V-LRN� VIRTUAL LEARNING NETWORK

Block – 5

Unit - 16

Database Resource Mgmt.

Information Systems For Managers

Topics to be covered

16.1 Introduction

16.2 Data as Organizational Resource

16.3 Organizing Data

16.4 DBMS and its Components

16.5 Modeling Data

16.6 Data Types

16.7 Developments in Database Technology

16.8 Database Administrator and the Role

16.9 Critical Success Factor of Data Warehousing

16.10 Summary

Introduction

• A university uses a database to keep student records, large libraries uses a database system to keep track of library and to provide various types of indexing to material by subject, title, author etc. and a bank uses database system to keep records of its customers, employees, loans etc. and many more.
• Businesses normally use a database to keep records of its employees, sales, production etc. All those who keep a collection of records for a common purpose, uses a database.

Introduction (Contd.)

• Therefore, a database system is a collection of programs, which allows storage, modification, and manipulation of information from a database.
• It is a layer of software between the physical database and the user.

Data as Organizational Resource

• Computers came into existence to speed up

the data processing. Computers helped to

manage data.

• We are living in the age of information processing. The ability to acquire accurate and timely data, managing data efficiently.

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• Data is also kept for monitoring the activities

and processes in business.

Data as Organizational Resource (Contd.)

Organizing Data

• In earlier times, data processing was done manually. Organizations appoint a large

number of people called clerks.

• The information technology devices used at that time was forms, ledger books and basic mechanical adding machines.
• The results of such manual operations were obtained at a time when the information was almost out of date (e.g. census).

Organizing Data (Contd.)

• Then some systems were invented in which processing was mostly mechanized.
• IBM and Remington Rand led the development

of punched card technology. Things have

changed considerably with the advent of

computers. There are a few terms that you

need to know about the data organization like

Bit, Byte, field, record, File, database.

• In DBMS, files are either organized sequentially or in an indexed form.

DBMS & its Components

• Database is a collection of related information stored along with the details of interpretation of the data contained.
• For managing the data in the database we need a system called Database Management System. For this, the organization maintains records by combining the data from different sources in an organization. DBMS is a complex piece of software that facilitates a flexible management of the data.

DBMS & its Components (Contd.)

Modeling Data

• Data models can be classified in two classes like Record-based logical Models and Object-based logical models.
• Record-Based logical data models can be classified into Hierarchical Models, Network Models and Relational Models.
• Hierarchical Models capture the intuitive hierarchy of the data elements. IMS belongs to the hierarchical data models.

Modeling Data (Contd.)

• Network Models- Since hierarchical models are unable to represent data items that existing at two different level of hierarchy, network models were proposed.
• The systems built using this model were ADABAS and DBMS-10 on DEC-10 machines.
• Relational Models - The systems built on this data model were dBase, Xbase and ORACLE. Almost all commercial systems presently available like Oracle 8i, 9i, 11, SQLServer, MySQL are built on the relational models.

Modeling Data (Contd.)

• Data modelling is achieved in two levels:

1) E-R modelling that builds the conceptual

model of the data.

2) Normalization, which removes redundancies.

• Object Oriented Logical Models can be of several types. One of them is Entity Relationship model. ER data model is based on the perception of the real world.
• This model allows us to represent the relationships among the objects called entities.

Modeling Data (Contd.)

• Entity- Any real-world object that has certain properties represented by a rectangle e.g.

student is an entity.

• Attribute- Attribute is the properties of an entity, like a student entity can have attribute as student name, student roll no., student class etc. attributes are placed inside the circles and attached to the entities and relationships.
• Relationship- Relationship specifies meaningful relation between two entities. A rhombus represents these with a relation specified in it.

Modeling Data (Contd.)

Data Type

• In database system, for storing the data, each column in the table have a certain type of data.
• For example when we create a table for employee’s personal data, then we may have different fields like name, address, phone, age etc. In this if we take the field “name” then this would of character type and “age” and “phone” are of numeric type.

Developments in Database Technology

• DBMS consists of a collection of interrelated data that is called a database and a collection of programs to manage and access the data.
• An RDBMS is a collection of tables, each of which is assigned a unique name. Each table consists of a set of fields and stores a large set of records.
• A data warehouse is a repository of information

collected from multiple sources, stored under a

unified schema that resides at a single site.

Database Administrator & The Role

• Large and complex databases need a lot of maintenance to work in a proper manner.
• A database administrator (DBA) does this maintenance. DBA is the supervisor of the database and hence have the highest level of expertise. DBA centrally controls the database and administers the overall user community.
• DBA also takes care of the data and controls the database structures. Duties of DBA includes definition control, quality control, update control, access control,recovering from failure / loss etc.

Database Administrator & The Role (Contd.)

Critical Success Factors of Data warehousing (Contd.)

• “A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision-making process’.
• Data warehouse is a central repository for significant pieces of the data that are collected by various business systems. Data from various online transaction processing applications and other sources is organized on the data warehouse for use in decision-making process.

Critical Success Factors of Data warehousing

• A data warehouse is used in applications like data mining, Web mining and a decision support system (DSS).
• Data Warehouse enables the executive, manager or the analyst to make better and faster decisions.It presents the right information in the right place at the right time with the right cost in order to support the right decision.
• A data warehouse should be able to use these data pertaining to different functions.

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Summary