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Chapter 5

Data Resource Management

Barbara Andress

on 31 December 2013

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Transcript of Chapter 5

Chapter 5
Data Resource Management
Learning Objectives
III. Database Structures (Models)
III. Database Structures (Models)
III. Data Warehouses and Data Mining
III. Data Warehouses
and Data Mining
II. Types of Databases
II. Fundamental Data Concepts
I. Database Management System
III. Database Structures (Models)
III. Database Structures (Models)
Entity Relationship Diagram
I. Data Resource Management
IV. Traditional File Processing
IV. Traditional File Processing
Section 2
Chapter 5
Data Resource Management
Explain the value of implementing data resource management processes and technologies in an organization.

Outline the advantages of a database management approach to managing the data resources of a business, compared with a file processing approach.

Explain how database management software helps business professionals and supports the operations and management of a business.
Provide examples to illustrate each of the
following concepts:

Major types of databases
Data warehouses and data mining
Logical data elements
Fundamental database structures
Database development
Learning Objectives
Data resources must be structured and organized in some logical manner so they can be accessed, processed, retrieved, and managed easily
Character – the most basic logical data element that can be observed, a single alpha or numeric or other symbol, represented by one byte

Field – a grouping of related characters, as a last name or a salary, represents an attribute of some entity General Purpose Application Programs – perform common information processing jobs for end users
II. Fundamental Data Concepts
Record – a grouping of attributes that describe an entity

File – a group of related data records

Database – a collection of logically related data elements
II. Fundamental Data Concepts
Relational Structure – the most widely used database model today; data is represented as a series of two-dimensional tables called Relations; each column is a named attribute of the entity, each row is an unnamed instance of that entity
Relational Operations
Select – create a subset that meets a criterion
Join – temporarily combine two or more tables for comparison
Project – create a subset of the columns in the temporary tables

Multidimensional Structure – variation of the Relational model using multidimensional structures to organize and express relationships
III. Database Structures (Models)
III. Database Structures (Models)
Object-Oriented Structure – combining the data of interest and the processes that act on that data into a structure called an object
Encapsulation – allows complex data types
Inheritance – allows replication of some/all of the characteristics of a parent object in the creation of a child object
III. Database Structures (Models)
How do databases currently focus on data to be stored?
What is suggested as a better away to focus on data warehouses?
What gains do these changes promise?
Database Pioneer Rethinks the Best Way to Organize Data
Database Administrator (DBA) – controls development and administration of the database

Data Definition Language (DDL) – used to specify the contents, relationships, and structure of the database

Data Dictionary – directory containing the metadata
IV. Database Development
Metadata – data about the data

Data Planning and Database Design

Data Modeling (Entity-Relationship Diagrams) – logical models of the data itself; this must be done before choosing the database model

Schema – the physical/internal view of a system

Subschema – the logical/external view of a system
IV. Database Development
IV. Database Development
IV. Database Development
What problem did AAA Missouri have?
How does Melissa solve this problem?
What other benefits does this software provide?
What is the ultimate goal of using this software? What business benefit will that provide?
What is the strength of Hadoop?
What does Hadoop do differently from pervious databases?
Why do we need something different today for handling data in databases?
What does this tell you about the future od handling data?
Data are an organizational
resource that must be managed as any other resource
Types of Databases Used by Organizations and End-Users
I. Data Resource Management
External Databases – outside the firm, free or fee-based
Hypermedia Databases – hyperlinked pages of multimedia
II. Types of Databases
What percentage of retails products are usually out of stock in the U.S.?
What percentage of promotional items are usually out of stock in the U.S.?
What effect does this have on business?
How does Coty deal with these issues?
Case Study and Questions:
Data Warehouse – stores data extracted from other databases

Data Mart – subset of a data warehouse focusing on a single topic, customer, product, etc.

Data Mining – analyzing a data warehouse to reveal hidden patterns and trends
III. Data Warehouses and Data Mining
Components of a Data Warehouse System
Data Mining Extracts Business Knowledge from a Data Warehouse
III. Data Warehouses and Data Mining
According to this case, what is the state of healthcare and BI?
In what ways did the system improve patients’ health?
How does SETMA view the cost and benefits of the system?
Data was stored in independent files without regard to other needs for that data

Problems of File Processing – databases seek to solve these problems

1. Data Redundancy – the same data is kept in more than one location; databases seek to Control (NOT reduce!) Redundancy; this led to Data Inconsistency – same data in multiple locations but the Values were Different
Problems of File Processing – databases seek to solve these problems

Lack of data Integration – data not easily available for ad hoc requests
Data Dependence – data and programs were “tightly coupled”, changing one meant having to change the other
Lack of Data Integrity (Standardization) – data was defined differently by different end users or applications
Are all dating sites the same? For users, what makes the difference between different dating sites?
What is the biggest challenge for eHarmony?
When is the demand for eHarmony’s services greatest? Why might this be? What does this mean from a business perspective?
Consolidate the data from separate files into databases accessible by multiple application programs
Database Management System (DBMS) – a collection of programs to create, maintain, and use (retrieve) data in a database
Database Maintenance – organizational databases need to be updated continually
Application Development – facilitated by the Data Manipulation Language (DML) provided by the DBMS
V. Database Management Approach
Database Interrogation – query (“ask”) the database for information

Query Language – allows ad hoc requests of the database

SQL Queries (Structured Query Language) – standard query language found in many databases

Boolean Logic – 3 logical operators: AND, OR, and NOT

Graphical and Natural Queries – easier methods of structuring SQL statements
V. Database Management Approach
Case Study and Questions
Case Study and Questions:
Case Study and Questions:
Case Study and Questions:
Operational Databases – store detailed data to support business processes and operations

Distributed Databases – many organizations distribute their databases over multiple locations

Replication – complex process of updating distributed data

Duplication – simplified method of updating distributed data
Case Study and Questions
Hierarchical Structure – treelike structure of one-to-many parent-child relationships (each child can have only one parent)
Network Structure – similar to hierarchical but allows many-to-many relationships (a child record can have more than one parent)
Evaluation of Database Structures – databases have grown more complex as needs have changed and grown in complexity
Logical and Physical Database Views
Key Terms:
Logical Data Elements
Key Terms:
Key Terms:
Database Structures
Key Terms:
Hicrarchical Structure
Network Structure
Relational Model Structure
Key Terms:
Key Terms:
Multidimensional Model
Key Terms:
Object Oriented Model
Key Terms:
DBA (Database Administrator)
DDL (Data Definition Languare
Data Dictionary
Key Terms:
Data Modeling
Key Terms:
Data Resource Management
Key Terms:
Operational Databases
Distributed Databases
Key Terms
External Databases
Hypermedia Databases
Key Terms:
Data Warehouse
Data Mart
Data Mining
Key Terms
File Processing
Data Redundancy
Database Management Approach (DBMA)
Database Development
Database Application Development
Database Maintenance
Key Terms:
Lack of Integration
Data Dependence
Key Terms:
Query Language
Report Generator
Structured Query Language
Boolean Logic
Database Maintenance
Application Development
Key Terms:
Database Management System (DBMS)
Database Maintenance
Spplication Development
AAA Missouri: Data Quality Is an Important First Step
Hadoop: Ready for the Large-scale Databases of the Future
Coty: Using Real-Time Analytics to Track Demand
Better Analytics Means Better Care
Online Dating: The Technology Behind Finding Love
Full transcript