CF

DBMS

21h 30m 50s
English
Paid

Explore the comprehensive world of Database Management Systems (DBMS) with this dedicated course. Gain insights into the technologies that facilitate efficient data storage, processing, and protection. Starting from basic concepts such as data, information, and database characteristics, you will progressively advance to complex topics like data models, SQL, NoSQL, and modern distributed and scalable systems.

Course Overview

The course aims to equip participants with an extensive understanding of database structure, practical operation, as well as ensuring reliability, security, and optimal performance of databases.

Learning Outcomes

Upon completing this course, participants will be able to:

  1. Differentiate data from information and comprehend the necessity of DBMS.
  2. Skillfully work with both relational and non-relational databases.
  3. Efficiently write and optimize SQL queries.
  4. Set up security measures, backups, and scaling solutions for database systems.
  5. Design databases tailored for real-world applications.

About the Author: takeUforward (Striver)

takeUforward (Striver) thumbnail

takeUforward is the YouTube channel and paid-course brand of Raj Vikramaditya (Striver), an Indian software engineer (formerly at Google) and one of the largest independent algorithm / data-structure educators online. The channel's Striver A2Z DSA Course/Sheet is one of the most-used free DSA-prep references on the internet.

His CourseFlix listing carries three takeUforward courses: Computer Networks, DBMS (Database Management Systems), and Low Level Design. Together the courses cover the foundational CS topics that gate large tech-company interviews alongside the algorithm material the channel is best known for.

Material is paid and aimed at engineers preparing for technical interviews at large tech companies, particularly the Indian-tech and FAANG-tier interview circuit where the CS-fundamentals questions are common. For broader content, see CourseFlix's System Design & Architecture and Preparing for an interview category pages.

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#1: 1.1 Data, Information & Database (Introduction to DBMS)
All Course Lessons (94)
#Lesson TitleDurationAccess
1
1.1 Data, Information & Database (Introduction to DBMS) Demo
11:47
2
1.2 Types of Databases
10:25
3
1.3 Database Management System
11:30
4
1.4 Need, Advantages and Disadvantages of DBMS
09:48
5
1.5 Data Abstraction in DBMS
09:52
6
1.6 DBMS Architecture
09:39
7
1.7 Database Users and Interactions
14:33
8
2.1 DBMS Interfaces (Data Models and ER Models)
19:25
9
2.2 Data Models and Their Types
12:33
10
2.3 ER Model and its Components
13:09
11
2.4 Types of Relationships in DBMS
11:29
12
2.5 Extended ER Features
12:43
13
2.6 Types of Inheritance
10:55
14
2.7 Entity-Relationship Diagram
12:20
15
2.8 Create ER Diagram
11:28
16
2.9 Relationships in ER Diagram
10:46
17
2.10 Relational Models
15:26
18
3.1 Intension and Extension (Relational Model and Normalization)
11:28
19
3.2 Keys in DBMS
11:05
20
3.3 Data Normalization
18:27
21
3.4 Functional Dependency
12:49
22
3.5 Armstrong's Axioms
10:47
23
3.6 Inference Rules
11:45
24
3.7 Closure in Functional Dependencies
09:54
25
3.8 Denormalisation
17:52
26
4.1 Database Languages (SQL and Query Optimization)
15:28
27
4.2 SQL Operators
12:44
28
4.3 Aggregates in SQL
10:48
29
4.4 SQL Clauses
10:45
30
4.5 SQL Joins
15:17
31
4.6 SQL Joins (Advanced)
14:23
32
4.7 SQL Joins (Advanced)
16:36
33
4.8 Views in SQL
17:26
34
4.9 Advanced Views in SQL
14:18
35
4.10 Indexed Views (Materialised Views)
17:06
36
4.11 SQL Subqueries
15:05
37
4.12 Types of SQL Subqueries
18:09
38
4.13 Query Processing
12:49
39
4.14 Query Optimization
18:24
40
4.15 Advanced Query Optimization
19:08
41
5.1 NoSQL Databases (NoSQL Databases)
24:55
42
5.2 BASE Properties
15:22
43
5.3 NoSQL Languages
24:15
44
5.4 Graph Databases
13:01
45
5.5 In-Memory Databases
07:35
46
5.6 Partitioning in Databases
20:07
47
5.7 Types of Partitioning
22:24
48
5.8 Sharding in DBMS
22:57
49
6.1 Sharding in DBMS (Distributed Database Systems)
16:04
50
6.2 Distributed Database Systems
14:13
51
6.3 Architecture of Distributed Database Systems
11:46
52
6.4 Data Distribution Methods
16:37
53
6.5 Fault Tolerance in Distributed Databases
18:03
54
6.6 Load Balancing in Distributed Databases
13:14
55
6.7 Data Replication Techniques
14:17
56
7.1 Thomas' Rules (Transactions and Concurrency)
08:19
57
7.2 ACID Properties
13:55
58
7.3 CAP Theorem
16:33
59
7.4 Database Transactions
13:27
60
7.5 Concurrency Control in Databases
18:31
61
7.6 Locking Protocol (Shared Locks, Exclusive Locks)
16:19
62
7.7 Timestamp Ordering Protocols in DBMS
17:23
63
7.8 Starvation in DBMS
10:07
64
7.9 Deadlock in DBMS
12:53
65
7.10 Concurrency Control in Distributed Databases
18:44
66
7.11 Serialization in Databases
19:12
67
7.12 Scheduling in Databases
12:04
68
7.13 Serialization Graphs in Databases
12:12
69
7.14 Isolation Levels
10:22
70
7.15 Managing Transaction Consistency and Concurrency
11:55
71
8.1 Triggers in Databases (Triggers and Procedural Features)
13:42
72
8.2 Stored Procedures in Databases
13:03
73
9.1 Database Recovery Management (Recovery and Backup)
12:48
74
9.2 Database Backups
13:00
75
10.1 Database Indexing (Indexing and Performance Tuning)
15:31
76
10.2 Types of Database Indexing
12:18
77
10.3 Indexing Techniques
11:53
78
10.4 B- and B+ Trees
12:24
79
11.1 Database Monitoring (Database Monitoring and Caching)
12:29
80
11.2 Performance Tuning
11:19
81
11.3 Database Caching
10:23
82
11.4 Database Caching Strategies
09:45
83
12.1 Data Encryption in DBMS (Security and Access Control)
08:53
84
12.2 Database Security
13:11
85
12.3 Encryption Techniques in DBMS
07:17
86
12.4 Data Masking Techniques
10:10
87
12.5 RBAC (Role-Based Access Control)
12:20
88
12.6 RBAC Models
11:30
89
13.1 Database Scaling (Scalability and Big Data)
13:52
90
13.2 Big Data and DBMS
14:18
91
13.3 DBaas (Database as a Service)
08:16
92
14.1 Database Migration (Data Warehousing and Migration)
11:06
93
14.2 Data Warehousing
10:29
94
14.3 Event-Driven Architecture
13:46
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Frequently asked questions

What prerequisites are necessary before taking this course?
The course does not have strict prerequisites, but having a basic understanding of computer science concepts and familiarity with programming can be beneficial. This foundational knowledge will help you grasp the concepts of data models, SQL, and NoSQL databases covered in the lessons.
What kind of projects or exercises will I work on in this course?
Throughout the course, participants will engage in practical exercises such as designing Entity-Relationship (ER) diagrams and writing SQL queries. These projects aim to reinforce the concepts of data models, normalization, and database design, ensuring you can apply these skills to real-world scenarios.
Who is the target audience for this course?
This course is designed for individuals looking to gain a comprehensive understanding of Database Management Systems. It caters to both beginners and those with some experience who want to deepen their knowledge in relational and non-relational databases, SQL optimization, and distributed systems.
How does the depth of this course compare to other DBMS courses?
The course covers a wide range of topics from basic to advanced levels, including SQL, NoSQL, data models, and distributed systems. It provides a detailed exploration of each subject, such as query optimization and fault tolerance in distributed databases, making it suitable for students seeking thorough understanding rather than an introductory overview.
Which specific tools or platforms will I learn to use?
The course focuses on foundational database concepts rather than specific tools. However, it extensively covers SQL and NoSQL languages, which are integral to managing and querying databases. This knowledge can be applied across various DBMS platforms.
What topics are not covered in this course?
While the course provides a broad overview of database management, it does not delve into specific database software installation, detailed programming language integration, or front-end application development. Instead, it focuses on the theoretical and practical aspects of database structures and operations.
How can the skills learned in this course be applied to other areas or careers?
The skills acquired in this course, such as SQL proficiency, understanding of data models, and knowledge of distributed systems, are highly transferable. They are essential for careers in data analysis, software engineering, and IT management. Mastery of these topics can also prepare you for advanced studies in data science and cloud computing.