Data Resource Management

DATA RESOURCE MANAGEMENT CHAPTER 5

Presented by: Mr. Naveet Kumar Vankani (11291) Miss. Saba Shahid () Mr. Ghufran Nisar (11153) Mr. Najam-us-Saqib Qasmi (12034) Miss. Iqra Madina (11940)

DATABASE  It is a concept or file organization.  It

consists of related files stored together so that group of data items can be easily accessed or retrieved by those who need them.

Database Management System  It is a software that functions as interface

between users, other programs and the database itself.  It allows the data to be created, maintained, and retrieved.  The database management systems approach was developed to solve the problems of file processing systems.

Types of Database: 1. Operational database 2. Distributed Database 3. External Database 4. Hypermedia Database

Operational Database  It stores detailed data needed to support the

business processes & operations of a company.  It is also called subject area database(SADB), transaction database & production database.  E.g. Customer database, human database, etc.

Distributed Databases  Replication or duplication of copies and

parts of databases to network servers at a variety of websites • Improves database performance at worksites.

External Database  Databases available for a fee from

commercial online services, or free from the Web • Example: hypermedia databases, statistical databases, bibliographic and full text databases • Search engines like Google or Yahoo are external databases

Hypermedia Databases  A hypermedia database contains: • Hyperlinked pages of multimedia • Interrelated hypermedia page elements, rather than interrelated data records

How Data are organized in IS:  Data are logically organized into

characters, fields, records, files. 1. Character: It consists of single alphabetic, numeric, or other symbol. 2. Field: Grouping of related characteristics.

3. Record: It represents a collection of

attributes that describe an entity. 4. File: It is a group of related records. • Any grouping of related records in tabular, or row & column form is called a File. • A single table may be referred to as a Flat file

DATABASE STRUCTURES  The

relationships among many individual data elements stored in database are based on one of the several logical data structures or models.

Types of Database Structure:  Common database structures…

• • • • •

Hierarchical Network Relational Object-oriented Multi-dimensional

Hierarchical Structure  Early DBMS structure  Records arranged in tree-like structure  Relationships are one-to-many

Network Structure  Used in some mainframe DBMS

packages • Many-to-many relationships

Relational Structure    

Most widely used structure Data elements are stored in tables Row represents a record; column is a field Can relate data in one file with data in another, if both files share a common data element

Relational Operations  Select

• Create a subset of records that meet a stated criterion • Example: employees earning more than $30,000  Join • Combine two or more tables temporarily • Looks like one big table  Project • Create a subset of columns in a table

Multidimensional Structure  Variation of relational model

• Uses multidimensional structures to organize data • Data elements are viewed as being in cubes • Popular for analytical databases that support Online Analytical Processing (OLAP)

Multidimensional Model

Object-Oriented Structure  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

Object-Oriented Structure

Object-Oriented Structure  Used in object-oriented database

management systems (OODBMS)  Supports complex data types more efficiently than relational databases • Example: graphic images, video clips, web pages

Database Development  Database development:  Involves data planning, database design and implementation  Creation of database models

Database Administrator (DBA)  In charge of enterprise database development  Improves the integrity and security of organizational databases  Uses Data Definition Language (DDL) to develop and specify data contents, relationships, and structure  Stores these specifications in a data dictionary or a metadata repository

Data Dictionary  A data dictionary

• Contains data about data (metadata) • Relies on specialized software component to manage a database of data definitions  It contains information on.. • The names and descriptions of all types of data records and their interrelationships • Requirements for end users’ access and use of application programs • Database maintenance • Security

Data Planning Process  It a top-down process. • Develop an enterprise model. • Define needs of end user in a business process. • Identify key data elements that are needed to perform their specific business activities. (ERDs)

Database Design Process  It is a data modeling process where the

relationships are identified in a data model that supports a basic business process. •

This model is called “schemas” or “subschema”. • The physical design of data basis.

Database Development

Data Warehouses • A process of centralized data management and

retrieval. • Stores data that has been extracted from other databases in an organization. • Central source of data that has been cleaned, transformed, and catalog. • Data is used for data mining, analytical processing, analysis, research, decision support.

 Data warehouses may be divided into data marts  Subsets of data that focus on specific aspects of a company (department or business process)

Data Mining • Data in data warehouses are analyzed to

reveal hidden patterns and trends • • • • • •

Market-basket analysis to identify new product bundles Find root cause of qualify or manufacturing problems Prevent customer attrition Acquire new customers Cross-sell to existing customers Profile customers with more accuracy