Databases - An Introduction PDF

Databases An Introduction M. Shukla  Data and information  Data Dates, values, names etc… For example: “21/04/1998”, “Frank”, ”Luton”, “Derby”  Information  Is data that is...

Databases An Introduction M. Shukla  Data and information  Data Dates, values, names etc… For example: “21/04/1998”, “Frank”, ”Luton”, “Derby”  Information  Is data that is given context, and therefore meaning  Information is about relationships between different bits of data For example: “Frank Derby was born in Luton on 21/04/1998” M. Shukla  Evolution of Database Systems  Collection of information existing over a long period of time  Data/information is a corporate asset of businesses  Data are raw facts, events, transactions that are of concern in a business managed by a DBMS  Information is data that has been processed in such a way as to be useful to the receiver Ted Codd Developed by Codd for IBM in the 70s Turing Award 1981 M. Shukla  Information process Information processing has several phases:  Data capture  Data recording  Data storage  Data processing (update/delete/retrieval)  Data output/presentation M. Shukla  Database Management System(DBMS)  The DBMS is expected to: Allow creation of database structures Give users ability to query data – using appropriate languages Support storage for large data amounts, over long periods of time Provide for recovery in event of failures, errors, intentional misuse etc. Control access to data from many users at once Including security M. Shukla  Evolution and Terminologies Associated with Systems  UML Systems  Database System  Manual and  Classes/Sub Relations/Tables Classes Computerised Rows/Tuples  Associations System Column/Attributes  Attributes Files Objects/Entities  Methods Records Relationships  Operations Data items/Fields  Inheritance Cabinets Systems M. Shukla  Systems essential to every business  Manual and Computerised Files What do they look like How do they work What are their limitations  Database Systems  Databases in our every day  What do they look like  Concepts associated with them  How do they work – the topic of this module M. Shukla  Example Customer Table (or Relation) Attribute Cust_ID F_Name L_Name DOB Record 1 Jake Stephens 20/01/1990 (or Tuple) 2 Medda Suna 15/05/1985 3 Krista Salton 06/12/1998 M. Shukla  Increase in Size Requirements  DBMS originally (1970s): were Banking systems, Airline reservation systems, Corporate record keeping  But more recently: Google stores exabytes of data from Web – specialised structures optimized for search-engine queries Satellites – petabytes of information stored in specialised systems Pictures –taking up much more space than words Video – gigabytes of space each e.g. YouTube 1 Exabyte = 1,000,000,000 GB M. Shukla  Data Size * Not shown is a Nibble which is 4 bits M. Shukla  What do they look like  A database is a collection of related data and the Database Management System (DBMS) is the software that manages and controls access to the database Examples: MS Access, Oracle SQL, MySQL, SQl Server, Foxpro, SQL Lite, MongoDBetc  A database management system allows you to store, retrieve, analyse and print information. M. Shukla  Database Management System components DB Admin Query Transaction DDL User apps compiler manager compiler Execution Logging Concurrency engine recovery control Index/file/ record Buffer Lock Buffers table manager Storage Manager Storage M. Shukla  Pros and Cons of Database Systems  Advantages  Disadvantages Control of data redundancy Complexity Data consistency Size More information from the Cost of DBMSs same amount of data Additional hardware costs Sharing of data Cost of conversion Improved Security Performance Enforcement of standards Higher impact of failure Improved maintenance through data independence Increased concurrency M. Shukla  Database Design  The basic steps;  Decide on the purpose of the Database  Determine the Information Requirements of the Database  Analysis of the system undertaken using various methods and models  Produce a Conceptual Entity Relationship Model for the Database  Logically what should it look like  Top down approach  Normalisation for designing a database  Convert Conceptual Data Model to a Physical Data Model M. Shukla  Database System Studies  Relational Database Modelling – Entity Relationship Models (ERM), UML – Class Models, Normalisation  Relational Database Programming Relational Algebra, MS Access, Structured Query Language (SQL)  Web development – XML etc.  Database Systems Implementation Storage management, query processing, transaction processing  Modern Database Systems  Search engines, data mining, peer-to-peer systems M. Shukla  Summary  Data is a corporate asset.  The purpose of information processing is to help us make decision, ie. personal investment in stocks and shares or for a business  Information processing phases  Manual file systems  Computerised file system  Database system  Concepts and terminologies Data, information, record, field, file, database, DBMS M. Shukla