BCA in Database Management at Navrachana University - Course, Fees, Admission, Seats, Syllabus

Creating a comprehensive semester-wise syllabus for Navrachana University's BCA in Database Management in a single line of HTML format requires condensing a lot of information. Since I don't have access to the specific and current syllabus details of Navrachana University's BCA in Database Management program, I'll create a generic example based on typical subjects that might be covered in such a program. This example should be adapted to fit the actual syllabus details.

Semester	Subjects
Semester 1	Introduction to Programming, Mathematics for Computer Science, Introduction to Database Systems, English Communication, Environmental Studies
Semester 2	Object-Oriented Programming, Data Structures, Operating Systems, Discrete Mathematics, Web Technologies
Semester 3	Advanced Database Management Systems, Computer Networks, Software Engineering, Statistics for Data Science, Elective 1
Semester 4	Database Design and Development, Cloud Computing, Information Security, Elective 2, Elective 3
Semester 5	Data Warehousing and Data Mining, Big Data Analytics, Project Management, Elective 4, Elective 5
Semester 6	Capstone Project, Internship, Elective 6, Elective 7

This table includes a header row with "Semester" and "Subjects" as column titles. Each subsequent row represents a semester, listing core subjects and electives that might be part of a BCA in Database Management program. Note that the actual subjects, the number of electives, and the specific curriculum structure can vary. Please consult the official Navrachana University curriculum for accurate and up-to-date information.

As of my update in April 2023 it might not be publicly accessible to find specific course outlines for Navrachana Universitys BCA program in Database Management Systems (DBMS). However I can give you an overview of the important subjects typically covered in undergraduate level Database Management courses. These topics are likely to be included in Navrachana Universitys curriculum or similar programs. It's important to note that for the accurate and up to date syllabus it would be best to consult the universitys official resources or directly contact the faculty. Here are some key areas usually addressed; **Introduction, to Database Systems** An overview of database management The history and evolution of databases The architecture of database systems Data models and languages used in databasesThe relational database model involves concepts such as tables, rows and columns. It also includes keys and indexes like keys and foreign keys. Data integrity and normalization play roles in this model. Additionally SQL (Structured Query Language) serves as the basis for operations, including DDL (Data Definition Language) DML (Data Manipulation Language) and DCL (Data Control Language). When it comes to SQL and advanced SQL you will learn how to create, alter and drop tables. CRUD operations (Create, Read, Update, Delete) are skills that you'll develop. Moreover advanced queries involving JOINs, subqueries and views will be covered. You will also explore stored procedures and triggers. Database design and modeling delve into the Entity Relationship (ER) model. You'll gain an understanding of ER diagrams. How they can be converted into relational schemas. Normalization techniques up to 3NF or even beyond will be taught along with data dictionary management. Transaction management and concurrency control discuss the ACID properties; Atomicity, Consistency, Isolation, Durability. Locking mechanisms are explored to handle concurrency issues. Techniques for detecting deadlocks are covered in addition to transaction isolation levels. Database security focuses on aspects like authentication and authorization for access control. Data encryption methods along with hashing techniques are introduced to protect information. Role based access control is another topic discussed alongside security vulnerabilities identification and countermeasures implementation. Data warehousing explores the basics of its architecture along with ETL processes; Extracting data from sources transforming it into a suitable format for analysis purposes before loading it into a data warehouse system. Introduction to data mining concepts is provided alongside techniques used for effective analysis through OLAP (Online Analytical Processing) systems. NoSQL databases are introduced as alternatives to relational databases with their distinct types such as document based databases or key value stores among others. You'll explore the use cases where NoSQL databases are preferred over options. Additionally an overview of Big Data technologies and ecosystems is provided to familiarize you with the basics, in this field.