Transcript Databases
Mgt 20600: IT Management & Applications Databases Tuesday April 4, 2006 Reminders Reading – For today Fundamentals text, Chapter Three, Organizing Data and Information – For next class on April 11th Fundamentals text, Chapter Six, Information and Decision Support Systems Homework – Homework Four Databases Due Thursday, April 14th Next week: Decision Support Systems Databases A well-designed and well-managed database is an extremely valuable tool in supporting decision making Databases are key corporate assets Databases are the foundation for sophisticated analyses that provide business intelligence – What new products to design – How to market to particular customer groups – Which customer groups are the most profitable Traditional Approach to Data Management Traditional approach: separate data files are created for each application Results in data redundancy (duplication) Data redundancy conflicts with data integrity Database Approach to Data Management Database approach: pool of related data is shared by multiple applications Significant advantages over traditional approach Advantages of Database Approach Improved strategic use of data Reduced data redundancy Improved data integrity Easier modification and updating Data and program independence Better access to data and information Standardization of data access A framework for program development Better overall protection of the data Shared data and information resources Disadvantages of the Database Approach More complexity More difficult to recover from a failure More expensive Databases Databases must contain – Accurate information – Right kinds of information – Current information – Information from all organizational functions Database Data Data regarding – Important entities Customers Suppliers Transactions – Each entity will have a number of attributes about which you want to collect and store information Customer address Customer phone number Customer account number Entities, Attributes, Keys Entity: a generalized class of people, places, or things (objects) for which data is collected, stored, and maintained (Table and records) Attribute: a characteristic of an entity (fields) Data item: a value of an attribute (fields) Key: field(s) that identify a record Primary key: field(s) that uniquely identify a record Hierarchy of Data Field: name, number, or characters that describe an aspect of a business object or activity Record: a collection of related data fields File: a collection of related records Database: a collection of integrated and related files Data Modeling and the Relational Database Model When building a database, consider: – Content: What data should be collected, at what cost? – Access: What data should be provided to which users, and when? – Logical structure: How should data be arranged to make sense to a given user? – Physical organization: Where should data be physically located? Data Modeling Building a database requires two types of design – Logical design Shows an abstract model of how data should be structured and arranged to meet an organization’s information needs – Physical design Fine-tunes the logical database design for performance and cost considerations Data Modeling Data model: a diagram of data entities and their relationships Entity-relationship (ER) diagrams: data models that use basic graphical symbols to show the organization of and relationships between data Data Modeling An Entity-Relationship (ER) Diagram for a Customer Order Database The Relational Database Model Relational model: all data elements are placed in two-dimensional tables (relations), which are the logical equivalent of files In the relational model: – Each table represents a data entity – Each row of a table represents a specific instance of a data entity – Columns of the table represent attributes The Relational Database Model A Relational Database Model Creating and Modifying the Database Data definition language (DDL) – Collection of instructions/commands that define and describe data and data relationships in a database – Allows database creator to describe the data and the data relationships that are to be contained in the schema and the subschemas Data dictionary: a detailed description of all the data used in the database Storing and Retrieving Data Logical and Physical Access Paths Providing a User View Schema: description of the entire database User view: user-accessible portion of the database Subschema – Contains a description of a subset of the database – Identifies which users can view and modify the data items in the subset – Is used to create different user views Providing a User View The Use of Schemas and Subschemas Creating and Modifying the Database A Typical Data Dictionary Entry Manipulating Data and Generating Reports Data manipulation language (DML): commands that manipulate the data in a database – Query-By-Example (QBE): a visual approach to developing database queries or requests – Structured Query Language (SQL): ANSI standard query language for relational databases – Database programs can produce reports, documents, and other outputs Manipulating Data Selecting: eliminates rows according to criteria Projecting: eliminates columns in a table Joining: combines two or more tables Linking: relates or links two or more tables using common data attributes Manipulating Data Linking Data Tables to Answer an Inquiry Database Administration Database administrator (DBA): directs or performs all activities to maintain a database environment – Designing, implementing, and maintaining the database system and the DBMS – Establishing policies and procedures – Training employees Selecting a Database Management System Important characteristics of databases to consider: – Size of the database – Number of concurrent users – Performance – Ability to be integrated with other systems – Features of the DBMS – Vendor considerations – Cost of the system