This document provides an overview of database management systems and related concepts. It discusses data hierarchy, traditional file processing, the database approach to data management, features and capabilities of database management systems, database schemas, components of database management systems, common data models including hierarchical, network, and relational models, and the process of data normalization.
1. The document discusses the components and overall structure of a database management system (DBMS). It describes the various levels of database architecture including the physical, logical, and external levels.
2. The key components of a DBMS include users, a query processor, storage manager, and data structures. The query processor consists of a DML compiler, DDL interpreter, and query evaluation engine. The storage manager includes modules for authorization, transactions, file management, and buffering.
3. Data models help represent the design of a database and describe entities, attributes, relationships, and constraints. Common models include the entity-relationship model and object-oriented model.
This document provides an overview of database management systems and the normalization process. It begins with definitions of data hierarchy and traditional file processing approaches. It then describes the benefits of a database approach using a DBMS, including features like querying, backup/replication, and security. Components of a DBMS are explained, including data definition languages, data manipulation languages, and the data dictionary. Common data models like hierarchical, network, relational, and object models are also summarized. The document concludes by defining key concepts in normalization like functional dependencies and normal forms, and providing an overview of the normalization process.
The document discusses key concepts related to databases and database management systems (DBMS). It defines what a database is - a collection of interrelated data organized for efficient retrieval, insertion and deletion. It describes characteristics of the database approach like self-describing nature, insulation between programs and data, support of multiple views, and sharing of data. The document also discusses database management systems, advantages and disadvantages of DBMS, types of DBMS like hierarchical, network, relational and object-oriented, database architectures, types of databases like centralized and distributed, data models, and defines what a database schema is.
This document provides an overview of database management systems (DBMS). It discusses what a DBMS is, its architecture and components. A DBMS allows for centralized control of data to reduce redundancy and inconsistencies. It also provides data sharing, integrity, security and recovery mechanisms. The document describes the entity-relationship, network, relational and object-oriented data models. It also discusses the three-tier architecture of a DBMS and the concept of data abstraction through the three schema architecture.
The three-level ANSI-SPARC architecture model provides a conceptual framework for understanding DBMS functionality. It consists of three levels - the external level describing different user views, the conceptual level representing a common view of data, and the internal level describing physical storage. This architecture aims to achieve logical and physical data independence by mapping between levels and allowing changes to lower levels without affecting higher ones.
This document provides an introduction to database management systems. It discusses the types of information needed for businesses, including operational, tactical, and strategic information. It also describes the limitations of traditional file-based systems, such as data redundancy and inconsistencies. The document then introduces database systems and their components, including the database itself and the database management system software. It explains the three levels of the database system architecture - the internal/physical level, conceptual/logical level, and external/view level - and the mappings between them.
The document provides an introduction to database management systems (DBMS). It defines a database as a collection of interrelated data organized for efficient retrieval, insertion and deletion. A DBMS is software that allows users to define, create, maintain and control access to the database. It also discusses the benefits of using a DBMS compared to file systems such as reduced redundancy, improved consistency and security. The key components of a DBMS architecture are also summarized such as the query processor, data dictionary, storage manager and query evaluation engine.
- DBMS stands for Database Management System and is a collection of interrelated data and a set of programs used to access, update, and manage the data. The goal of a DBMS is to provide an environment that is convenient and efficient for retrieving, storing, and manipulating data.
- A database schema represents the logical structure of a database and includes information about the database's tables, fields, relationships, and data types. A database instance is a snapshot of the data stored in a database at a particular point in time.
- There are three levels of data abstraction: the physical level describes how data is physically stored, the logical level describes the logical relationships and structure of data, and the view level describes how different
The document discusses database essentials including database management systems, database applications, the purpose of database systems, data models, database languages, database architecture, and the relational data model. Specifically, it defines what a DBMS is, provides examples of common database applications, describes why databases were developed to address limitations of file processing systems, outlines several data models including the relational model, discusses database languages for defining and manipulating data, presents the client-server architecture of database systems, and explains key concepts of the relational model including tables, tuples, attributes, relations, and domains.
The document provides an introduction to database management systems. It discusses key concepts such as the purpose of DBMSs, data models, database languages, database design, storage and query processing. It also describes common DBMS components like the data dictionary and different types of database users. Overall, the document serves as a high-level overview of database management systems and lays the foundation for further exploration of topics within this domain.
The document provides an introduction to databases including:
- The structure of databases and the hierarchy of data types
- The differences between file-based and database approaches
- The components of a database system including the database, DBMS, applications, users, and tools
- The purposes of using a database including storing, finding, and analyzing information
This document provides an overview of database management systems and related concepts. It discusses the three schema architecture including external, conceptual, and internal schemas. It also covers data models, data definition and manipulation languages, database administrators, keys such as primary keys and foreign keys, and integrity constraints including referential integrity, check constraints, and NOT NULL constraints. The goal of these concepts is to provide a structured and standardized way to define, manipulate, and manage database systems and data.
The document introduces databases and their components. It defines key terms like data, information, database, DBMS, and discusses the evolution from file-based systems to database systems. The main advantages of database systems are minimal data redundancy, sharing of data across systems, improved data consistency when values are stored and updated in one place.
The document provides an introduction to database management systems (DBMS). It defines what a database and DBMS are, and explains that a DBMS allows users to define, create, and manipulate databases for applications. It also discusses some key components of a DBMS environment, including software, hardware, data, procedures, and database access languages like SQL. The document compares traditional file-based data storage with DBMS approaches and outlines some benefits DBMS provide like reduced redundancy, improved data integrity and sharing, and increased accessibility.
The document discusses key concepts related to database management systems (DBMS), including:
1. A DBMS allows for the creation, organization, and management of structured data in a centralized database that can be easily accessed and shared.
2. The three-level architecture of a DBMS separates the database into an internal, conceptual, and external schema to abstract the physical storage from the logical design and user view.
3. Key components of a DBMS include hardware for storage and input/output, software for managing the database, and users who design, implement and query the database system.
The document discusses key concepts related to databases including:
- A database is an organized collection of data stored electronically and accessed via a DBMS.
- Data is logically organized into records, tables, and databases for meaningful representation to users.
- Databases offer advantages like reduced data redundancy, improved data integrity, and easier data sharing.
- Database subsystems include the database engine, data definition language, and data administration.
The document then covers database types, uses, issues, and security concepts.
The document defines key database concepts such as data, information, databases, data modeling, and database management systems (DBMS). It describes what a database is, the basic database structure, and the process of data modeling. It also discusses different types of DBMS software, database designs, and types of databases including relational, distributed, cloud, NoSQL, object-oriented, and graph databases. Additionally, it covers data manipulation using SQL and database advantages like redundancy control and disadvantages like costs.
This document provides an overview of 18 chapters on database systems and management. It begins with a dedication by the author Muhammad Sharif and then outlines each of the 18 chapters, which cover topics such as data types, data models, database design, normalization, transactions, relational algebra, indexing, security, and Oracle database administration. The document also includes acknowledgments thanking contributors and reviewers.
CHAPTER 1 Database system architecture.pptxkashishy2
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The document discusses key concepts related to database management systems (DBMS). It defines a database as a collection of related data used to solve an institution's data management needs. A DBMS is software that allows users to define, create, maintain and control access to the database. The document outlines the differences between data and databases, as well as the characteristics and components of a DBMS, including different views (physical, conceptual, external) of databases. It also discusses data modeling concepts such as entities, attributes, keys, and different types of data models (conceptual, logical, physical).
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Chapter 4 Chapter Relational DB - Copy.pptx
1. LEARNING OBJECTIVES
1. What is a database system, and how does it differ from file-oriented systems?
2. What is a relational database system?
3. How do you design a well-structured set of tables in a relational database?
4. How do you query a relational database system?
2. Databases and Files
1. What is the nature of data stored in an accounting system
For financial reporting, an accounting system must necessarily store data about :
• Assets
• Liabilities and equity
• revenue and expense transactions.
• audit, tax, and control information needs.
• information about budgets, transactions in progress
3. File-Oriented Systems
In early processing systems, an organization’s information was
stored as groups of records in separate files. These file
processing systems constituted of a few data files and many
application programs. Each file called a flat file contained and
processed information for one specific function, such as
accounting or inventory.
4. Limitations of File Processing System:
• Separated and Isolated Data: To make a decision, a user
might need data from two separate files.
• Data Redundancy: Often, the same information was stored
in more than one file. the replication of data caused loss of
data integrity. no one would know which information was
correct.
• Difficulty in representing data from user’s view: it was
difficult to determine relationships between isolated data in
order to meet user requirements
5. Database Systems
• Databases were developed to address the proliferation of
redundant data in the files of systems using the file approach.
• The goal of the database approach is to create an organization-
wide database that stores all of the data needed to operate the
business while linking data across various functions and
eliminating redundancy
• In summary, a database is an organized collection of data about a
set of entities stored with as little data redundancy as possible. A
database’s value comes from the consolidation of data into a
common pool that can serve a variety of users and data
processing applications.
7. The Advantages of Database Systems
• DBMS offers a variety of techniques to store & retrieve data
• Uniform administration procedures for data
• A DBMS uses various powerful functions to store and retrieve data efficiently.
• Offers Data Integrity and Security
• The DBMS implies integrity constraints to get a high level of protection against prohibited
access to data.
• Reduced Application Development Time
• Consume lesser space
• Reduction of redundancy.
• Data independence.
8. A database Management System
(DBMS)
• is the program that manages and controls the data and the
interfaces between the data and the application programs that
use the data stored in the database
• The database administrator (DBA) is responsible for coordinating,
controlling, and managing the database
9. LOGICAL AND PHYSICAL VIEWS OF DATA
The logical view is how people conceptually organize and understand the relationships among data
items.
For example : a sales manager views all customer information as being stored in a table.
The physical view refers to the way data are physically arranged and stored in the
computer system.
The DBMS allows users to access, query, or update the database without reference to how or where
data are physically stored.
Separating the logical and physical views of data also means that users can change their logical view
of data without changing the way data are physically stored
The Database approach provides two separate views of the data: the physical view and the
logical view
11. Physical Schema
It is also known as Internal level.
This is the lowest level of the architecture.
This data is stored in the external hard drives in the form of bits.
This level describes how the data actually stored in the storage device.
This physical level also discuess encryption techniques.
This level is also responsible for allocating space of the data.
12. Conceptual Schema
It is also known as logical level.
The conceptual level is a higher level than the physical level.
This level is maintained by DBA(database administrator).
The whole design of the database such as relationship among data ,schema of data etc.are
described in this level.
It is the middle level between external or internal levels.
13. External Schema
It is also known as view level.
This is highest level architecture and closest to the user.
The user doesn’t need to know the database schema details such as data structure, table
definition etc.
External level is related to the data which is viewed by individual end users.
14. A data dictionary
A data dictionary can be defined as a collection of metadata such as object name, data
type, size, classification, and relationships with other data assets. A data dictionary acts
as a reference guide on a dataset.
15. DBMS Language
A DBMS has several languages :
The data definition language (DDL) :
builds the data dictionary
creates the database
describes logical views for each user, and specifies record or field security constraints
Examples of DDL commands in structured query language (SQL) would be the CREATE, DROP,
and ALTER statements.
16. DBMS Language
A DBMS has several languages :
The data manipulation language (DML)
changes database content, including data, updates, insertions, and deletions
SQL examples
would include INSERT, UPDATE, TRUNCATE, and DROP statements
17. DBMS Language
A DBMS has several languages :
The data query language (DQL)
is a high-level, English-like language that contains powerful, easy-to-use commands that
enable users to retrieve, sort, order, and display data.
SQL examples
the SELECT statement in the SQL language
18. Relational data model
A two-dimensional table representation of data; each row represents a unique entity (record)
and each column is a field where record attributes are stored
Inventory Relation
Attribute/Column Name
Row/Record
/Tuple
Filed
20. Simple Attributes
The Student is an entity represented by a rectangle
It consists of attributes: Roll_no, class, and Age.
We can't further subdivide the Roll_no attribute and even the other two attributes into sub-
attributes.
These attributes are also known as atomic attributes
21. Composite Attributes
The Student is an entity represented by a rectangle
It consists of attributes: Roll_no, class, and Age.
We can't further subdivide the Roll_no attribute and even the other two attributes into sub-
attributes.
These attributes are also known as atomic attributes
22. Basic Requirements Of A Relational
Database
We now turn to the guidelines used to develop a properly structured relational
database.
. Every column in a row must be single valued
Primary keys cannot be null.
Foreign keys, if not null, must have values that correspond to the value of a primary key in
another table
All nonkey attributes in a table must describe a characteristic of the object identified by the
primary key
These four constraints produce a well-structured (normalized) database in which
data are
consistent and data redundancy is minimized and controlled.
23. Two Approaches to Database
Desgine
normalization
begins by assuming that everything is initially stored in one large table. Rules are then
followed to decompose that initial table into a set of tables that are called third normal form
(3NF)
semantic data modeling
the designer uses knowledge of business processes and information needs to create a
diagram that shows what to include in the database. This diagram is used to create a set of
relational tables that are already in 3NF
24. Database Systems And The Future of Accounting
Database systems expand accounting’s ability to produce real-time dynamic reports of all aspects
of the accounting equation
Databases are capturing increasing amounts of transaction data beyond what was captured
through accounting journals and ledgers in double entry accounting.
Presently, data about even the smallest movements of materials in production, inventory
defects, machine operations, and employee effort can be captured in real time.
Management can access the information they need whenever they want it. For example, tables
storing information about assets can include historical costs as well as current replacement
costs, market values, and real-time utilization
25. Chapter Quiz
1. What is each row in a relational database table called?
a. tuple
b. relation
c. attribute
d. anomaly
2. An employee database that consolidates payroll, personnel, and job skills master files is referred to
as
a. data integration.
b. data sharing.
c. data independence.
26. Chapter Quiz
3. Which of the following describes a situation where non-primary key items are stored multiple
times, leading to data inconsistencies?
a. update anomaly
b. insert anomaly
c. delete anomaly
4. The internal-level schema of a database system consists of an individual user’s view of portions
of a database and is also called a subschema.
a. True
b. False
27. Chapter Quiz
5. Which of the following is an individual user’s view of the database?
a. internal-level schema
b. conceptual-level schema
c. external-level schema
d. logical-level schema
6. Which of the following would managers most likely use to retrieve information about sales
during the month of October?
a. DQL
b. DML
c. DSL
d. DDL
28. Chapter Quiz
7. Which of the following is not considered an advantage of a database system?
a. Data are independent of the programs that use them.
b. Integrated data can be shared with authorized users.
c. Data can be stored multiple times in multiple locations.
d. Master files are consolidated and accessible to many application programs.
8. The constraint that all foreign keys must have either null values or the value of a primary key in
another table is referred to as which of the following?
a. referential integrity rule
b. entity integrity rule
c. foreign key value rule
d. null value rule
29. Chapter Quiz
9. The constraint that all primary keys must have non-null data values is referred to as which of the
following?
a. referential integrity rule
b. entity integrity rule
c. normalization rule
d. relational data model rule
10.Which of the following is not a basic requirement of a relational database?
a. Primary keys cannot be null.
b. Every column in a row must be single valued.
c. Foreign keys cannot be null.
d. All non-key attributes in a table must describe a characteristic of the object identified by the
primary key