2005 SPRING CSMUIntroduction to Information Management1 Organizing Data John Sum Institute of Technology Management National Chung Hsing University

2005 SPRING CSMU Introduction to Information Management 2 Data  A necessity for almost any enterprise to carry out its business. Consists of raw facts, and when organized may be transformed into information. Database  A collection of data organized to meet users ’ needs Database Management System (DBMS)  A group of programs that manipulate the database and provide an interface between the database and the user of the database or other application programs.

2005 SPRING CSMU Introduction to Information Management 3 Character Basic building block of information, represented by a byte. Field A group of characters. Record A collection of related fields. Table A collection of related records. Database A collection of integrated and related tables. The Hierarchy of Data

2005 SPRING CSMU Introduction to Information Management 4 Entity  A generalized class of people, places, or things (objects) for which data is collected, stored, and maintained. Attribute  A characteristics of an entity; something the entity is identified by. Keys  A field or set of fields in a record that is used to identify the record. Entities Customer, Employee Attributes Customer name, Employee name Primary key A field or set of fields that uniquely identifies the record. Data Entities, Attributes, and Keys

2005 SPRING CSMU Introduction to Information Management 5 Key FieldAttributes Entities (records) Keys and Attributes

2005 SPRING CSMU Introduction to Information Management 6 The Traditional Approach  Separate files are created and stored for each application program.

2005 SPRING CSMU Introduction to Information Management 7 Data redundancy  Duplication of data in separate files. Lack of data integrity  The degree to which the data in any one file is accurate. Program-data dependence  A situation in which program and data organized for one application are incompatible with programs and data organized differently for another application. Drawbacks to the Traditional Approach

2005 SPRING CSMU Introduction to Information Management 8 The Database Approach  A pool of related data is shared by multiple application programs. Rather than having separate data files, each application uses a collection of data that is either joined or related in the database.

2005 SPRING CSMU Introduction to Information Management 9 The Database Approach

2005 SPRING CSMU Introduction to Information Management 10 Planned Data Redundancy  A way of organizing data in which the logical database design is altered so that certain data entities are combined. Summary totals are carried in the data records rather than calculated from elemental data. Some data attributes are repeated in more than one data entity to improve database performance. Data Modeling and Database Models

2005 SPRING CSMU Introduction to Information Management 11 Data Model  A map or diagram of entities and their relationships. Enterprise data modeling  Data modeling done at the level of the entire organization. Entity-Relationship (ER) diagrams  A data model that uses basic graphical symbols to show the organization of and relationships between data. Data Modeling

2005 SPRING CSMU Introduction to Information Management 12 Attributes Entities Relationship Entity Relationship (ER) Diagram

2005 SPRING CSMU Introduction to Information Management 13 Hierarchical Database Model  A data model in which the data is organized in a top-down, or inverted tree structure. Network Data Model  An expansion of the hierarchical database model with an owner-member relationship in which a member may have many owners. Relational Data Model  All data elements are placed in two-dimensional tables, called relations, that are the logical equivalent of files. Database Models

2005 SPRING CSMU Introduction to Information Management 14 Hierarchical Database Model

2005 SPRING CSMU Introduction to Information Management 15 A Network Data Model Members Owners

2005 SPRING CSMU Introduction to Information Management 16 A Relational Data Model

2005 SPRING CSMU Introduction to Information Management 17 Relational Database Terms Selecting  Data manipulation that eliminates rows according to certain criteria. Projecting  Data manipulation that eliminates columns in a table. Joining  Data manipulation that combines two or more tables. Linked  Related tables in a relational database together.

2005 SPRING CSMU Introduction to Information Management 18 DescriptionDept. NumberManager SSNLastnameHiredate Sales Manual Fiske Linking Data Tables to Answer an Inquiry

2005 SPRING CSMU Introduction to Information Management 19 Logical Access Path Application requires information from the DBMS. Physical Access Path DBMS accesses a storage device to retrieve data. 25 Logical and Physical Access Paths

2005 SPRING CSMU Introduction to Information Management 20 Concurrency Control  A method of dealing with a situation in which two or more people need to access the same record in a database at the same time. Data Manipulation Language (DML)  The commands that are used to manipulate the data in a database. Structured Query Language (SQL)  A standardized data manipulation language. Manipulating Data

2005 SPRING CSMU Introduction to Information Management 21 Structured Query Language

2005 SPRING CSMU Introduction to Information Management Database Output

2005 SPRING CSMU Introduction to Information Management 23 Microsoft Access Lotus Approach Orcale IBM DB2 DBMS Selection Criteria Database size Number of concurrent users Performance Integration Features The vendor Cost Popular DBMS

2005 SPRING CSMU Introduction to Information Management Distributed Databases A database in which the actual data may be spread across several smaller databases connected via telecommunications devices.

2005 SPRING CSMU Introduction to Information Management Distributed Databases

2005 SPRING CSMU Introduction to Information Management 26 Open Database Connectivity (ODBC) A set of standards that ensures software written to comply with these standards can be used with any ODBC- compliant database.

2005 SPRING CSMU Introduction to Information Management 27 The automated discovery of patterns and relationships in a data warehouse. 33 Data Mining