Data Deduplication Strategies and Benefits

Questions and Answers

What is the primary goal of data deduplication?

To reduce storage capacity needs (correct)

To improve data security

To increase data transmission speed

To enhance data integrity

Which technique is used to identify duplicates in hash-based deduplication?

Content analysis

Hash value comparison (correct)

Data compression

Error-correcting codes

What is the primary importance of data integrity?

To ensure data reliability and trustworthiness (correct)

To improve data manageability

To enhance data security

To reduce storage costs

Which type of data compression reduces data size without losing data quality?

Lossless compression Signup and view all the answers

What is the primary purpose of data backups?

To ensure data availability and recoverability Signup and view all the answers

What is the goal of data normalization?

To eliminate data duplication and anomalies Signup and view all the answers

What is the first normal form (1NF) in data normalization?

Each table cell contains a single value Signup and view all the answers

Which data normalization rule states that a non-key attribute depends on another non-key attribute?

Third normal form (3NF) Signup and view all the answers

Study Notes

Data Redundancy and Data Duplication

Data Deduplication

Process of eliminating duplicate or redundant data to reduce storage capacity needs
Strategies:
- Exact deduplication: eliminate exact duplicates
- Near-deduplication: eliminate similar data with some variations
Techniques:
- Hash-based deduplication: use hash values to identify duplicates
- Content-based deduplication: analyze data content to identify duplicates
Benefits:
- Reduced storage costs
- Improved data manageability
- Enhanced data security

Data Integrity

Refers to the accuracy, completeness, and consistency of data
Importance:
- Ensures data reliability and trustworthiness
- Prevents data corruption and loss
Techniques to maintain data integrity:
- Data validation: check data against a set of rules or constraints
- Data normalization: organize data to minimize data redundancy and inconsistencies
- Error-correcting codes: detect and correct errors in data transmission or storage

Data Compression

Process of reducing the size of data to reduce storage or transmission costs
Types:
- Lossless compression: reduces data size without losing data quality (e.g., ZIP, GIF)
- Lossy compression: reduces data size by discarding some data (e.g., JPEG, MP3)
Techniques:
- Run-length encoding: replace sequences of identical values with a single value and count
- Huffman coding: assign shorter codes to frequently occurring values

Data Backups

Process of creating copies of data to prevent data loss in case of failure or disaster
Importance:
- Ensures data availability and recoverability
- Reduces downtime and data loss risks
Strategies:
- Full backups: create complete copies of all data
- Incremental backups: create copies of only changed data since last backup
- Differential backups: create copies of all data changed since last full backup

Data Normalization

Process of organizing data to minimize data redundancy and inconsistencies
Goals:
- Eliminate data duplication and anomalies
- Improve data integrity and consistency
Normalization rules:
- First normal form (1NF): each table cell contains a single value
- Second normal form (2NF): each non-key attribute depends on the entire primary key
- Third normal form (3NF): if a table is in 2NF, and a non-key attribute depends on another non-key attribute, then it should be moved to a separate table