This course provides a comprehensive introduction to database management systems (DBMS), covering both theoretical concepts and practical skills.…
This course provides a comprehensive introduction to database management systems (DBMS), covering both theoretical concepts and practical skills. …
Learning Mode: Learn at ALC or at Home
Detailed Course Curriculum
Hands-on module breakdown aligned with MKCL production standards and industry requirements.
Introduction
History of DBMS
Purpose of Database Systems
Advantages of using the DBMS approach
Disadvantages of using the DBMS approach
DBMS and its applications: Enterprise Information & Banking and Finance
Example of a Database
Architecture of DBMS
Data Models, Schemas and Instances
Categories of Data Models
Database Schema vs Database State
Data-Manipulation Language (DML)
Data-Definition Language (DDL)
Database Administrators and Database Users
Database Users and User Interfaces
The Database System environment
Database System Utilities
Centralized and Client/Server Architecture for DBMS
High-Level Conceptual Data Models
Introduction to ER Model
Symbols in ER Diagram
Entity types
Entity sets
Attributes
Entity-Set and Keys
Relationship
Relational Model Integrity
CONSTRAINTS
Keys in DBMS
ER DIAGRAM
Naming Conventions
ER Design Issues
Structural constraints Weak entity types
Generalization
Specialization
Relational Model Concepts
Informal Definitions
Formal Definitions
Structure of Relational Databases
Database Schema
Characteristics of Relations
Relational Integrity Constraints
Other Types of Data Constraints
Domains, Attributes, Tuples and Relations
Represent all the Entities and Relationships in Tabular Fashion
PRELIMINARIES
Selection and Projection
Unary Operations
The SELECT Operation
PROJECT Operation
Sequences of Operations and the RENAME Operation with an Example
Set Theory Operations
The UNION, INTERSECTION and MINUS Operations - Examples
The CARTESIAN PRODUCT (CROSS PRODUCT) Operation
Binary Relational Operations and additional relational operations
List of Operators with Purpose
Additional Relational Operations and Generalized Projection
Relational Database Design using ER-to-Relational mapping
Procedure to Create a Relational Schema from an Entity-Relationship (ER)
Mapping of Binary 1: N Relationship Types
Introduction
SQL Data Definition and commands
Operators and Expressions
MYSQL Installation - Demo
Schema and Catalog Concepts in SQL
The CREATE TABLE Command in SQL
Attribute Data Types and Domains in SQL
Specifying Attribute Constraints and Attribute Defaults
Basic Retrieval Queries in SQL
Ambiguous Attribute Names, Aliasing, Renaming and Tuple Variables
Tables as Sets in SQL
Order of Query Execution
Ordering of Query Results
Error Codes
INSERT, DELETE, and UPDATE Statements in SQL
Additional Features of SQL
Create a Table Called Employee with the 2-Column Table Structure
Create Department Table with the 2-Column Table Structure
Queries Using DDL and DML
Design SQL Queries for Suitable Database Application
Using SQL DML Statements
Comparisons Involving NULL and Three-Valued Logic
Nested Queries, Tuples and Set or Multi-Set Comparisons
Correlated Nested Queries
Functions
The EXISTS and UNIQUE Functions in SQL
Explicit Sets and Renaming of Attributes in SQL
Join - Introduction
Cross Join
INNER Join
SELF Join
LEFT OUTER Join
RIGHT OUTER Join and FULL OUTER Join
Join - Examples
Join - Alternate Syntax
Multi Way Join
Design and Develop SQL DDL statements which demonstrate the use of SQL objects such as Table, View, Index, Sequence
Example of a simple query on one relation- Retrieve the birth date and address of the employee
Consider the schema for a Library Database: Write SQL queries to Retrieve details of all books in the library
Consider the schema for an Order Database of Salesman’s: Create a view that finds the salesman who has the customer with the highest order of a day.
Querying (using ANY, ALL, IN, Exists, NOT EXISTS, UNION, INTERSECT, Constraints etc.) - for railway ticketing
Using NESTING OF QUERIES- Retrieve the name and address of all employees who work for the ‘Research’ department.
Design at least 10 SQL queries for suitable database application using SQL DML statements: all types of Join, Sub-Query and View.
Aggregate Functions in SQL
Order by Clause
Grouping
Specifying General Constraints as Assertions in SQL
Perform Query Using Aggregate Function
Write a PL/SQL Block of code
Introduction to Triggers in SQL_1
Assertions vs Triggers
Views in SQL
The DROP Command
The ALTER Command
List Data Definition Languages (DDL) Commands of Base Table and View
List Data Manipulation Language (DML) Of Base Tables and Views
SQL Query Using Grouping Functions
Insert, Delete and Update Triggers
Database Trigger on Library Table
Accessing Databases from Applications
Cursors
Introduction to JDBC
JDBC Classes and Interfaces
JDBC Driver Management
Connections
Executing SQL Statements
Result Sets
Matching Java and SQL Data Types
Exceptions and Warnings
Examining Database Metadata
SQL in Java (SQLJ)
Stored procedures
SQL/PSM
Write a SQL block
Introduction and Objectives to DB Design
Informal Design Guidelines for Relation Schema
Redundant Information in Tuples and Update Anomalies
Generation of Spurious Tuples
Functional Dependencies - Definition and Diagrammatic Notations
Normal Forms based on Primary Keys
Boyce-Codd Normal Form
Multivalued Dependency and Fourth Normal Form
Join Dependencies and Fifth Normal Form
Inference Rules, Equivalence and Minimal Cover
Inference Rules for Functional Dependencies
Equivalence of Sets of Functional Dependencies
Properties of Relational Decompositions
Algorithms for Relational Database Schema Design
Nulls, Dangling Tuples and Alternative Relational Designs
Inclusion and Template Dependencies
Functional Dependencies Based on Arithmetic Functions and Procedures
Domain-Key Normal Form
Features and Types of Transaction Processing
Single-User vs Multiuser Systems
Transactions, Database Items, Read and Write Operations and DBMS Buffers
Transaction and System Concepts
ACID Properties
Commit Point of a Transaction
DBMS Specific Buffer Replacement Policies
Characterizing Schedules Based on Recoverability & Serializability
Transaction Support in SQL
Introduction to Concurrency Control
Two-Phase Locking Techniques for Concurrency Control
Variations of Two-Phase Locking
Dealing with Deadlock and Starvation
Deadlock Detection
Concurrency Control Based on Timestamp Ordering
Multiversion Concurrency Control Techniques
Granularity of Data Items and Multiple Granularity Locking
Recovery Concepts
NO - UNDO or REDO Recovery Based on Deferred Update
Recovery Techniques Based on Immediate Update
Shadow Paging
Database Backup and Recovery from Catastrophic Failures
Working of Key-Value Databases
Features and Functions of Key-Value Databases
Schema Design to Support Key Value
Key - Value Database Vs Cache
The Property Graph Model
Why Data Relationships Matter
Why Other NoSQL Databases don’t Fix the Problem Either
Relational vs Graph Data Modelling Match-Up
Example Data Model - Fraud Detection in Email Communications
Database Query Language
Difference Between Cloud and Database
Cloud Database Deployment Models
Key Benefits of Cloud Databases
When to Use a Cloud Database
Additional Considerations of Cloud Database
Some Large Cloud Providers and Databases
Advantages of Sharding
Shared - Nothing Architecture
Shared - Disk Architecture
Sharding
Sharded Cluster Components
Considerations Before Sharding
Sharded and Non-Sharded Collections and Connecting to a Sharded Cluster
Introduction, Benefits of Business Intelligence Tools
Best data analytics and BI tools
Microsoft Power BI
Tableau
Qlik Sense
Sisense
Best BI tool for developing and deploying analytics apps
Looker – data analytics and BI tool for start-ups and mid-sized businesses
Oracle
Domo BI
SAS Analytics
Relationship of RDBMS Terminology with MongoDB
Sample Document
Key Components of MongoDB Architecture
MongoDB - Advantages
Functionality of MongoDB
MongoDB - CAP Approach
MongoDB - Hierarchical Objects
MongoDB - Environment
MongoDB Processes and Configuration
Install MongoDB on Windows
Install MongoDB on Ubuntu
MongoDB Statistics
CRUD Operations in MongoDB
Data Modelling
Some Considerations While Designing Schema in MongoDB
Create Database
Drop Database
Create Collection
Data Types
Insert Document
Query Document
Update Document
Delete Document
Design and Develop MongoDB Queries using CRUD operations
Projection
Limiting Records
Sorting Records
Aggregation - Examples
Authentication Mechanisms in MongoDB
Bulk Operations with Examples
Indexing
Replication
Program to Implement Aggregation and Indexing in MongoDB
Create Backup of Sharded Cluster
SQL vs Mongo DB Entities
Consistency of Data
Query through API
Exercise on Student Database Agenda
MongoDB – Deployment
Typical MongoDB Deployment, Read Preference and Write Concern_1
Operation Performance and Partition
Relationships
Database References
List of Drivers Supported by DBRefs
MongoDB - Map Reduce
Using MongoDB as a Service: mLab
Execute the Query and Study its Execution Plan
Careers in Database Technology
Eligibility Criteria
• Basic knowledge of computers and keen desire to build skills in this field.
• Open to students, job seekers, and working professionals.
Official Certification
• Official MKCL KLiC Certificate upon successful completion of the course and evaluations.
Work-Centric Learning Approach
• Step 1: Learners are given an overview of the course and its connection to life and work
• Step 2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Step 3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Step 4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
• Step 5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
• Step 6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
• Step 7: Learners are engaged in appreciation of real-life case studies developed by the experts.
• Step 8: Learners are encouraged to proceed from appreciation to imitation of the experts.
• Step 9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Step 10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
• Step 11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
• Step 12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!
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MKCL Certified Program
Admissions Open 2026
Flexible Offline & Hybrid Batches
Course Overview
Duration:120 hours
Track:Software Development
Skill Level:Foundation
Language:English
Mode:Learn at ALC or at Home
Certificate:Official MKCL
Key Course Highlights:
Understand DBMS Fundamentals: Purpose, advantages, and applications of DBMS.
Design and Model Databases: Use ER diagrams and relational schemas.
Proficient in SQL: Write complex SQL queries for data definition, manipulation, and control.
Optimize Databases: Apply normalization and ensure data integrity.
Manage Transactions: Understand ACID properties, concurrency, and recovery.
Explore Advanced DB Concepts: Use triggers, stored procedures, and sharding for optimization.
Work with NoSQL Databases: Gain proficiency in MongoDB operations and data modelling.
Develop Database Applications: Integrate databases with programming languages like Java.
Learn Modern Database Technologies: Understand cloud, key-value, and graph databases.
Use Data Analytics Tools: Work with Power BI, Tableau, and other BI platforms.
Solve Real-World Problems: Apply database techniques to practical scenarios.
Career-Ready Skills: Prepare for roles in database technology and data analytics.