2. Basic Database Terminology
• Database – A collection (or list) of information.
A database is comprised of one or more lists
(called tables) of data organized by columns,
rows, and cells.
• Tables – The view that displays the data base as a
combinations of rows (records) and columns
(fields). The cells contain the bits and pieces of
data for each record in each field. The first row of
a table is reserved for the field names.
3. Basic Database Terminology
• Field names – Identify the different categories in
a database. The top row is reserved for field
names. Examples of field names are First name,
last name, address, city, state, zip, phone number.
• Field – Categories in a database. Fields are
displayed in columns. For Example, in a database,
the zip field contains all the zip codes from each
of the records. These are the bits and pieces of
data.
4. Basic Database Terminology
• Records – Related information that is separated
by columns or fields. A name and address are
considered one record in the database. A second
Name and address are a different record.
• Cells - The intersection of columns and rows that
contain the data for each record
• Data – All of the records of information in a
database including the field names. Data + Field
Names = Records All Records = a Database.
5. Basic Database Terminology
• Objects – Enables you to find, view, display, and print
data differently, based on your needs. The most
commonly used objects are tables, queries, forms and
reports.
Tables show all records in a spreadsheet format
Queries allow you to ask questions of the one or more
tables and show only the information you ask for
Forms display one record at a time
Reports give and organize why of presenting
information.
6.
7. Instance and Schema
Database Instance
The term instance is typically used to describe
a complete database environment, including
the RDBMS software, table structure, stored
procedures and other functionality. It is most
commonly used when administrators describe
multiple instances of the same database. Also
Known As: environment
8. Instance and Schema
Examples: An organization with an
employees database might have three
different
instances: production (used to contain live
data), pre-production (used to test new
functionality prior to release into production)
and development (used by
database developers to create new
functionality).
9. Instance and Schema
SCHEMA
A relation schema can be thought of as the
basic information describing a table or
relation. This includes a set of column names,
the data types associated with each column,
and the name associated with the entire table.
10. Instance and Schema
For example, a relation schema for the
relation called Students could be expressed
using the following representation:
Students(sid: string, name: string, login:string,
age: integer, gpa: real)
There are five fields or columns, with names
and types as shown above.
12. Data Models
A collection of concepts that can be used
to describe the structure of a database
(data types, relationships, and constraints)
basic operations (retrieval and updates)
specify the dynamic aspect or behavior
of a database application( user-defined
operations )
13. Categories of Data Models
• High-level or conceptual data models (common
users)
• low-level or physical data models (describe the
details of how data is stored )
• in between, representational (or implementation)
data models can serve both categories above
14. Conceptual Data Model
• Use concepts such as
– Entities:a real-world object or concept (DEPT)
(COURSE)
– Attributes:property of interest that further describes an
entity (dept no, name, telephone, etc)
– Relationships:interaction among the entities (DEPT)
provides (COURSE)
15. Physical Data Model
• Describes how data is stored in the computer.
• It represents info such as
– record formats
– record orderings
– access path: make search more efficient
16. Representational Data Model
• Used in traditional commercial DMBS
• they include
– Relational Data model
– Network model
– Hierarchical model
17. Schemas
• Is the description of the database (not database itself)
– Specified during database design
– Not expected to change frequently
– A displayed schema is called a schema diagram (Fig 2.1)
• Each object in the schema-such as STUDENT or
COURSE-is a schema construct.
• Schema diagram represents only some aspects of a
schema (name of record type, data element and
some type of constraint)
18.
19. Instances and Database State
• The data in the database at a particular moment in time is
called a database state or snapshot or current set of
occurrences or instances in the database
• When we define a new database we have database state is
empty state (schema specified only in DBMS)
• The initial state when the database is first populated
• Then At any point in time, the database has a current state
• schema evolution: when we need to change the schema
20. The Three-Schema Architecture
• Importance of using DB approach
– insulation of programs and data
– support of multiple user views
– use of a catalog to store the database description (schema).
• The aim is to separate the user application and physical
DB
• schema can be defined into three levels:
– The internal level has an internal schema
– describes the physical storage structure of the database.
– uses a physical data model
21.
22. The Three-Schema Architecture
– The conceptual level has a conceptual schema describing the
structure of the whole database for a community of users.
– It hides the details of physical storage structures and
concentrates on describing entities, data types, relationships,
user operations, and constraints.
– A high-level data model or an implementation data model
can be used at this level.
– The external or view level includes a number of external
schemas or user views describing the part of the db that a
particular user group is interested in and hides the rest of the
db from that user group.
– A high-level data model or an implementation data model
can be used at this level.
23. Data Independence
• Is the capacity to change the schema at one level of a
database system without having to change the schema at
the next higher level.
• Logical data independence: capacity to change the
conceptual schema without having to change external
schemas or application programs.
• Physical data independence: capacity to change the
internal schema without having to change the conceptual
(or external) schemas
24. DBMS Languages
• Data Definition Language DDL: Language to specify
conceptual and internal schemas for the database and any
mappings between the two.
• Storage definition language SDL: used when clear
distinction between conceptual and internal schema.
• view definition language VDL: specify user views and
their mappings to the conceptual schema.
• data manipulation language DML:retrieval, insertion,
deletion, and modification of the data
25. DBMS Languages …..
• SQL relational database language: represents a
combination of DDL, VDL, and DML, as well as
statements for constraint specification and schema
evolution
• There are two main types of DMLs:
– A high-level or nonprocedural DML : specify complex DB
operations. Example SQL(set-at-a-time)
– A low-level or procedural DML: retrieve individual records
or objects from DB and process each separately (record-at-atime).
26. DBMS Interfaces
• Menu-Based Interfaces for Browsing
– menus leads to formulation of a request
• Forms-Based Interfaces
– display a form for each user (insert, select)
– designed for naïve users.
• Graphical User Interfaces (GUI)
– display schema as diagram.
– Utilize both menu and forms.
27. DBMS Interfaces
• Natural Language Interfaces
– Accept requests in native language and attempt to
understand them.
– Refers to words in the schema and (standard words) to
interpret the request.
• Interfaces for Parametric Users (eg tellers)
– goal is to min the number of keystroks required. (use of
function) keys
• Interfaces for the DBA
– creating accounts, system privileges, changing schema,
etc.
28. The Database System
Environment
• DBMS Component Modules (fig 2.3)
–
–
–
–
–
–
–
–
db & DBMS stored in disk controlled by OS.
Stored data manager control access to DBMS
SDM puts data in buffers in main memory
DDL compiler process schema definitions and store it
in meta data.
Run-time-data-proc handles DB accesses @runtime
receive update or retrieve and solve them on the DB
Query-Compiler: handles high level queries: parse,
analyze and interpret uses DB access code.
Precompiler extract DML commands from app program
29.
30. Database System Utilities
• Loading: load existing files into the DB
• Backup: creates backup copy of the DB
• File reorganization: reorganize files for better
performance
• Performance monitoring: monitor DB usage and
provide statistics to DBA
31. Tools, Application Environments
& Communications Facilities
• Case: design phase
• data (information) repository: store catalog info,
design decisions, usage, app program description,
user information
• Application Developer: e.g. power builder. Help
in development of DB design, GUI, query, update
etc.
• Comm Software: allow users remotely to access
the DB
32. Classification of DBManagement
Systems
• Data model:
– relational, object, object-relational, hierarchical, network, and
other.
• Number of users supported by the system.
– Single-user systems and Multiuser systems
• Number of sites over which the database is distributed.
– centralized, distributed DBMS (DDBMS) ,Homogeneous
DDBMSs ,federated DBMS (develop software to access
several autonomous preexisting databases stored under
heterogeneous DBMSs. )
33. Classification of DBManagement
Systems …..
• Cost of the DBMS: 10K-100K. Single 100-3K
• General-purpose vs Special-purpose (When
performance is a primary consideration.
– Example: on-line transaction processing (OLTP)
systems, which must support a large number of
concurrent transactions without imposing excessive
delays. )
