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Colonel Zulfiquer Ahmed Amin
M Phil, MPH, PGD (Health Economics), MBBS
Armed Forces Medical Institute (AFMI)
A database is an organized
collection of data, which can be
used:
• alone, or
• combined /
related to other data
for multiple purposes.
WHAT IS DATABASE (DB)?
DATABASE MANAGEMENT SYSTEMS
A database management
system (DBMS) is a collection of
programs that enables to store,
modify, and extract information
from a database
DB & DBMS
“Database" refers to a set of related data and the
way it is structured or organized.
Access to this data is usually provided by a
"database management system" (DBMS) consisting of an
integrated set of computer software that allows users to
interact with one or more databases and provides access
to all of the data contained in the database (although
restrictions may exist that limit access to particular data)
KEY CHARACTERISTICS OF DBMS
Key characteristics of DBMS are:
Performance
store large volume of database
share data (access)
provide security (authorization)
remove redundancy (Duplication) and
provide concurrent access (different users at the
same time).
Database and Database Management (DBM): Health Informatics
Database and Database Management (DBM): Health Informatics
Database management systems
were developed to handle the
following difficulties of typical file-
processing systems supported by
conventional operating systems:
PURPOSE OF DATABASE MANAGEMENT
PURPOSE OF DATABASE MANAGEMENT
 Data redundancy (Duplication) and inconsistency
 Difficulty in accessing data
 Data isolation – multiple files and formats. Isolating data as
much as possible can keep malware from spreading and
contain it to one unit.
 Integrity problems: Data integrity is the maintenance of, and
the assurance of the accuracy and consistency of, data over
its entire life-cycle.
 Atomicity of updates: In computer science, ACID (Atomicity,
Consistency, Isolation, Durability) of database transactions
intended to guarantee validity even in the event of errors,
power failures, etc. Atomicity requires that each transaction
be "all or nothing": if one part of the transaction fails, then
the entire transaction fails, and the database state is left
unchanged.
 Concurrent access by multiple users
 Security problems
• Data independence: Data independence is the idea that generated
and stored data should be kept separate from applications that use
the data for computing and presentation.
• Efficient data access: DBMS makes use of queries to access data
from the database.
• Data integrity: Data integration means ensuring that the data in the
database is accurate. Incorrect information gets rejected and
cannot be stored in the database.
ADVANTAGES OF A DBMS
● Data administration: Database administration is the function of
managing and maintaining database management systems (DBMS)
software.
● Concurrent access: The ability to gain admittance to a system or
component by more than one user.
● Crash recovery: DBMS is a highly complex system with hundreds
of transactions being executed every second. If it fails or crashes
amid transactions, it is expected that the system would follow
some sort of techniques to recover lost data.
● Controlling redundancy: In a file system, each application has its own data
storage system. That means some of the data may be repeated in each of
these storage system increasing redundancy and wasting storage space. But
when database is centralized, all data is stored only in one place.
● Data Security: With more users being able to access the data, security of
data gains prime importance. Corporations spend a lot of time and energy
to develop DBMS that enforce better data privacy and security policies.
DBMS can enforce access controls to selectively make data visible to certain
classes of users only. Access controls may even decide if a user is allowed to
only retrieve data or if the user can update it too. Usually, databases are
password protected to prevent unauthorized use.
● Reduced application development (RAD) time: In case of a DBMS,
development of a new application using the same database takes very
little time. Once a database is up and running, generally substantially less
time is required to create new applications using DBMS facilities.
● Control data inconsistency: Data inconsistency occurs when the same
data appears in different places. If a change is made in the data at one
place but the same data value in another place is not updated, then it
results in inconsistency. In a DBMS, all applications use the same set of
centralized data. So a change in data needs to be done only in one place
and the change gets updated in all applications using the database.
So why not use them always?
– Expensive/complicated to set up & maintain
– This cost & complexity must be offset by need
– General-purpose, not suited for special-purpose tasks: A common
example is an email system that performs many of the functions of a
general-purpose DBMS such as the insertion and deletion of
messages composed of various items of data or associating messages
with a particular email address; but these functions are limited to
what is required to handle email and don't provide the user with all
of the functionality that would be available using a general-purpose
DBMS.
WHY NOT USE DBMS ALWAYS?
Well-known DBMSs include:
 MySQL
 Microsoft Access
 Oracle
 dBASE
 FoxPro
 IBM DB2
 LibreOffice Base
 MariaDB
 PostgreSQL
 SQLite
 Microsoft SQL Server etc.
DATABASE MANAGEMENT SYSTEMS
 Hierarchical DBMS
 Network DBMS
 Relational DBMS
 Object-oriented DBMS
TYPES OF DBMS
A database model shows the structure of a database, including the
relationships and constraints that determine how data can be stored
and accessed.
Hierarchical database model
In a Hierarchical database model is a data model where the data is
organised like a tree. The structure allows repeating information using
parent/child relationships: each parent can have many children but each
child only has one parent. All attributes of a specific record are listed under
an entity type.
In a database, an entity type is the equivalent of a table; each individual
record is represented as a row and an attribute as a column. Entity types are
related to each other using 1: N mapping, also known as one-to-many
relationships.
In order to retrieve data from a hierarchical database the whole tree needs
to be traversed starting from the root node. This model is recognized as the
first database model created by IBM in the 1960s.
For example, where each student in a school reports to a given
department, the department can be used as a parent record and the
individual students will represent secondary records, each of which links
back to that one parent record in a hierarchical structure.
A record in the hierarchical database
model corresponds to a row (or tuple) in
the relational database model and an entity
type corresponds to a table (or relation).
Network Database Model
The network database model was a progression from the
hierarchical database model and was designed to solve some of that
model's problems, specifically the lack of flexibility. Instead of only
allowing each child to have one parent, this model allows each child
to have multiple parents (it calls the children members and the
parents owners). It addresses the need to model more complex
relationships such as the orders/parts many-to-many relationship
mentioned in the hierarchical article.
As the figure shows, A1 has two members, B1 and B2. B1. is the
owner of C1, C2, C3 and C4. However, in this model, C4 has two
owners, B1 and B2
Relational Database Design
Relational database was proposed by Edgar Codd (of IBM Research) around
1969. It has since become the dominant database model for commercial
applications (in comparison with other database models such as
hierarchical, network and object models). Today, there are many
commercial Relational  Database  Management  System (RDBMS), such as
Oracle, IBM DB2 and Microsoft SQL Server.
A relational database organizes data in tables (or relations). A table is made
up of rows and columns. A row is also called a record (or tuple). A column is
also called a field (or attribute). A database table is similar to a
spreadsheet. However, the relationships that can be created among the
tables enable a relational database to efficiently store huge amount of
data, and effectively retrieve selected data.
The model also accounts for the types of relationships between
those tables, including one-to-one, one-to-many, and many-to-many
relationships.
Object Oriented Database
An object database is a database management system in which
information is represented in the form of objects. Object is the
physical entity which exist in the universe.
- Engineering Database
- Multimedia Database
Database and Database Management (DBM): Health Informatics
It is important to design the database in such a
way that:
 A specific item can be reached easily
 The database can respond to the user’s
different questions easily
 The database occupies minimum storage
space
DATABASE DESIGN
It is important to design the database in such a
way that (cont.):
DATABASE DESIGN
 The database contains no unnecessary
data
 Data can be added and updated easily
without causing mistakes
 Requirement analysis
 Conceptual database design
 Physical database design
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 Entity-
Relation model
STEPS IN DATABASE DESIGN
•Physical database design
Implementation of the conceptual design
using a Database Management System
STEPS IN DATABASE DESIGN
DATA ABSTRACTION
Data abstraction is the reduction of a
particular body of data to a simplified
representation of the whole.
• For the system to be usable, it must retrieve
data efficiently.
• Since many database-systems users are not
computer trained, developers hide the
complexity from users through several levels of
abstraction, to simplify users’ interactions with
the system
DATA ABSTRACTION
Levels of Abstraction
Physical level:
The lowest level of abstraction
describes how the data are actually stored.
The physical level describes complex data
structures in detail.
LEVELS OF ABSTRACTION
Logical level:
•The next-higher level of abstraction describes what
data are stored in the database, and what
relationships exist among those data.
•The logical level thus describes the entire database in
terms of a small number of relatively simple
structures.
LEVELS OF ABSTRACTION
View level:
•The highest level of abstraction describes only part of the entire
database.
•Many users of the database system do not need all this
information; instead, they need to access only a part of the
database.
•The view level of abstraction exists to simplify their interaction
with the system.
LEVELS OF ABSTRACTION
• 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
DB
LEVELS OF ABSTRACTION
• The collection of database at a particular
moment is called the instance of the database
• The overall design of the database is called
the database scheme
INSTANCE AND SCHEMES
• Connect two or more entity sets.
• Represented by diamonds.
Students CoursesTaking
RELATIONSHIPS
Many-many Many-one One-one
MULTIPLICITY OF RELATIONSHIPS
EXAMPLE OF ENTITY-RELATIONSHIP MODEL
customer accountdepositor
National ID customer-street
customer-name
account-number
balancecustomer-city
HOSPITAL DATABASE E-R RELATIONSHIPS
PHARMACY DATABASE E-R RELATIONSHIP
DATA ADMINISTRATION
Data Administration
A high-level function that is responsible for
the overall management of data resources in an
organization, including maintaining corporate-wide
definitions and standards
DATABASE ADMINISTRATION
Database Administration
A technical function that is responsible for
physical database design and for dealing with
technical issues such as security enforcement,
database performance, and backup and recovery
• Data policies, procedures, standards
• Planning
• Data conflict (ownership) resolution
• Managing the information repository
• Internal marketing of DA concepts
DATA ADMINISTRATION FUNCTIONS
• Selection of DBMS and software tools
• Installing/upgrading DBMS
• Tuning database performance
• Improving query processing performance
• Managing data security, privacy, and
integrity
• Data backup and recovery
DATABASE ADMINISTRATION FUNCTIONS
The Data Warehouse is a stable, read-only
database that combines information from
separate systems into one, easy-to-access
location.
DATA WAREHOUSE
DATA WAREHOUSE
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Database and Database Management (DBM): Health Informatics

  • 1. Colonel Zulfiquer Ahmed Amin M Phil, MPH, PGD (Health Economics), MBBS Armed Forces Medical Institute (AFMI)
  • 2. A database is an organized collection of data, which can be used: • alone, or • combined / related to other data for multiple purposes. WHAT IS DATABASE (DB)?
  • 3. DATABASE MANAGEMENT SYSTEMS A database management system (DBMS) is a collection of programs that enables to store, modify, and extract information from a database
  • 4. DB & DBMS “Database" refers to a set of related data and the way it is structured or organized. Access to this data is usually provided by a "database management system" (DBMS) consisting of an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data)
  • 5. KEY CHARACTERISTICS OF DBMS Key characteristics of DBMS are: Performance store large volume of database share data (access) provide security (authorization) remove redundancy (Duplication) and provide concurrent access (different users at the same time).
  • 8. Database management systems were developed to handle the following difficulties of typical file- processing systems supported by conventional operating systems: PURPOSE OF DATABASE MANAGEMENT
  • 9. PURPOSE OF DATABASE MANAGEMENT  Data redundancy (Duplication) and inconsistency  Difficulty in accessing data  Data isolation – multiple files and formats. Isolating data as much as possible can keep malware from spreading and contain it to one unit.  Integrity problems: Data integrity is the maintenance of, and the assurance of the accuracy and consistency of, data over its entire life-cycle.
  • 10.  Atomicity of updates: In computer science, ACID (Atomicity, Consistency, Isolation, Durability) of database transactions intended to guarantee validity even in the event of errors, power failures, etc. Atomicity requires that each transaction be "all or nothing": if one part of the transaction fails, then the entire transaction fails, and the database state is left unchanged.  Concurrent access by multiple users  Security problems
  • 11. • Data independence: Data independence is the idea that generated and stored data should be kept separate from applications that use the data for computing and presentation. • Efficient data access: DBMS makes use of queries to access data from the database. • Data integrity: Data integration means ensuring that the data in the database is accurate. Incorrect information gets rejected and cannot be stored in the database. ADVANTAGES OF A DBMS
  • 12. ● Data administration: Database administration is the function of managing and maintaining database management systems (DBMS) software. ● Concurrent access: The ability to gain admittance to a system or component by more than one user. ● Crash recovery: DBMS is a highly complex system with hundreds of transactions being executed every second. If it fails or crashes amid transactions, it is expected that the system would follow some sort of techniques to recover lost data.
  • 13. ● Controlling redundancy: In a file system, each application has its own data storage system. That means some of the data may be repeated in each of these storage system increasing redundancy and wasting storage space. But when database is centralized, all data is stored only in one place. ● Data Security: With more users being able to access the data, security of data gains prime importance. Corporations spend a lot of time and energy to develop DBMS that enforce better data privacy and security policies. DBMS can enforce access controls to selectively make data visible to certain classes of users only. Access controls may even decide if a user is allowed to only retrieve data or if the user can update it too. Usually, databases are password protected to prevent unauthorized use.
  • 14. ● Reduced application development (RAD) time: In case of a DBMS, development of a new application using the same database takes very little time. Once a database is up and running, generally substantially less time is required to create new applications using DBMS facilities. ● Control data inconsistency: Data inconsistency occurs when the same data appears in different places. If a change is made in the data at one place but the same data value in another place is not updated, then it results in inconsistency. In a DBMS, all applications use the same set of centralized data. So a change in data needs to be done only in one place and the change gets updated in all applications using the database.
  • 15. So why not use them always? – Expensive/complicated to set up & maintain – This cost & complexity must be offset by need – General-purpose, not suited for special-purpose tasks: A common example is an email system that performs many of the functions of a general-purpose DBMS such as the insertion and deletion of messages composed of various items of data or associating messages with a particular email address; but these functions are limited to what is required to handle email and don't provide the user with all of the functionality that would be available using a general-purpose DBMS. WHY NOT USE DBMS ALWAYS?
  • 16. Well-known DBMSs include:  MySQL  Microsoft Access  Oracle  dBASE  FoxPro  IBM DB2  LibreOffice Base  MariaDB  PostgreSQL  SQLite  Microsoft SQL Server etc. DATABASE MANAGEMENT SYSTEMS
  • 17.  Hierarchical DBMS  Network DBMS  Relational DBMS  Object-oriented DBMS TYPES OF DBMS A database model shows the structure of a database, including the relationships and constraints that determine how data can be stored and accessed.
  • 18. Hierarchical database model In a Hierarchical database model is a data model where the data is organised like a tree. The structure allows repeating information using parent/child relationships: each parent can have many children but each child only has one parent. All attributes of a specific record are listed under an entity type. In a database, an entity type is the equivalent of a table; each individual record is represented as a row and an attribute as a column. Entity types are related to each other using 1: N mapping, also known as one-to-many relationships. In order to retrieve data from a hierarchical database the whole tree needs to be traversed starting from the root node. This model is recognized as the first database model created by IBM in the 1960s.
  • 19. For example, where each student in a school reports to a given department, the department can be used as a parent record and the individual students will represent secondary records, each of which links back to that one parent record in a hierarchical structure.
  • 20. A record in the hierarchical database model corresponds to a row (or tuple) in the relational database model and an entity type corresponds to a table (or relation).
  • 21. Network Database Model The network database model was a progression from the hierarchical database model and was designed to solve some of that model's problems, specifically the lack of flexibility. Instead of only allowing each child to have one parent, this model allows each child to have multiple parents (it calls the children members and the parents owners). It addresses the need to model more complex relationships such as the orders/parts many-to-many relationship mentioned in the hierarchical article.
  • 22. As the figure shows, A1 has two members, B1 and B2. B1. is the owner of C1, C2, C3 and C4. However, in this model, C4 has two owners, B1 and B2
  • 23. Relational Database Design Relational database was proposed by Edgar Codd (of IBM Research) around 1969. It has since become the dominant database model for commercial applications (in comparison with other database models such as hierarchical, network and object models). Today, there are many commercial Relational  Database  Management  System (RDBMS), such as Oracle, IBM DB2 and Microsoft SQL Server. A relational database organizes data in tables (or relations). A table is made up of rows and columns. A row is also called a record (or tuple). A column is also called a field (or attribute). A database table is similar to a spreadsheet. However, the relationships that can be created among the tables enable a relational database to efficiently store huge amount of data, and effectively retrieve selected data.
  • 24. The model also accounts for the types of relationships between those tables, including one-to-one, one-to-many, and many-to-many relationships.
  • 25. Object Oriented Database An object database is a database management system in which information is represented in the form of objects. Object is the physical entity which exist in the universe. - Engineering Database - Multimedia Database
  • 27. It is important to design the database in such a way that:  A specific item can be reached easily  The database can respond to the user’s different questions easily  The database occupies minimum storage space DATABASE DESIGN
  • 28. It is important to design the database in such a way that (cont.): DATABASE DESIGN  The database contains no unnecessary data  Data can be added and updated easily without causing mistakes
  • 29.  Requirement analysis  Conceptual database design  Physical database design STEPS IN DATABASE DESIGN
  • 30. •Requirement analysis What does the user want? • Conceptual database design Defining the entities and attributes, and the relationships between these --> The Entity- Relation model STEPS IN DATABASE DESIGN
  • 31. •Physical database design Implementation of the conceptual design using a Database Management System STEPS IN DATABASE DESIGN
  • 32. DATA ABSTRACTION Data abstraction is the reduction of a particular body of data to a simplified representation of the whole.
  • 33. • For the system to be usable, it must retrieve data efficiently. • Since many database-systems users are not computer trained, developers hide the complexity from users through several levels of abstraction, to simplify users’ interactions with the system DATA ABSTRACTION
  • 35. Physical level: The lowest level of abstraction describes how the data are actually stored. The physical level describes complex data structures in detail. LEVELS OF ABSTRACTION
  • 36. Logical level: •The next-higher level of abstraction describes what data are stored in the database, and what relationships exist among those data. •The logical level thus describes the entire database in terms of a small number of relatively simple structures. LEVELS OF ABSTRACTION
  • 37. View level: •The highest level of abstraction describes only part of the entire database. •Many users of the database system do not need all this information; instead, they need to access only a part of the database. •The view level of abstraction exists to simplify their interaction with the system. LEVELS OF ABSTRACTION
  • 38. • 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 DB LEVELS OF ABSTRACTION
  • 39. • The collection of database at a particular moment is called the instance of the database • The overall design of the database is called the database scheme INSTANCE AND SCHEMES
  • 40. • Connect two or more entity sets. • Represented by diamonds. Students CoursesTaking RELATIONSHIPS
  • 42. EXAMPLE OF ENTITY-RELATIONSHIP MODEL customer accountdepositor National ID customer-street customer-name account-number balancecustomer-city
  • 43. HOSPITAL DATABASE E-R RELATIONSHIPS
  • 44. PHARMACY DATABASE E-R RELATIONSHIP
  • 45. DATA ADMINISTRATION Data Administration A high-level function that is responsible for the overall management of data resources in an organization, including maintaining corporate-wide definitions and standards
  • 46. DATABASE ADMINISTRATION Database Administration A technical function that is responsible for physical database design and for dealing with technical issues such as security enforcement, database performance, and backup and recovery
  • 47. • Data policies, procedures, standards • Planning • Data conflict (ownership) resolution • Managing the information repository • Internal marketing of DA concepts DATA ADMINISTRATION FUNCTIONS
  • 48. • Selection of DBMS and software tools • Installing/upgrading DBMS • Tuning database performance • Improving query processing performance • Managing data security, privacy, and integrity • Data backup and recovery DATABASE ADMINISTRATION FUNCTIONS
  • 49. The Data Warehouse is a stable, read-only database that combines information from separate systems into one, easy-to-access location. DATA WAREHOUSE