Data resource management and DSS

Data Resource Management and
DSS

Database
• Database is a collection of logically related data that are
organized in a way to facilitate easy accessing and processing
of data.
• DATABASE : A collection of data is referred to as database.
• e.g. 1. record of students stored in files
• 2. information stored over internet
•
• DATABASE MANAGEMENT SYSTEM: It is basically a
computer based record keeping system (program).
• e.g. MySQL
• Microsoft Access
• FileMaker
• FoxPro

DATABASE MANAGEMENT SYSTEMS
BASIC CONCEPTS
1. What is a database?
A database is a collection of data which can be used:
• alone, or
• combined / related to other data
to provide answers to the user’s question.

Fundamental Data Concept
• Character: Single alphabetic, numeric, other
symbol
• Field: Column, grouping of Character
• Record: Logical grouping of field attribute
• File(table): a group of related record
• Database: integrated collection of logically
related data element

What Is a DBMS?
• A very large, integrated collection of data.
• Models real-world enterprise.
▫ Entities (e.g., students, courses)
▫ Relationships (e.g., Kritika is taking MIS564)
• A Database Management System (DBMS) is
a software package designed to store and
manage databases.

Contd…
• Character: Basic Logical element which consists of single
alphabet, numeric, symbol.
• Field: Next higher level of data is the field or data item. A field
consists of group of related characters. For example age
• Record: The fields required to describe the attributes of an
entity are grouped to form a record. Record represents a
collection of attributes that describes a single instance of an
entity
• File: A group of related records is a data file. If its
independent of any other files related to it, a single table may
be referred to as a flat file.
• Database: It is an integrated collection of logically related data
elements. A database consolidates records previously stored
in separate files into a common pool of data elements that
provides data for many application.

Data resource management and DSS

Database Systems: Today
From Friendster.com on-lin

Other Ways Databases Make Life Better?
• “Players could finally
sign up for the Star
Wars Galaxies game
last week as Sony
opened up registration
to the public.”
• “Once players got in to
the game they found
that the game servers
were offline because of database problems.”
• “Some players spent hours tuning their in-
game characters only to find that crashes
deleted all their hard work.”
• Source: BBC News Online, July 1, 2003.

Purpose of database :
1. It reduces DATA REDUNDANCY to a large extent.
2. It controls DATA INCONSISTENCY.
3. It facilitate SHARING of data.
4. It ensures DATA SECURITY.
Name D.O.B Fees
Harsh 23/01/1993 Not paid
Amar 04/11/1994 Paid
Devendra 14/06/199
2
Not paid
Harsh 23/01/1993 Not paid
Name D.O.B Fees
Harsh 23/01/199
3
Paid
Amar 04/11/199
4
Paid
Devendra 14/06/199
2
Paid
Harsh 23/01/199
3
Not paid
Data Redundancy Data Inconsistency

2. What is a Database Management System?
A DBMS is a collection of programs which
• provide management of databases
• control access to data
• contain a query language to retrieve information easily

3. Database Design
It is important to design the database in such a way that:
• A specific item can be reached easily
(maximum guarantee that the desired record will be
reached)
• The database can respond to the user’s
different questions easily
(necessary relationships are provided)

•The database occupies minimum storage space
(choosing data types and how to express a certain
concept is important)
•The database contains no unnecessary data
(storing the gross salary is enough, the net salary
can be calculated from the gross salary)
• Data can be added and updated easily
without causing mistakes
(no data redundancy)

Data redundancy
Different and conflicting versions of the same data
e.g. Employee database:
personal info payroll
- ID - ID (relating parameter)
- name - name (causes redundancy)
- address - gross salary

STEPS IN DATABASE DESIGN
• Requirement analysis
What does the user want?
• Conceptual database design
Defining the entities and attributes, and the
relationships between these --> The ER model
• Physical database design
Implementation of the conceptual design using a
Database Management System

TERMINOLOGY
• Entity --> What is this table about? students
• Attribute (Field) --> What items of information are
necessary to keep concerning this entity?
ID, name, department, year, advisor
• Record (Tuple) --> A set of values for each attribute for
one item
20027654 Anil PM 30 Nepal

• Key --> The attribute used to define a required item
who is the of PM?
Types of keys:
* Primary Key: Key used to uniquely identify a record
* Foreign Key: A field in this table which is the Primary
key of another table
• Relationship --> Definitions linking two or more tables

Why Use a DBMS?
• Data independence and efficient access.
• Reduced application development time.
• Data integrity and security.
• Uniform data administration.
• simultaneous access, recovery from crashes.

Why Study Databases??
• Shift from computation to information
▫ at the “low end”: mix up to webspace (a mess!)
▫ at the “high end”: scientific applications
• Datasets increasing in diversity and volume.
▫ Digital libraries, interactive video
• DBMS encompasses most of CS
▫ OS, languages, theory, multimedia, logic
?

Levels of Abstraction
• Many views, single
conceptual (logical)
schema and physical
schema.
▫ Views describe how users
see the data.
▫ Conceptual schema defines
logical structure
▫ Physical schema describes
the files and indexes used.
Physical Schema
Conceptual Schema
View 1 View 2 View 3

Various levels of database implementation (concept of
abstraction)
1. INTERNAL LEVEL (PHYSICAL LEVEL):
It describes how data are actually stored on the storage
medium.
It is closest to database programmer.
Lowest level of database abstraction.
2. CONCEPTUAL LEVEL:
It describes what data are actually stored in database.
It is closest to the database manager.
It is an intermediate level of database abstraction.
3. EXTERNAL LEVEL (VIEW LEVEL):
It describes the way in which the data are viewed by individual
user.

Three levels of data abstraction
View 1 View 2 View 3
Conceptual
level
Physical
level
External level
Internal
Stored-acc. length=60
Account # type=bytes(15) offset=0
Name type=bytes(20)
offset=15
Type type=bytes(10)
offset=35
Amount type=bytes(15)
offset=45
Conceptual
AC_No numeric(15)
AC_Name character(20)
Type character(10)
Amount numeric(15)
View 1
AC_Name
Amount
View 2
AC_No
AC_Name
Type
Amount
Account holder Manager
(DBMS Programmer)
Database
handler
User

Example: University Database Conceptual schema:
 Students(sid: string, name: string, login: string,
age: integer, gpa:real)
 Courses(cid: string, cname:string, credits:integer)
 Enrolled(sid:string, cid:string, grade:string)
 Physical schema:
 Relations stored as unordered files.
 Index on first column of Students.
 External Schema (View):
 Course_info(cid:string,enrollment:integer)

Class Discussion
• Explain the different characteristics and benefits
of DBMS

Data Independence *
• Data independence is the type of data transparency
that matters for a centralised DBMS. It refers to the
immunity of user applications to changes made in the
definition and organization of data. Physical data
independence deals with hiding the details of the
storage structure from user applications.
• Applications insulated from how data is structured and
stored.
• Logical data independence: Protection from changes in
logical structure of data.
• Physical data independence: Protection from changes
in physical structure of data.
* One of the most important benefits of using a DBMS!

Concurrency Control
 Concurrent execution of user programs is essential
for good DBMS performance.
 Because disk accesses are frequent, and relatively
slow, it is important to keep the CPU humming by
working on several user programs concurrently.
 Interleaving actions of different user programs can
lead to inconsistency: e.g., check is cleared while
account balance is being computed.
 DBMS ensures such problems don’t arise: users can
pretend they are using a single-user system.

Structure of a DBMS
• A typical DBMS has a
layered architecture.
• The figure does not
show the concurrency
control and recovery
components.
• This is one of several
possible architectures;
each system has its own
variations.
Query Optimization
and Execution
Relational Operators
Files and Access Methods
Buffer Management
Disk Space Management
DB

Types of Databases
•Hierarchical database
•Network database
•Relational database
•Object-oriented database

HIERARCHICAL DATABASE
• A DBMS is said to be hierarchical if the relationships
among data in the database are established in such a
way that one data item is present as the subordinate
of another one.
• Here subordinate means that items have 'parent-child'
relationships among them. Direct relationships exist
between any two records that are stored consecutively.
The data structure "tree" is followed by the DBMS to
structure the database. No backward movement is
possible/allowed in the hierarchical database.

• Advantage
Hierarchical database can be accessed and updated rapidly
because in this model structure is like as a tree and the
relationships between records are defined in advance. This
feature is a two-edged.
• Disadvantage
This type of database structure is that each child in the tree
may have only one parent, and relationships or linkages
between children are not permitted, even if they make sense
from a logical standpoint. Hierarchical databases are so in
their design. it can adding a new field or record requires that
the entire database be redefined.

NETWORK DATABASE
• A DBMS is said to be a Network DBMS if the
relationships among data in the database are of
type many-to-many.
• The relationships among many-to-many appears in
the form of a network. Thus the structure of
a network database is extremely complicated because
of these many-to-many relationships in which one
record can be used as a key of the entire database. A
network database is structured in the form of a graph
that is also a data structure.

RELATIONAL DATABASE
• A DBMS is said to be a Relational DBMS or RDBMS if
the database relationships are treated in the form of a
table. there are three keys on relational DBMS 1)relation
2)domain 3)attributes.
• A network means it contains fundamentel constructs
sets or records.sets contains one to many
relationship,records contains fields statical table that is
composed of rows and columns is used to organize the
database and its structure and is actually a two
dimension array in the computer memory. A number of
RDBMSs are available, some popular examples are
Oracle, Sybase, Ingress,Informix, Microsoft SQL
Server, and Microsoft Access.

OBJECT-ORIENTED DATABASE
• Object-oriented databases use small, reusable chunks of
software called objects. The objects themselves are stored
in the object-oriented database. Each object consists of two
elements: 1) a piece of data (e.g., sound, video, text, or
graphics), and 2) the instructions, or software programs
called methods, for what to do with the data.
• Object-oriented databases have two disadvantages. First,
they are more costly to develop. Second, most
organizations are reluctant to abandon or convert from
those databases that they have already invested money in
developing and implementing. However, the benefits to
object-oriented databases are compelling. The ability to
mix and match reusable objects provides incredible
multimedia capability.

DATA WAREHOUSE
AND
DATA MINING

Which are our
lowest/highest margin
customers ?
Who are my customers
and what products
are they buying?
Which customers
are most likely to go
to the competition ?
What impact will
new products/services
have on revenue
and margins?
What product prom-
-otions have the biggest
impact on revenue?
What is the most
effective distribution
channel?
A PRODUCER WANTS TO KNOW….

DATA, DATA EVERYWHERE
YET ...
 I can’t get the data I need
 need an expert to get the data
 I can’t understand the data I found
 available data poorly documented
 I can’t use the data I found
 results are unexpected
 data needs to be transformed from
one form to other
 I can’t find the data I need
 data is scattered over the network
 many versions, subtle differences

Evolution of Database Technology
• 1960s:
▫ Data collection, database creation, IMS and network
DBMS
• 1970s:
▫ Relational data model, relational DBMS implementation
• 1980s:
▫ RDBMS, advanced data models (extended-relational,
OO, deductive, etc.) and application-oriented DBMS
(spatial, scientific, engineering, etc.)
• 1990s—2000s:
▫ Data mining and data warehousing, multimedia
databases, and Web databases
44

DATA WAREHOUSE
The data warehouse is that portion of an overall
Architected Data Environment that serves as the
single integrated source of data for processing
information.

CHARACTERISTICS
DATA
WAREHOUSE
Subject
Oriented
Integrated
Non
Volatile
Time
variant
Accessible
Process
Oriented

TERMS RELATED
TO DATA WAREHOUSE
DATA MART
STAGING AREA
OLAP
OLAP TOOLS

Data
Acquisition
Warehouse
Design
Analytical
Data Store
Enterprise
Warehouse
Data Marts
Metadata
Directory
Metadata
Repository
DATA
MANAGEMENT
METADATA
MANAGEMENT
Data
Analysis
Web
Information
Systems
Operational,
External &
other
Databases
COMPONENTS OF
DATAWAREHOUSE SYSTEM

HOW IS THE WAREHOUSE
DIFFERENT?
The data warehouse is distinctly different from
the operational data used and maintained by day-
to-day operational systems. Data warehousing is
not simply an “access wrapper” for operational
data, where data is simply “dumped” into tables
for direct access.

OPERATIONAL DATA
Application oriented
Detailed
Accurate, as of the moment
of access
Serves the clerical
community
Performance sensitive
(immediate response required
when entering a transaction)
Flexible structure; variable
contents
Small amount of data used in
a process
DATA WAREHOUSE
Subject oriented
Summarized
Represents values over time
Serves the managerial
community
Performance relaxed
(immediacy not required)
Static structure
large amount of data used in
a process

• Evolution in organizational use of data warehouses
Organizations generally start off with relatively simple use of data
warehousing. Over time, more sophisticated use of data warehousing
evolves.
The following general stages of use of the data warehouse can be
distinguished:
• Off line Operational Database
Data warehouses in this initial stage are developed by simply copying the
data off an operational system to another server where the processing load
of reporting against the copied data does not impact the operational system's
performance.
• Off line DataWarehouse
Data warehouses at this stage are updated from data in the operational
systems on a regular basis and the data warehouse data is stored in a data
structure designed to facilitate reporting.

• Real Time Data Warehouse
–Data warehouses at this stage are updated
every time an operational system performs a
transaction (e.g. an order or a delivery or a
booking.)
• Integrated DataWarehouse
– Data warehouses at this stage are updated every
time an operational system performs a
transaction. The data warehouses then generate
transactions that are passed back into the
operational systems.

Methods of Minimizing Non-sampling Errors
• Checking the sampling process
• Preparation of questionnaire
• Pilot survey
• Fix procedures
• Use of competent manpower
• Provide information
• Provide training
• Use of experts
• Checking data processing and analysis

Data resource management and DSS

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