Information Management

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The term that means groups of information that represent the qualitative or quantitative attributes of a variable or set of variables.

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Data

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defined as a refined or processed data that has been transformed into meaningful and useful form of data for specific users.

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Information

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a collection of information that is organized so that it can easily be accessed, managed and updated.

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Database

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a collection of interrelated data and a set of programs to access the data.

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DBMS

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facilitates the process of defining, constructing, manipulating, and sharing databases among various users and applications.

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DBMS

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Database consist of:

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Database

DBMS

Application Program

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Data System Components

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Data

Hardware

Software

User

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a collective system of components that comprise and regulates the group of data, management, and use of data, which consist of software, hardware, people, techniques of handling database, and the data also

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Database Environment

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It is the job of updating, sorting, or validating a datafile.

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File System Data Processing

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A chunk of data

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File

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Ranges of database

PC’s, PDAs, cellphones used in special situations where there is a need to share data among users.

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Personal Database

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Ranges of Database

Designed to support collaboration in a small team (less than 25people)

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Workgroup Database

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Ranges of Database

typically larger than aworkgroup (25-100 people) and more diverse range offunctions.

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Department Database

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Ranges of Database

Scope of the whole organization

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Enterprise Database

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Types to Database

The most intuitive way to visualize this type of relationship is by visualizing an upside down tree of data.

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Hierarchical Database

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Type of Database

This model solves the problem of data redundancy by representing relationships interms of sets rather than hierarchy.

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Network Database

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Types of Database

Uses relations or two-dimensionaltables to store information

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Relational Database

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Types of Database

is a database management system(DBMS) similar to a relational database, but with an object-oriented database model

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Object Relational Database

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is the process of creating a simplified diagram of a software system and the data elements it contains, using text and symbols to represent the data and how it flows

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Data Modelling

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a core data management discipline

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Data Modelling

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It is the typical starting point for data modeling, identifying the various data sets and data flow through the organization.

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Conceptual Model

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Types of Database

Uses relations or two-dimensional tables to store information

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Relational Database

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represents a set of things,persons, or concepts relevant to a business

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Entities

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represents an association between two of the above entities

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Relationships

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a core data management discipline

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Data Modelling

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It describes the specifics of how the logical model will be realized. It is specific to a designated database software system

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Physical Model

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It visually map entities,their attributes and therelationships betweendifferent entities.

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Entity-Relationship Data Modelling

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They consist of fact tables thatcontain data about transactionsor other events and dimensiontables that list attributes of theentities in the fact tables

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Dimensional Modelling

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Typically paired withgraph databases, it'soften used to describedata sets that containcomplex relationships.

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Graph Modelling

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is a set of approved guidelines or framework within an organization.

is a statement that imposes some form of constraint on a specific aspect of the database.

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Business Rule

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Types of Business Rules

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Database-oriented & Application-oriented

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Impose constraints that you can establish within the logical design of the database.

A constraint dictated by the business based on their unique data integrity needs.

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Database-oriented

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Impose constraints that you cannot establish within the logical design of the database.

Are ones that are automatically applied based on the design of a databasae

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Application-oriented

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Refers to the process of hiding irrelevant details from the user

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Data Abstraction

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Three levels of data abstraction

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Logical

Physical

Conceptual

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User and data should not directly interact with each other.

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Data Independence

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This level tells the application about how the data should be shown to the user.

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View Level

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This level tells how the data is actually stored and structured.

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Conceptual or Logical Level

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Tells us that where the data is actually stored; it tells the actual location of the data that is being stored by the user.

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Physical Level or Internal Schema

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Represents the database as a collection of relations. A relation is nothing but a table of values.

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Relational Model

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Each column in a table

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Attribute

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The relations are saved in the table format.

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Tables

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It is nothing but a single row of a table, which contains a single record.

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Tuple

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Represents the name of the relation with its attributes.

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Relation Schema

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The total number of attributes which in the relation is called the degree of the relations

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Degree

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Total number of rows present in the table.

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Cardinality

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Represents the set of values for a specific attribute.

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Column

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A finite set of tuples in the RDBMS system.

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Relation Instance

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Every row has one, two or multiple attributes

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Relation key

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Every attribute has some pre-defined value and scope

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Attribute domain

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Referred to conditions which must be present for a valid relation.

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Relational Integrity Constraints

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Types of Integrity Constraints

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Domain

Key

Referential Integrity

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Can be violated if an attribute value is not appearing in the corresponding domain or it is not of the appropriate data type.

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Domain Constraints

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An attribute that can uniquely identify a tuple in a relation is called the key of the table. the value of the attribute for different tuples in the relation has to be unique.

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Key Constraints

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based on the concept of the foreign keys

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Referential Integrity Constraints

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An important attribute of a relation which should be referred to in other relationships.

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Foreign Key

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Operations in Relational Model

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Insert

Delete

Modify

Select

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More than one such minimal subsets

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Candidate Keys

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True or False

no two tuples can have identical values for key attributes

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true

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True or False

a key attribute can not have NULL values

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True

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Having mutiple copies of same data in the database.

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Redundancy

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If a student detail has to be inserted whose course is not being decided yet then insertion will not be possible till the time course is decided for student.

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Insertion Anomaly

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If the details of student in this table are deleted then the details of college will also get deleted which not occur by common sense.

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Deletion Anomaly

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If the rank of the college changes then changes will have to be all over the database which will be time-consuming and computationally costly.

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Update Anomaly

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the record in table A relates to one, and only one, record in table B and each record in table B relates to one, and only one, record in table A.

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One-to-one Relationship

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a record in table A can relate to zero, one, or many records in table B.

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One-to-many Relationship

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The given tables hold data about employees and the projects to which they are assigned.

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Many-to-Many Relationship

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12 rules of Relational Database by?

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Dr. Edgar F. Codd

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The data stored in a database, may it be user data or metadata, must be a value of some table cell.

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Rule 1: Information Rule

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Every single data element is guaranteed to be accessible logically with a combination of table name, primary-key and attribute name.

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Rule 2: Guaranteed Access Rule

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The null values in a database must be given a systematic and uniform treatment.

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Rule 3: Systematic Treatment of NULL values

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The structure description of the entire database must be stored in an online catalog, known as data dictionary, which can be accessed by authorized users.

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Rule 4: Active Online Catalog

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Collection of metadata is stored in

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Data dictionary or system catalog

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accessed by the DBMS to perform various transactions and data dictionary has the user accessible views that are accessed by the developers, designers or users.

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System Catalogs

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A database can only be accessed using a language having linear syntax that supports data definition, data manipulation, and transaction management operations.

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Rule 5: Comprehensive Data Sub-Language Rule

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All the views of a database, which can theoretically be updated, must also be updatable by the system.

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Rule 6: View Updating Rule

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Types of Views

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User, ALL and DBA

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those table and views which are created by the current user/schema.

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User View

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lists all the tables and views that are owned by the current user as well as those tables and views which it has access.

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ALL View

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will have access to all the tables and views of all the user/schema.

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DBA View

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A database must support high-level insertion, update, and deletion.

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Rule 7: High-Level Insert, Update and Delete Rule

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True or False

DBMS supports relational set operators

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True

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Combines two different results obtained by a query into a single result in the form of a table.

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Union

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Gives the common data values between the two data sets that are intersected.

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Intersection

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takes the two sets and returns the values that are in the first set but not the second set

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Set Difference

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The data stored in database must be independent of the applications that access the database.

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Rule 8: Physical Data Independence

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Must be independent of its user's view.

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Rule 9: Logical Data Independence

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must be independent of the application that uses it.

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Rule 10: Integrity Independence

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The end-user must not be able to see that the data is distributed over various locations.

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Rule 11: Distribution Independence

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If a system has an interface that provides access to low-level records, then the interface must not be able to subvert the system and bypass security and integrity constraints.

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Rule 12: Non-Subversion Rule

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A graphical representation that depicts relationships among people, objects, places, concepts or events within an IT system

it uses in terms of logic and business rules.

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Entity Relationship model or diagram

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lacks of specific details but provides an overview of the scope of the project

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Conceptual Data Model

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Which is more detailed than a conceptual, illustrating specific attributes and relationships among data points.

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Logical Data Model

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which provides the blueprint for a physical manifestation.

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Physical Data Model

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Components of ERD

which are the objects or concepts that can have data stored about them

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Entities

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Components of ERD

does not have a primary key and are dependent on the parent entity.

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Weak Entity

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Components of ERD

has a primary key.

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Strong Entity

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Components of ERD

which are properties or characteristics of entities.

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Attributes

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Components of ERD

An attribute that has multiple values for a single entity at a time.

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Multivalued Attribute

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Components of ERD

If an attribute has two or more other attributes

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Composite Attribute

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Components of ERD

An attribute whose value can be calculated from another attribute.

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Derived Attribute

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Components of ERD

Represented by diamond-shaped box.

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Relationship

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Participation Constraints

each entity is involved in the relationship.

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Total Participation

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Participation Constraints

not all the entities are involved in the relationship.

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Partial Participation

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a high-level data mode that incorporates the extensions to the original ER model.

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Extended Entity Relationship Mode (EER)

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an entity that can be divided into further subtype.

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Super Class

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a process of generalizing an entity which contains generalized attributes or properties of generalized entities.

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Generalization

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Relationship of one super or sub class with more than one super class

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Category or Union

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Represents relationship between a wholeobject and its component

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Aggregation

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It is formed by combining multiple interrelated entities into a single entity object. It is useful way to represent a data model for a large and complex organization.

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Entity Clustering

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For entity integrity rule, each table has a primary key. Primary key cannot have NULL value.

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True

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process of organizing the data in a database.

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Database Normalization

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An attribute is dependent on another attribute if another attribute uniquely identifies it.

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Functional Dependency

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is an unexpected side effect of trying to insert, update, or delete a row.

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Data Anomalies

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used to eliminate or reduce redundancy in database tables.

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Normal Forms

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Divide the base into logical units called tables.

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1NF

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To take data that is only partly dependent on the primary key and enter that data into another table.

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2NF

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An attribute, which is part of the candidate-key, is known as a prime attribute.

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Prime Attribute

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An attribute, which is not a part of the prime-key.

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Non-prime attribute

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Remove the data in the table that is not dependent on the primary key.

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3NF

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Based on functional dependencies that take into account all candidate keys in a relation.

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Boyce-Codd Normal Form (BCNF)

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If no database table instance contains two or more, independent and multivalued data describing the relevant entity.

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4NF

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also known as project join normal form.

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5NF

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a constraint that is similar to FD (functional dependency) or MVD (multivalued dependency).

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Join Dependency

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a language for storing and processing information in a relational database.

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Structured Query Language (SQL)

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SQL was invented in the 1970s based on the relational data model. SEQUEL means?

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Structured English Query Language

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The first vendor to offer a commercial SQL relational database management system.

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Oracle

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consist of rows and columns

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SQL Table

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composed such as identifiers, variables, and search conditions that form a correct SQL statement.

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SQL Statement

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starts by tokenizing, or replacing, some of the words in the SQL statement with special symbols.

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Parser

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The parser verifies that the SQL statement conforms to SQL semantics, or rules, that ensure the correctness of the query statement.

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Correctness

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The parser also validates that the user running the query has the necessary authorization to manipulate the respective data.

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Authorization

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Creates a plan for retrieving, writing, or updating the corresponding data in the most effective manner.

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Relational Engine

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the software component that processes the byte code and runs the intended SQL statement.

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Storage Engine

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are specific keywords or SQL statement that developers use to manipulate the data stored in a relational database.

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SQL Commands

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refers to SQL commands that design the database structure.

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Data Definition Language (DDL)

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consists of instructions for retrieving data stored in relational database.

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Data query language (DQL)

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statements write new information or modify existing records in a relational database.

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Data Manipulation Language (DML)

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to manage or authorize database access for other users.

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Data Control Language (DCL)

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The relational engine use _____ to automatically make database database changes.

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Transaction Control Language (TCL)

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a set of formally defined guidelines of the structured query language.

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SQL Standards

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a cyberattack that involves tricking the database with SQL queries.

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SQL Injection

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an open-source relational database management system offered by oracle.

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MySQL

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SQL vs MySQL

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SQL is a standard language for database creation and manipulation.

MySQL is a relational database program that uses SQL queries.

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refersto non-relational database that don't use tables to store data.

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NoSQL

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is the official name of Microsoft's relational database management system that manipulates data with SQL.

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SQL Server