DBMS Concepts

DBMS Tutorial Components of DBMS. Applications of DBMS The difference between file system and DBMS. Types of DBMS DBMS Architecture DBMS Schema Three Schema Architecture. DBMS Languages.

DBMS ER Model

ER model: Entity Relationship Diagram (ERD) Components of ER Model. DBMS Generalization, Specialization and Aggregation.

DBMS Relational Model

Codd’s rule of DBMS Relational DBMS concepts Relational Integrity Constraints DBMS keys Convert ER model into Relational model Difference between DBMS and RDBMS Relational Algebra DBMS Joins

DBMS Normalization

Functional Dependency Inference Rules Multivalued Dependency Normalization in DBMS: 1NF, 2NF, 3NF, BCNF and 4NF

DBMS Transaction

What is Transaction? States of transaction ACID Properties in DBMS Concurrent execution and its problems DBMS schedule DBMS Serializability Conflict Serializability View Serializability Deadlock in DBMS Concurrency control Protocols

Difference

Difference between DFD and ERD

Misc

Advantages of DBMS Disadvantages of DBMS Data Models in DBMS Relational Algebra in DBMS Cardinality in DBMS Entity in DBMS Attributes in DBMS Data Independence in DBMS Primary Key in DBMS Foreign Key in DBMS Candidate Key in DBMS Super Key in DBMS Aggregation in DBMS Hashing in DBMS Generalization in DBMS Specialization in DBMS View in DBMS File Organization in DBMS What Is A Cloud Database What Is A Database Levels Of Locking In DBMS What is RDBMS Fragmentation in Distributed DBMS What is Advanced Database Management System Data Abstraction in DBMS Checkpoint In DBMS B Tree in DBMS BCNF in DBMS Advantages of Threaded Binary Tree in DBMS Advantages of Database Management System in DBMS Enforcing Integrity Constraints in DBMS B-Tree Insertion in DBMS B+ Tree in DBMS Advantages of B-Tree in DBMS Types of Data Abstraction in DBMS Levels of Abstraction in DBMS 3- Tier Architecture in DBMS Anomalies in Database Management System Atomicity in Database Management System Characteristics of DBMS DBMS Examples Difference between Relational and Non-Relational Databases Domain Constraints in DBMS Entity and Entity set in DBMS ER Diagram for Banking System in DBMS ER Diagram for Company Database in DBMS ER Diagram for School Management System in DBMS ER Diagram for Student Management System in DBMS ER Diagram for University Database in DBMS ER Diagram of Company Database in DBMS Er Diagram Symbols and Notations in DBMS How to draw ER-Diagram in DBMS Integrity Constraints in DBMS Red-Black Tree Deletion in DBMS Red-Black Tree Properties in DBMS Red-Black Tree Visualization in DBMS Redundancy in Database Management System Secondary Key in DBMS Structure of DBMS 2-Tier Architecture in DBMS Advantages and Disadvantages of Binary Search Tree Closure of Functional Dependency in DBMS Consistency in Database Management System Durability in Database Management System ER Diagram for Bank Management System in DBMS ER Diagram for College Management System in DBMS ER Diagram for Hotel Management System in DBMS ER Diagram for Online Shopping ER Diagram for Railway Reservation System ER Diagram for Student Management System in DBMS Isolation in DBMS Lossless Join and Dependency Preserving Decomposition in DBMS Non-Key Attributes in DBMS Data Security Requirements in DBMS DBMS functions and Components What is Homogeneous Database? DBMS Functions and Components Advantages and Disadvantages of Distributed Database Relational Database Schema in DBMS Relational Schema Transaction Processing in DBMS Discriminator in DBMS

Defference between Database and Data Warehouse

Database

A database is a collection of related information is called a database. It has some elements that can be mapped to real-world objects. It is designed in such a manner that has all the data for a specific purpose is stored in a single place.

Data Warehouse

It is a complete report accounting for every process and a complete analysis of the organization. It stores both historical and current data of the organization. It is used for making decisions and future predictions.

Basic Difference Between Database and Data Warehouse

  • Database as discussed is a collection of related information put together for a specific purpose while the Database Warehouse contains both historical and cumulative data that can be further used for analysis and prediction.
  • The purpose of the Database is to store the data for reference while the purpose of the Data warehouse is used to study the data.
  • Data stored in the Database is more application based while the data Warehouse data is more subject related. 
  • Database uses Transactional Processing whereas Data warehouse uses Analytical Processing to determine the conclusion from them.
  • Database tables and joins are complex but they are not redundant as the data stored in a database is stored in a single file in a normalised manner while the data in Data Warehouse is simple but redundant as it is de-normalized.
  • Database is designed keeping Entity-Relationship modelling techniques while the Data Warehouses are based on the Data Modelling techniques.

Characteristics of a Database

  • It is a secure way of accessing and storing the data.
  • It is used for performing the create, retrieve, update and delete operation on the data stored.
  • Database enables the various applications to access and alter the data stored at the same time.
  • Database Management System maintains the quality of the data stored in the database by implementing integrity constraints on the data.
  •  Multiple users can access the data stored in the database at the same time, this is called concurrent access of the data.
  • In a database all the data is stored in a single file which prevents data redundancy as the data stored is normalised.
  • We can implement various views of the data for a better understanding.
  • Database system ensures that the atomicity, consistency, isolation and durability of the data is maintained throughout.
  • It acts as isolation between the program and data so that change in one does not affect the other.
  • It maintains the concurrency and the operation on the database occurs in the form of transactions.

Characteristics of a Data Warehouse

  • Data warehouse helps business users to access critical data from some sources all in one place.
  • It ensures that the data stored is consistent even when multiple operations are being performed on it.
  • The data stored from multiple sources is stored in one place and increasing the efficiency of the production process.
  • Data warehouse reduces the TAT (total turnaround time) and makes the analysis of progress easier.
  • Data warehouse makes the data retrieval process quite efficient as all the quality data is stored at this place, it saves them time that would otherwise take to collect information from various sources.
  • Data warehouse we can study the trend of the company since the time of establishment and can make future predictions on that accord.
  • It makes the operation of the business efficient and helps to maintain customer relationships.
  • It isolates the analytical information from the transactional information improving the performance of both the systems.
  • It provides valuable information to the Stakeholders as it is all true and cannot be altered and can be used to analyse various aspects of the business. Data warehouse provides more accurate reports.
  • A data warehouse is subject-oriented, it contains all the information about the organization’s operation and can be used to analyse the performance of the organization.
  • The data be stored in the Data warehouse should be easily understandable and written in a unanimously acceptable manner.
  • A data warehouse is non-volatile, it is an accumulation of historical as well as current data, the previous data is not to be deleted even when the new information is constantly being added to it.

Database Vs Data Warehouse

FeaturesDatabaseDatawarehouse
ObjectiveIt is used to store information.It is used to study the data.
ProcessingIt uses online transaction processingIt uses online analytical processing.
UsageIt performs CRUD operations and keeps up with day to day operationsIt is used to analyse the growth of the business.
Tables and JoinsThey are complex but with no redundant data.They are simple but data may be redundant.
ModellingER modelling is usedData Modelling is used
Data ApplicationUsually, data is collected from one applicationData is gathered from multiple application
Type of DataData is recent and updated continuouslyData stored is historical as well as current.
SummaryData is detailedData stored is to the point.