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Data Resource Management Section 1: “Technical Foundations of Database Management” Chapter 5

Data Resource Management Section 1: “Technical Foundations of Database Management” Chapter 5. Outline. Section 1: Technical Foundations of Database Management Database Management Fundamental Data Concepts Database Structures Database Development

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Data Resource Management Section 1: “Technical Foundations of Database Management” Chapter 5

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  1. Data Resource Management Section 1: “Technical Foundations of Database Management” Chapter 5

  2. Outline • Section 1: Technical Foundations of Database Management • Database Management • Fundamental Data Concepts • Database Structures • Database Development • Data planning and Database Design (not required)

  3. Section 1 Technical Foundations of Database Management

  4. Database Management • Data are a vital organizational resource that need to be managed like other important business assets. • Today's business enterprise cannot succeed without quality data about their internal operations and external environment. • In all information systems, data resources must be organized and structured in some logical manner so that they can be accessed easily, processed efficiently, retrieved quickly, and managed effectively. • Database provide a logical organization method and easy access to the data stored in it.

  5. Logical Data Elements • Data may be logically organized into:

  6. Logical Data Elements Character Field(data item) Record File(table, flat file) Database • A single alphabetic, numeric, or other symbol • Grouping of all the fields used to describe the attributes of an entity • Example… payroll records with name, SSN, pay rate • Primary Key. • Consists of a grouping of related characters. • Represents an attribute (characteristic) of some entity(object, person, place, event) • Examples… salary, job title • Group of related records • Integrated collection of logically related data elements • It consolidates records previously stored in separate files into a common pool of data elements that provides data for many applications

  7. Fundamental Data Concepts

  8. Fundamental Data Concepts • The data stored in a database are independent of the application programs using them and of the type of storage devices on which they are stored. • Databases contain data elements describing entities and relationships among entities.

  9. Electric Utility Database Business applications that access the data in the DB

  10. Database Structures • The relationships among the many individual data elements stored in databases are based on one of several logical data structures, or models. • Database management system (DBMS) packages are designed to use a specific data structure to provide end users with quick, easy access to information stored in databases. • Five fundamental database structures: • Hierarchical , network , relational, object-oriented and multidimensional models.

  11. Common Database Structures: Hierarchical • Early mainframe DBMS packages used this structure. • Records arranged in a hierarchy or tree-like structure • Relationships are one-to-many Root Element

  12. Common Database Structures: Network • Can represent more complex logical relationships and is still used by mainframe DBMS packages. • Many-to-many relationships among records.

  13. Common Database Structures: Relational • Most widely used structure • Used by microcomputer DBMS packages, as well as by most midrange and mainframe systems. • Data elements are stored in tables (sometimes referred to as relations). • Row represents a record; column is a field. • DBMS packages based on relational model can relate data in one table with data in another, if both tables share a common data element.

  14. Common Database Structures: Relational • A lot of commercial products exist to create and manage relational models: • Mainframe relational DB applications: • Oracle10g from Oracle • DB2 from IBM • Midrange DB applications: • SQL Server from Microsoft. • The most commonly used DB application for the PC is Microsoft Access.

  15. Common Database Structures: Multidimensional • Variation of relational model that uses multidimensional structures to organize data and express the relationships between them. • Data elements are viewed as being in cubes. Each side of the cube is considered a dimension of the data. • Each dimension represent a different category. • Have become the most popular database structure for the analytical databases that support Online Analytical Processing (OLAP) applications, in which fast answers to complex business quires are expected.

  16. Multidimensional Database Structures

  17. Multidimensional Database Structures

  18. Multidimensional Model

  19. Common Database Structures: Object-Oriented • the object-oriented model is considered one of the key technologies of a new generation of multimedia Web-based applications. • An object consists of • Data values describing the attributes of an entity • Operations that can be performed on the data • Encapsulation Combine data and operations • Inheritance  New objects can be created by replicating some or all of the characteristics of parent objects • OODBMS now is popular in CAD and in multimedia Web-based applications. • Supports complex data types more efficiently than relational databases • Examples: graphic images, video clips, web pages

  20. Common Database Structures: Object-Oriented • major relational DBMS vendors add object-oriented modules to their relational software. • Examples include multimedia object extensions to IBM’s DB2 and Oracle’s object-based “cartridges” for Oracle.

  21. Database Development • Database management package like Microsoft Access or Lotus Approach allow end users to develop the databases they need easily. • Large organizations usually place control of enterprise database development in the hands of (DBA) and other database specialists.

  22. Database Development Database Administrator (DBA) In charge of enterprise-wide database development Improves integrity and security of organizational databases Uses Data Definition Language (DDL) in DBMS to develop and specify data content, relationships, and structure This information is then stored in a database of data definitions and specifications called a data dictionary or metadata repository which is managed by the DBA

  23. Data Dictionary Data Dictionary Directory holds information about the database and the data that it stores (data about data = metadata) Relies on specialized software component to manage a database of data definitions Names and descriptions of all types of data records and their interrelationships Requirements for end users’ access and use of applications Contains information on… Database maintenance Security

  24. Data Dictionary

  25. Database Development • Developing a large DB of complex data types can be a complicated task. • Database administrator and the database design analyst work with end users and system analysts to model the business processes and the data they require. Then they determine: • What data definitions should be included in the DB. • What relationships should exist among the data elements.

  26. Questions ..

  27. Resources .. • Read from Chapter 5 (Section 1)

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