
  29. 29. Database Systems Performance <ul><li>Choosing an appropriate database architectures </li></ul><ul><ul><li>hierarchical database model </li></ul></ul><ul><ul><li>network database model </li></ul></ul><ul><ul><li>relational database model </li></ul></ul><ul><ul><li>object-oriented database model </li></ul></ul><ul><ul><li>multidimensional database model </li></ul></ul><ul><li>Optimising query performance </li></ul><ul><ul><li>good query design </li></ul></ul>
  30. 30. <ul><li>Data is viewed as a corporate asset </li></ul><ul><li>As with any asset, management is essential to exploit the resource to the maximum benefit </li></ul><ul><li>Effective management of data provides support for operations and decision making at all organisational levels </li></ul><ul><li>The roles of data administration and database administration have evolved to meet the complex task of </li></ul><ul><ul><li>achieving effective management of data resources </li></ul></ul><ul><ul><li>leveraging those resources to the greatest advantage </li></ul></ul>Information Resource Management
  31. 31. Information Resource Management <ul><li>There are three major roles in information resource management </li></ul><ul><ul><li>data administration </li></ul></ul><ul><ul><ul><li>planning, analysis </li></ul></ul></ul><ul><ul><li>database administration </li></ul></ul><ul><ul><ul><li>physical design and operational use </li></ul></ul></ul><ul><ul><li>application development </li></ul></ul><ul><ul><ul><li>systems design and implementation </li></ul></ul></ul>
  32. 32. Information Resource Management <ul><li>Ineffective data administration leads to poor data utilisation </li></ul><ul><li>New technologies and trends are driving the evolution of the roles of data administrator and database administrator </li></ul><ul><li>Roles of the </li></ul><ul><ul><li>data administrator </li></ul></ul><ul><ul><li>database administrator </li></ul></ul><ul><li>Evolving roles of the DA and DBA </li></ul>
  33. 33. Final Exam <ul><li>3 hour exam, 10 minute reading time </li></ul><ul><li>Ten questions </li></ul><ul><ul><li>1 question consisting of ten short answer questions (10 x 1 mark) </li></ul></ul><ul><ul><li>6 short to medium length questions (1 x 5 marks, 6 x 10 marks) </li></ul></ul><ul><ul><li>ER modelling (10 marks) </li></ul></ul><ul><ul><li>normalisation (15 marks) </li></ul></ul><ul><li>Attempt all questions! </li></ul>
  34. 34. Exam Strategy <ul><li>Know the date, time and location of your exam – it’s your responsibility! </li></ul><ul><li>Know your seat number </li></ul><ul><li>Make sure you have your student ID card with you </li></ul><ul><li>Get to the exam early </li></ul><ul><li>Ensure you have adequate writing materials with you </li></ul><ul><li>No text books or notes allowed </li></ul><ul><li>Relax – there’s really not much to worry about </li></ul><ul><ul><li>whatever you have to do (within reason) to help you relax is ok </li></ul></ul>
  35. 35. Exam Strategy <ul><li>3 hour, 10 minute reading time, 100 marks </li></ul><ul><ul><li>you’ve got 180 minutes to earn 100 marks! </li></ul></ul><ul><li>Convert marks to minutes  1.8 minutes/mark </li></ul><ul><li>Calculate time available for each question </li></ul><ul><li>It is a guide to the amount of effort I expect you to spend on each question </li></ul><ul><li>Once the available time for a question is up, stop writing! </li></ul><ul><li>If you finish a question within the available time, return to any incomplete answers </li></ul><ul><li>Make sure you understand the questions! </li></ul>
  36. 36. Study Strategy <ul><li>Give yourself sufficient time for revision </li></ul><ul><ul><li>don’t wait till the day before the exam to start studying </li></ul></ul><ul><li>Study all topics covered in lectures </li></ul><ul><li>Re-read lecture notes, your notes, text books, tutorial notes </li></ul><ul><li>Do all exercises especially revision exercises </li></ul><ul><li>Attempt previous exams </li></ul><ul><li>Consult tutors or lecturer before exam </li></ul><ul><li>Get plenty of sleep, drink lots of water, eat green vegetables </li></ul><ul><ul><li>it’s not quite time to party yet! </li></ul></ul>

×