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Understanding Data, Information, and Database Management Systems

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cullen
18 diapositives · 374 Views · Oct 22, 2014

In today's digital landscape, understanding the distinction between data and information is crucial. Data represents unprocessed facts and figures, while information is data organized meaningfully for interpretation and use. A Database Management System (DBMS) efficiently manages these data structures, providing integrity, security, and high performance. With 85% of data being unstructured and growing, mastering database design and manipulation is essential for effective data management and knowledge generation. This overview discusses the fundamental concepts of data, information, and the significance of DBMS in organizations.

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  1. Database System I Gde Dharma N

  2. Fenomena “Information Overload” “The percentage of unstructured data is 85% of the total and growing..” ---Delphi Group Survey, 2008

  3. Data VS Information : What is the difference?

  4. What is Data? • Data can be defined in many ways. • Data is a collection of facts, such as values or measurements. • Data can be defined in many ways. Information science defines data as unprocessed information. • It can be numbers, words, measurements, observations or even just descriptions of things.

  5. What is Information? • Information is data that have been organized and communicated in a coherent and meaningful manner. • Data is converted into information, and information is converted into knowledge. • Knowledge; information evaluated and organized so that it can be used purposefully.

  6. Universe of Discourse • A database is a model of some aspect of the reality of an organisation. • It is conventional to call this reality a universe of discourse (UoD), or a domain of discourse. Universe of Discourse Database Design Database Scheme

  7. What is Database? • A Databaseis any collection of data. • Models a real-world enterprise • A DBMSis a software system designed to maintain a database. • We use a DBMS when • there is a large amount of data • security and integrity of the data are important • many users access the data concurrently

  8. Nature of Database • Factbases • Datum • Persistence • Intensional dan Extensional Parts • Integrity • Redudancy • Transactions • Integrity Constraints

  9. Data Model • Hierarchy Data Model • Network Data Model • Relational Data Model

  10. DBMS Approach • Top-Down Approach, start making database with planning stage. Example : Entity Relationship Diagram. • Bottom-Up Approach, used to transform from traditional system or form to database.

  11. Why use a DBMS? • Without a DBMS, we’d have : Access by a collection of ad hoc programs Users of the data There is no control or coordination of what these program do with the data Data stored as bits on disk organized as files

  12. Why use a DBMS? • With a DBMS, we have : Application Users of the data DBMS DBMS provide control and coordination to protect the data. Data stored as bits on disk organized as files

  13. DBMS Advantage • High Performance for large data. • Data Integrity. • Data Independence. • Centralization of data. • Data Security more flexible.

  14. Main Component of Database • Hardware • Software • Data • User

  15. Layers of Data Abstraction View 1 View 2 View 3 External Layer Conceptual Schema / Internal Schema / Logical Schema Logical Layer Database File Physical Layer

  16. Functional Component of Database • Database Manager • File Manager • Disk Manager

  17. Database Development Life Cycle

  18. Thank you for your attention. • Any Question?????  