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Christoph F. Eick Introduction Data Management Today 1. Introduction to Databases 2. Questionnaire 3. Course Information 4. Grading and Other Things.

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Presentation on theme: "Christoph F. Eick Introduction Data Management Today 1. Introduction to Databases 2. Questionnaire 3. Course Information 4. Grading and Other Things."— Presentation transcript:

1 Christoph F. Eick Introduction Data Management Today 1. Introduction to Databases 2. Questionnaire 3. Course Information 4. Grading and Other Things

2 Christoph F. Eick Introduction Data Management Spring 2003 Schedule COSC 6340  Exams:  Undergraduate Material Review Exam: Th., Feb. 13 (in class)  Midterm Exam: Tu., March 25 (in class)  Final Exam: Tu., May 6, 11a  Qualifying Exam Part2: Fr.,. May 9, 10:30-noon  Project and Graded Home Works  Project1(Feb. 15-March 15), Project2 (March 30-April 20), Homework1 (deadline: Feb. 27; March 11), Homework2 (deadline: April 17)  Last day of lecture: Th., April 24, 2003  Spring Break: March 4+6

3 Christoph F. Eick Introduction Data Management Elements of COSC 6340  I: Basic Database Management Concepts --- Review of basic database concepts, techniques, and languages (4 weeks, Chapters 1-5, 7-11, and 18 of the textbook).  II: Implementation of Relational Operators and Query Optimization (Chapters 12+13, 1.5 weeks)  III: Relational Database Design (1.5 weeks, chapters 15+16,)  IV: Introduction to KDD and Making Sense of Data (Chapters 1, 2, 6, and 7 of the Han/Kamber book centering on data warehouses, OLAP, and data mining). 3 weeks  V: Object-oriented Databases, PL/SQL, Object-relational Database Systems, and SQL3 (1.5 weeks; other material)  VI: Internet Databases and XML (1 week, chapter 22 of the textbook and other teaching material)

4 Christoph F. Eick Introduction Data Management Textbooks for COSC 6340  Required Text: Raghu Ramakrishnan and Johannes Gehrke, Data Management Systems, McGraw Hill, Third Edition, 2002 (complication: the chapter numbers in the new edition are different!!)  Recommended: Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Morgan Kaufman Publishers, 2001, ISBN 1-55860-489-8 (4 chapters will be covered)  Other books with relevant material: Ramez Elmasri and Shamkant Navathe, Fundamentals of Database Systems, Third Edition Addison Wesley ISBN: 0-8053- 1755-4

5 Christoph F. Eick Introduction Data Management Schedule for Part1 of COSC 6340  Jan. 14: Introduction to COSC 6340  Fast Review of Undergraduate Material (Jan. 16-Feb. 13)  Jan. 16: Entity-Relationship Data Model  Jan. 21: Entity-Relationship Data Model  Jan. 23: Relational Data Model  Jan. 28: Mapping E/R to Relations  Jan. 30: Files, B+-trees, and hashing (chapter 8, 9, 10)  Feb. 4: Files, B+-trees, and hashing (chapter 8, 9, 10)  Feb. 6: Relational Algebra and SQL (very brief!!)  Feb. 11: Transaction Management (chapter 18)  Feb. 13: Exam0 (Undergraduate Review Exam)

6 Christoph F. Eick Introduction Data Management Why are integrated databases popular?  Avoidance of uncontrolled redundancy  Making knowledge accessible that would otherwise not be accessible  Standardization --- uniform representation of data facilitating import and export  Reduction of software development (though the availability of data management systems) Integrated Database Bookkeeping Device Car Salesman

7 Christoph F. Eick Introduction Data Management Popular Topics in Databases  Efficient algorithms for data collections that reside on disks (or which are distributed over multiple disk drives, multiple computers or over the internet).  Study of data models (knowledge representation, mappings, theoretical properties)  Algorithms to run a large number of transactions on a database in parallel; finding efficient implementation for queries that access large databases; database backup and recovery,…  Database design  How to use database management systems as an application programmer / end user.  How to use database management systems as database administrator  How to implement database management systems  Data summarization, knowledge discovery, and data mining  Special purpose databases (genomic, geographical, internet,…)

8 Christoph F. Eick Introduction Data Management Data Model Schema (defines a set of database states) Current Database State is used to define

9 Christoph F. Eick Introduction Data Management Schema for the Library Example using the E/R Data Model Many-to-Many1-to-11-to ManyMany-to-1 title author B# when phone name ssn Check_out Person Book (0,35)(0,1)

10 Christoph F. Eick Introduction Data Management Relational Schema for Library Example in SQL/92 CREATE TABLE Book (B# INTEGER, title CHAR(30), author CHAR(20), PRIMARY KEY (B#)); CREATE TABLE Person (ssn CHAR(9), name CHAR(30), phone INTEGER, PRIMARY KEY (ssn)); CREATE TABLE Checkout( book INTEGER, person CHAR(9), since DATE, PRIMARY KEY (B#), FOREIGN KEY (book) REFERENCES Book, FOREIGN KEY (person) REFERENCES Person));

11 Christoph F. Eick Introduction Data Management Referential Integrity in SQL/92  SQL/92 supports all 4 options on deletes and updates.  Default is NO ACTION (delete/update is rejected)  CASCADE (also delete all tuples that refer to deleted tuple)  SET NULL / SET DEFAULT (sets foreign key value of referencing tuple) CREATE TABLE Enrolled (sid CHAR (20), cid CHAR(20), grade CHAR (2), PRIMARY KEY (sid,cid), FOREIGN KEY (sid) REFERENCES Students ON DELETE CASCADE ON UPDATE SET DEFAULT )

12 Christoph F. Eick Introduction Data Management Example of an Internal Schema for the Library Example INTERNAL Schema Library12 references Library. Book is stored sequentially, index on B# using hashing, index on Author using hashing. Person is stored using hashing on ssn. Check_out is stored sequentially, index on since using B+-tree.

13 Modern Relational DBMS Modern DBMS Modern DBMS Support for Web-Interfaces, XML, and Data Exchange Efficient Implementation of Queries (Query Optimization, Join & Selection & Indexing techniques) Transaction Concepts; capability of running many transactions in parallel; support for backup and recovery. Support for special Data-types: long fields, images, html-links, DNA-sequences, spatial information,… Support for higher level user interfaces: graphical, natural language, form-based,… Support for OLAP and Data Warehousing Support for Data Mining operations Support for OO; capability to store operations Support for data- driven computing


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