Data Processing in DBMS

DATA PROCESSING

Converting raw data into meaningful information in a database system.

Stages of data processing in DBMS:

1. Data Collection / Input

From various sources like user input, sensors, online forms, scripts, or APIs etc.
Input data à raw and unorganized.

2. Data Storage

· Stored:- structured format, ex. tables (in relational DBMS) or other structures (e.g., documents in NoSQL). 

3. Data Manipulation / Processing

The DBMS processes à queries and transactions to manipulate data.
It involves:
CRUD operations: 
Querying:  using SQL 

4. Data Output / Information Retrieval

· Based on user or application requests such as:- 
Reports
Dashboards
User interfaces (UI)

5. Data Storage (Post-Processing)

Saved back to the database, files.

6. Feedback / Update Cycle

7. Data Maintenance:

- Backup and Recovery:
- Concurrency Control: 
- Data Integrity: 

Components Involved in Data Processing

1. Query Processor:
2. Storage Manager:
3. Transaction Manager:
4. Data Dictionary:
5. Database Engine:
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Flow of Data Processing

1. Query Submission: 
2. Query Parsing and Validation: 
3  Execution: 
5. Result Delivery: 
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Types of Data Processing in DBMS

1. Batch Processing:

2. Online Transaction Processing (OLTP):

3. Online Analytical Processing (OLAP):

Benefits of Data Processing in DBMS

- Efficiency: 
- Data Integrity: 
- Scalability:
- Security: 
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