Study transactions, indexing, normalization, and database design.
Learning Mode: Learn at ALC or at Home
Detailed Course Curriculum
Hands-on module breakdown aligned with MKCL production standards and industry requirements.
PL/SQL Block of Code
SQL Query Using Aggregate Functions_1
SQL Query Using Aggregate Functions_2
SQL Query Using Aggregate Functions_3
SQL Query Using Aggregate Functions_4
Introduction to Triggers in SQL_1
Introduction to Triggers in SQL_2
Introduction to Triggers in SQL_2
Assertions vs Triggers
The DROP Command
The ALTER Command
Example on Assertions
List Data Definition Languages (DDL) Commands of Base Table and View
List Data Definition Languages (DDL) Commands of Base Table and View
List Data Manipulation Language (DML) Of Base Tables and Views_1
List Data Manipulation Language (DML) Of Base Tables and Views_2
Exercise on Data Manipulation Language (DML) Of Base Tables and Views_1
Exercise on Data Manipulation Language (DML) Of Base Tables and Views_1
Exercise on Data Manipulation Language (DML) Of Base Tables and Views_2
Exercise on Data Manipulation Language (DML) Of Base Tables and Views_2
Examples Using Grouping Functions
Examples Using Grouping Functions
SQL Query Using Grouping Functions
Insert, Delete and Update Triggers
Database Trigger on Library Table
Database Application Development
Accessing Databases from Applications
Accessing Databases from Applications
Cursors
Cursors
Basic Cursor Definition and Usage
Basic Cursor Definition and Usage Examples
Properties of Cursors
Dynamic SQL
Introduction to JDBC_1
Introduction to JDBC_2
JDBC Classes and Interfaces
JDBC Driver Management
JDBC Driver Management
Connections
Executing SQL Statements
Result Sets
Matching Java and SQL Data Types
Exceptions and Warnings
Examining Database Metadata_1
Examining Database Metadata_2
SQL in Java (SQLJ)
Stored procedures
Stored procedures
Stored Procedures - Steps to Call and Execute
Example - Creation of Stored Procedures
SQL/PSM
SQL/PSM Example
Write a SQL block
Write a SQL block
SQL Block to Create Trigger on Library Table
Introduction and Objectives to DB Design
Informal Design Guidelines for Relation Schema
Imparting Clear Semantics to Attributes in Relations, Guidelines and Example
Redundant Information in Tuples and Update Anomalies
Insertion, Deletion and Modification Anomalies
Insertion, Deletion and Modification Anomalies
Generation of Spurious Tuples
Functional Dependencies - Definition and Diagrammatic Notations
Normalization of Relations
Practical Use of Normal Forms
Definitions of Keys and Attributes Participating in Keys
First Normal Form (1NF)
Second Normal Form (2NF)
Second Normal Form (2NF)
Third Normal Form (3NF)
Boyce-Codd Normal Form
Multivalued Dependency and Fourth Normal Form
Formal Definition of Multivalued Dependency
Formal Definition of Multivalued Dependency
Join Dependencies and Fifth Normal Form
Normalization Algorithms
Inference Rules, Equivalence and Minimal Cover
Inference Rules, Equivalence and Minimal Cover
Inference Rules for Functional Dependencies
Inference Rules for Functional Dependencies
Equivalence of Sets of Functional Dependencies
Sets of Functional Dependencies with Algorithms
Sets of Functional Dependencies with Algorithms
Properties of Relational Decompositions
Universal Relation Schema
Universal Relation Schema
Attribute Preservation Condition of a Decomposition
Attribute Preservation Condition of a Decomposition
Dependency Preservation Property
Dependency Preservation Property
Lossless (Non-additive) Join Property
Lossless (Non-additive) Join Property
Testing Binary Decompositions for the Nonadditive Join Property
Testing Binary Decompositions for the Nonadditive Join Property
Algorithms for Relational Database Schema Design
Dependency Preservation and Nonadditive Join Decomposition into 3NF Schemas
Dependency Preservation and Nonadditive Join Decomposition into 3NF Schemas
Nonadditive Join Decomposition into BCNF Schemas
Nonadditive Join Decomposition into BCNF Schemas
Nulls, Dangling Tuples and Alternative Relational Desig
Problems with NULL Values and Dangling Tuples
Problems with NULL Values and Dangling Tuples
Inclusion Dependencies
Template Dependencies
Functional Dependencies Based on Arithmetic Functions and Procedures
Domain-Key Normal Form
Domain-Key Normal Form
Transaction Processing
Features and Types of TPS
Single-User vs Multiuser Systems
Transactions, Database Items, Read and Write Operations and DBMS Buffers_1
Transactions, Database Items, Read and Write Operations and DBMS Buffers_2
Why Concurrency Control Is Needed_1
Why Concurrency Control Is Needed_2
Why Recovery Is Needed
Why Recovery Is Needed
Transaction and System Concepts
Transaction States and Additional Operations
Transaction States and Additional Operations
The System Log
The System Log
ACID Properties_1
ACID Properties_2
ACID Properties_2
Commit Point of a Transaction
DBMS Specific Buffer Replacement Policies
Desirable Properties of Transactions_1
Desirable Properties of Transactions_1
Desirable Properties of Transactions_2
Desirable Properties of Transactions_2
Characterizing Schedules Based on Recoverability
Characterizing Schedules Based on Serializability
Testing Conflict Serializability of a Schedule S-1
Testing Conflict Serializability of a Schedule S-1
End Test
Credit 3 End Test
Credit 3 End Test
Transaction Support in SQL_1
Transaction Support in SQL_2
Transaction Support in SQL_2
Introduction to Concurrency Control_1
Introduction to Concurrency Control_2
Introduction to Concurrency Control_2
Two-Phase Locking Techniques for Concurrency Control
Types of Locks and System Lock Tables_1
Types of Locks and System Lock Tables_1
Types of Locks and System Lock Tables_2
Types of Locks and System Lock Tables_2
Guaranteeing Serializability by Two-Phase Locking
Guaranteeing Serializability by Two-Phase Locking
Variations of Two-Phase Locking_1
Variations of Two-Phase Locking_2
Dealing with Deadlock and Starvation_1
Dealing with Deadlock and Starvation_1
Dealing with Deadlock and Starvation_2
Deadlock Detection_1
Deadlock Detection_2
Deadlock Detection_2
Concurrency Control Based on Timestamp Ordering
Timestamps
Timestamps
Multiversion Concurrency Control Techniques
Multiversion Technique Based on Timestamp Ordering
Multiversion Two-Phase Locking Using Certify Locks
Validation Concurrency Control Techniques
Validation Concurrency Control Techniques
Granularity of Data Items and Multiple Granularity Locking
Recovery Concepts
Recovery Outline and Categorization of Recovery Algorithms
Recovery Outline and Categorization of Recovery Algorithms
Caching (Buffering) of Disk Blocks
Caching (Buffering) of Disk Blocks
Write-Ahead Logging, Steal/No-Steal and Force/No-Force_1
Write-Ahead Logging, Steal/No-Steal and Force/No-Force_1
Write-Ahead Logging, Steal/No-Steal and Force/No-Force_2
Write-Ahead Logging, Steal/No-Steal and Force/No-Force_2
Checkpoints in the System Log and Fuzzy Checkpointing
Checkpoints in the System Log and Fuzzy Checkpointing
Transaction Rollback and Cascading Rollback
Transaction Rollback and Cascading Rollback
Transaction Actions That Do Not Affect the Database
Transaction Actions That Do Not Affect the Database
NO - UNDO or REDO Recovery Based on Deferred Update
Recovery Techniques Based on Immediate Update
Shadow Paging
Database Backup and Recovery from Catastrophic Failures
Key value Database
Introduction
Working of Key-Value Databases
Features and Functions of Key-Value Databases
Schema Design to Support Key Value_1
Schema Design to Support Key Value_2
Key - Value Database Vs Cache
Graph Database
The Property Graph Model
Why Data Relationships Matter
Why Other NoSQL Databases don’t Fix the Problem Either
Relational vs Graph Data Modeling Match-Up
Example Data Model - Fraud Detection in Email Communications
Database Query Language
Cloud Databases
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
Database Clustering and Sharding
Shared - Nothing Architecture
Shared - Disk Architecture
Sharding
Sharded Cluster Components
Shard Keys
Advantages of Sharding
Considerations Before Sharding_1
Considerations Before Sharding_2
Considerations Before Sharding_3
Sharded and Non-Sharded Collections and Connecting to a Sharded Cluster_1
Sharded and Non-Sharded Collections and Connecting to a Sharded Cluster_2
Data Analytics and BI Tools
Introduction, Benefits of Business Intelligence Tools
Best data analytics and BI tools
Microsoft Power BI_1
Microsoft Power BI_2
Tableau_1
Tableau_2
Qlik Sense_1
Qlik Sense_2
Sisense_1
Sisense_2
Best BI Tool for Developing and Deploying Analytics Apps
Looker
Oracle_1
Oracle_2
Domo BI_1
Domo BI_2
SaS Analytics_1
SaS Analytics_2
MongoDB - Overview
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_1
Install MongoDB on Ubuntu_2
MongoDB Statistics
CRUD Operations in MongoDB_1
CRUD Operations in MongoDB_2
CRUD Operations in MongoDB_3
CRUD Operations in MongoDB_4
MongoDB - Data Modelling and Documentation
Data Modelling
Some Considerations While Designing Schema in MongoDB
Some Considerations While Designing Schema in MongoDB_1
Some Considerations While Designing Schema in MongoDB_2
Create Database
Drop Database
Create Collection
Data Types
Insert Document
Query Document
Update Document
Delete Document
Design and Develop MongoDB Queries using CRUD operations
Design and Develop MongoDB Queries using CRUD operations
Projection
Limiting Records
Sorting Records
Aggregation
Aggregation - Examples
Authentication Mechanisms in MongoDB
Backing up and Restoring Data
Backing up and Restoring Data- Examples
Bulk Operations with Examples
Indexing_1
2D - Sphere Index
Indexing_2
Replication_1
Replication_2
Program to Implement Aggregation and Indexing in MongoDB_1
Program to Implement Aggregation and Indexing in MongoDB_2
Program to Implement Aggregation and Indexing in MongoDB_3
Create Backup of Sharded Cluster
SQL vs Mongo DB Entities
Consistency of Data_1
Consistency of Data_2
Query through API_1
Query through API_2
Exercise – 1
Exercise – 2
Exercise – 3
Advanced MongoDB
MongoDB – Deployment
Typical MongoDB Deployment, Read Preference and Write Concern_1
Operation Performance and Partition
MongoDB - Covered Queries_1
MongoDB - Covered Queries_2
Relationships
Embedded Relationships in MongoDB
One to One Relationships in MongoDB
One to Many Relationships in MongoDB
Document Referenced Relationships in MongoDB_1
Document Referenced Relationships in MongoDB_2
Database References_1
Database References_2
List of Drivers Supported by DBRefs
MongoDB - Map Reduce
Syntax
Examples
Using MapReduce_1
Using MapReduce_2
Using MongoDB as a Service: mLab
Implement MapReduce Operation using MongoDB_1
Implement MapReduce Operation using MongoDB_2
Implement MapReduce Operation using MongoDB_3
Execute the Query and Study its Execution Plan_1
Execute the Query and Study its Execution Plan_2
Careers in Database Technology_1
Careers in Database Technology_2
Careers in Database Technology_3
Mini Project 1
Mini Project 2
Mini Project 3
Mini Project 4
Mini Project 5
Credit 4 End Test
Credit 4 End Test
Credit 4 End Test
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:60 hours
Track:Software Development
Skill Level:Advanced
Language:English
Mode:Learn at ALC or at Home
Certificate:Official MKCL
Key Course Highlights:
SQL Mastery
Ability to write complex SQL queries, including aggregate and grouping functions.
Proficiency in using triggers, cursors, and stored procedures for database operations.
Database Design Expertise
Design efficient relational schemas using normalization and functional dependencies.
Prevent anomalies and ensure data integrity in relational databases.
Transaction Management Skills
Manage transactions with ACID properties, concurrency control, and recovery mechanisms.
Handle deadlocks, timestamp ordering, and multi-version concurrency control.
NoSQL Database Proficiency
Work with NoSQL databases, including MongoDB, for CRUD operations, indexing, and aggregation.
Apply advanced concepts like replication, sharding, and MapReduce.
Cloud and Big Data Knowledge
Understand cloud database deployment and utilize BI tools like Power BI and Tableau for analytics.
Implement clustering and sharding techniques for scalable databases.
Practical Experience
Develop database-driven applications using SQL, JDBC, and MongoDB.
Apply knowledge to real-world projects and mini-case studies.
Career Readiness
Gain the technical expertise needed for roles in database management, analytics, and cloud solutions.
Be prepared to work as a database administrator, data analyst, or application developer.
These outcomes reflect the comprehensive skill set and industry readiness gained from the course.