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Data definition language
DDL
Data manipulation language
DML
CREAT SCHEMA AUTHORIZATION
Creates a database schema
CREATE TABLE
Creates a new table in the user's databse schema
NOT NULL
Ensures that a column will not have null values
UNIQUE
Ensures that a column will not have duplicate values
PRIMARY KEY
Defines a primary key for a table
FOREIGN KEY
Defines a foreign key for a table
DEFAULT
Defines a default value for a column ( when no value is give)
CHECK
validates data in an attribute
CREATE INDEX
Creates an index for a table
CREATE VIEW
Creates a dynamic subset of rows and column from on or more tables
ALTER TABLE
Modifies a table's definition (adds, modifies, or deletes attributes or constraints)
CREATE TABLE AS
Creates a new table based on a query in the user's database schema
DROP INDEX
Permanently deletes an index
DROP VIEW
Permanently deletes a view
Authentications
the process DBMS uses to verify that only registered users access the database
Numeric
Number( L, D) or Numeric(L, D)
Character
Char (L)
Date (DATE)
Stores dates in the Julian format
iNSERT: Command to insert data into table
INSERT INTO tablename VALUES();
COMMIT Syntax
COMMIT [WORK];
SELECT Syntax
Command to list the content
SELECT columnlist FROM tablename;
UPDATE
Command to modify data
Syntax - UPDATE tablename SET columnname = expression [, columnname = expression] [WHERE conditionlist];
ROLLBACK
Syntax -ROLLBACK;
Undoes the changes since last COMMIT
command
DELETE
Command to delete
Syntax - DELETE FROM tablename
Subquery
Query embedded/nested inside another query
=
Equal to
<
Less than
<=
less than or equal to
>
greater than
>=
Greater than or equal to
<> or !=
Not equal to
Alias
Alternate name given to a column or table in any SQL statement to improve the readability
The Rule of Precedence
Establish the order in which computations are completed
Performed in this order:
1. Operations within parentheses
2. Power operations
3.Multiplications and divisions
4.Additions and subtractions
OR and AND
Used to link multiple conditional expressions in a WHERE or HAVING clause
OR
requires only one of the conditional expressions to be true
AND
requires all of the conditional expressions to be true
NOT
is used to negate the result of a conditional expression
Boolean algebra
is dedicated to the use to logical operations
Between
Checks whether attribute value is within a range
IS NULL
Checks whether attribute value is null
LIKE
Checks whether attribute value matches given string pattern
IN
Checks whether attribute value matches any value within a value list
EXISTS
Checks if subquery returns any rows
ALTER TABLE command
To make changes in the table structure
Use _______________ command to ADD primary and foreign keys
ALTER TABLE
DROP TABLE
Deletes table from database
Syntax - DROP TABLE tablename;
ORDER BY
clause is useful when listing order is important
Syntax - SELECT columnlist
FROM tablelist
[WHERE conditionlist]
[ORDER BY columnlist [ASC | DESC]];
Cascading order sequence
Multilevel ordered sequence
DISTINCT clause
Produces list of values that are unique
Syntax- SELECT DISTINCT columnlistFROM tablelist;
Recursive query
Table is joined to itself using alias
Systems analysis
Process that establishes need for and extent of information system
Systems development
Process of creating information system
Database development
Process of database design and its implementation
Purpose of Database Initial Study
Analyze company situation
Define problems and constraints
Define objectives
Define scope and boundaries
Database Design
Supports company's operations and objectives
Most critical phase
Ensures final product meets user and system requirements
Virtualization
Creates logical representations of computing resources independent of underlying physical computing resources
Create the databases
Requires the creation of special storage-related constructs to house the end-user tables
Load or convert the data
Requires aggregating data from multiple sources
Full backup/dump
All database objects are backed up in their entirety
Differential backup
Only modified/updated objects since last full backup are backed up
Transaction log backup
Only the transaction log operations that are not reflected in a previous backup are backed up
Software
Software-induced failures may be traceable to the operating system, the DBMS software, application program, or viruses and other malware
Hardware
Hardware-induced failures may include memory chip errors, disk crashes, bad disk sectors, and disk-full errors.
Programming exemptions
Application program or end users may roll back transactions when certain conditions are defined. Programming exemptions can also be caused by malicious or improperly tested code that can be exploited by hackers.
Transactions
The system detects deadlocks and aborts one of the transactions
External factors
Backups are especially important when a system suffers completely destruction from fire, earthquake, flood, or other natural disaster
Minimum data rule
All that is needed is there, and all that is there is needed
Conceptual Design
Designs a database independent of database software and physical details
Conceptual data model
Describes main data entities, attributes, relationships, and constrains
Conceptual Design Steps
1. Data analysis and requirements
2. Entity relationship modeling and normalization
3. Data model verification
4. Distributed database design
Data Analysis and Requirements
"Discover data element characteristics
Obtains characteristics from different sources
Requires thorough understanding of the company's data types and their extent and uses
Take into account business rules
Derived from description of operations
"
Description of Operations
Provides precise, up-to-date, and reviewed description of activities defining an organization's operating environment
Developing the conceptual model using ER diagrams
1. Identify, analyze, and refine the business rules.
2. Identify the main entities, using the results of Step 1.
3. Define the relationships among the entities, using the result of Step 1 and 2.
4. Define the attributes, primary keys, and foreign keys for each of the entities.
5. Normalize the entities.
6. Complete the initial ER diagram.
7. Validate the ER model against the end users' information and processing requirements.
8. Modify the ER model, using the results of Step 7.
Module
Information system component that handles specific business function
Data Model Verification
Verified against proposed system processes Revision of original design Careful reevaluation of entities Detailed examination of attributes describing entities
The ER Model Verification process
1. Identify the ER model's central entity
2. Identify each module and its components.
3. Identify each modules transaction requirements
4. Verify all processes against system requirements.
5. Make all necessary changes suggested in Step 4.
6. Repeat steps 2-5 for all modules
Cohesivity
Strength of the relationships among the module's entities
Module coupling
Extent to which modules are independent to one another
Database fragment
Subset of a database stored at a given location
Distributed Database Design
Portions of database may reside in different physical locations, Ensures database integrity, security, and performance
DBMS Software Selection
Cost
DBMS features and tools
Underlying model
Portability
DBMS hardware requirements
Logical design
Designs an enterprise-wide database that is based on a specific data model but independent of physical-level details
Physical design
Process of data storage organization and data access characteristics of the database
Logical Design Steps
1. Map the conceptual model to logical model components.
2. Validate the logical model using normalization.
3. Validate the logical model integrity constraints.
4. Validate the logical model against user requirements.
Mapping the conceptual model to the relational model
1. Map strong entities.
2. Map supertype/subtype relationships
3. Map weak entities.
4. Map binary relationships.
5. Map higher-degree relationships.
Physical Design Steps
1. Define data storage organization
2. Define integrity and security measures
3. Determine performance measurements
Clustered Tables
Technique that stores related rows from two related tables in adjacent data blocks on disk
Database Role
Set of database privileges that could be assigned as a unit to a user or group