Management Information Systems Chapter 7: Business Intelligence and Databases

Organizing Data in a Traditional File Environment

• A database is a group of related files, and a file is a group of records of the same type
• A record is a group of related fields, and a field is a group of characters that describes an entity (person, place, thing)
• Attribute: each characteristic or quality describing an entity

The Data Hierarchy

• A computer system organizes data in a hierarchy:
  • Bit: represents either a 0 or a 1
  • Byte: a group of bits that represents one character, number, or symbol
  • Field: a group of related bytes
  • Record: a group of related fields
  • File: a collection of related records
  • Database: a collection of related files

Problems with Traditional File Environment

• Data redundancy: presence of duplicate data in multiple files
• Data inconsistency: same attribute has different values
• Program-data dependence: changes in program require changes to data accessed by program
• Lack of flexibility
• Poor security
• Lack of data sharing and availability

The Database Approach to Data Management

• Object-Oriented DBMS (OODBMS): stores data and procedures as objects
• Hybrid object-relational DBMS: provides capabilities of both OODBMS and relational DBMS
• Databases in the cloud: typically less functionality than on-premises DBs

Capabilities of Database Management Systems

• Data definition capability: specifies structure of database content
• Data dictionary: automated or manual file storing definitions of data elements and their characteristics
• Data manipulation language: used to add, change, delete, and retrieve data from database
• Structured Query Language (SQL): used to manipulate data
• Report generation capabilities: for creating polished reports

Entity-Relationship Diagram

• Used by database designers to document the data model
• Illustrates relationships between entities
• Distributing databases: storing database in more than one place (partitioned or replicated)

Managing Data Resources

• Establishing an information policy: firm's rules, procedures, roles for sharing, managing, standardizing data
• Data administration: firm function responsible for specific policies and procedures to manage data
• Data governance: policies and processes for managing availability, usability, integrity, and security of enterprise data
• Database administration: defining, organizing, implementing, and maintaining database

Ensuring Data Quality

• More than 25% of critical data in Fortune 1000 company databases are inaccurate or incomplete
• Most data quality problems stem from faulty input
• Data quality audit: structured survey of the accuracy and level of completeness of the data in an information system
• Data cleansing: software to detect and correct data that are incorrect, incomplete, improperly formatted, or redundant