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8/2/2019 Dbms Slides - Uic - 2
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Amity Business School
DBMS
DATABASE MANAGEMENT SYSTEM
& ITS COMPONENTS
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What Exactly Is DBMS?
A database management system (DBMS)is an extremely complex set of software
programs that controls the Organization,Storage & Retrieval of Data in a database& also controls Its security & Integrity.
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DATABASE
It is a complete file system that uses a particular file organization to facilitate
rapid & simultaneous updating of related records, also providing easy & rapidaccess to all stored data.
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TYPES OF DATABASE
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WHAT LED TO THEDEVELOPMENT OF DBMS
The problem arising from the traditional file environment approachbrought forward the development of DBMS i.e.
DATA REDUNDANCY
DATA INCONSISTENCY
DATA ISOLATION
DATA INTEGRITY
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DBMS provided solutions by eliminating these problems and providingwith the following advantages :
1. Reduced complexity of the organizations information systems
environment.
2. Reduced data redundancy & inconsistency
3. Improved maintenance costs.
4. Increased access & availability of data & information.
MAJOR COMPONENTS OF DBMS
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DATA MODEL : It defines theway data are conceptually
structured.
TYPES OF DATA MODEL
A) Hierarchical Database Model :
In this particular model, the database is arranged logically inan inverted tree pattern such thateach database has only one
owner. For example,
Management hierarchy in anorganization
MANY EMPLOYEES BUT ONE MANAGER AT EACH LEVEL :
Searching is fast & efficient in hierarchical database model.
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c) Relational Database Model :
It is based on the simple concept of tables in order to
capitalize on characteristics of rows & columns ofdata. In a relational database, these tables are calledrelations, besides this, each row of data is equivalentto a record and each column of data is equivalent toa field.
NAME TITLE AGE DIVISIO
Smith A. Dir. Accounting 43 CHINA
Jones W. Dir. Total QualityManagement
32 STERNWARE
Lee J. Dir. I.T. 46 CHINA
Durham K. Manager, Production 35 STERNWARE
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EMERGING DATA MODELS
Object-Oriented Database Model :
It is a recent development in database models. Thecentral idea is that of an object i.e. a small amount
of data encapsulated with all the data needed inorder to perform an operation with that data.
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Multidimensional Database Model :
In this model, the data are intimately related & can be viewed & analyzed from different perspectives or dimensions. These dimensionsrepresent the primary views of business data, for
example,
SALE DATA(Dimensions)
Product Geography Time
It represents sales of a specific product, in a
specific market, at a particular time.
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MultidimensionalModel
Dealership
Actual Salesfor Blue &Sports acrossdealers
Sales Volumes
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Data Definition Language:
The data definition language defines what types of
information are in the database & how they will bestructured. It is essentially the link between the logicaland physical structures of the database.
LOGICAL : the way the user views data
PHYSICAL : the way the data is physically stored.
It defines the physical characteristics of each record.
a) the fields within the record
b) Each fields data type
c) Each fields length & logical name
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Data Manipulation Language :
The data manipulation language allows users toretrieve, sort, display & delete the contents of a database & for this very purpose QUERYLANGUAGES are used.
QUERY LANGUAGE :
A query language is a set of commands for creating, updating & accessing data from adatabase.
A i i S h l
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One of the most popular forms of query language is SQL orSTRUCTURED QUERY LANGUAGE . SQL offers the ability to
perform complicated searches with relatively simple statement
such as
SELECT- to specify a desired attribute.
FROMto specify the table to be used
WHEREto specify conditions to apply in the query.For example,
SELECTName, Address, City State, PIN
FROMCustomer
WHERE State = MH
The result would be a list of the names & addresses of allcustomers located in Maharashtra.
A i B i S h l
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Data Dictionary :
The data dictionary stores definitions of data elements
i.e. fields & data characteristics such as individuals, business functions programs & reports that use the data elements as well as the physical representation,responsible parties in the organization i.e. data owners
& security. Because the data dictionary providesstandard definitions for all data elements, the potential for data inconsistency is reduced. In addition, it provides for faster program development because
programmers do not have to create new data names.Data dictionaries also make it easier to modify data &information.
A i B i S h l
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BENEFITS OF DBMS TO CORPORATEWORLD
Data Warehouses :
A data warehouses is a relational or multidimensionalDBMS designed to support management decision making.
Data warehouses are oriented around the major business subjects of the enterprise, such as customer, vendor, product or activity. The data in the warehouse are stored in a single, agreed upon format which provides business users with a Customer centre view of the
companys heterogeneous data.
It provides added value to the companys customers byallowing them to access better information.
A it B i S h l
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Data Marts :
A data-mart is a scaled-down version of a data
warehouse that focuses on a particular subject area. Itis designed to support the unique business requirements of a specific department or businessprocess. A company can have many data marts, each
focused on a subset of the entire firm. Because of its reduced scope, a data mart takes less time to build, costs less and is less complex than anenterprise data warehouse. Therefore, a data mart is
appropriate when a company needs to improve data access in a targeted area, such as the marketingdepartment.
A it B i S h l
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Data Mining :
Data mining provides a means of extracting
previously unknown, predictive information from
the base of accessible data in data warehouses.
Data mining tools use sophisticated, automated
algorithms to discover hidden patterns,
correlations & relationships among organizational
data. These tools are used to predict future trends
& behaviors, allowing businesses to makeproactive, knowledge driven decisions.
Amit B i S h l
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For example, one typical predictive problems is
targeted marketing. Data mining can use data on
past promotional mailings to identify the targets
most likely to maximize the return on the
companys investment in future mailings.
Amity Business School
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