Data Deduplication Strategies and Benefits

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

Data Redundancy and Data Duplication

Data Deduplication

Eliminates duplicate or redundant data to reduce storage capacity needs
Strategies: Exact deduplication, Near-deduplication
Techniques: Hash-based deduplication, Content-based deduplication
Benefits: Reduced storage costs, Improved data manageability, Enhanced data security

Data Integrity

Refers to the accuracy, completeness, and consistency of data
Ensures data reliability and trustworthiness
Prevents data corruption and loss
Techniques to maintain data integrity: Data validation, Data normalization, Error-correcting codes

Data Compression

Reduces the size of data to reduce storage or transmission costs
Types: Lossless compression, Lossy compression
Techniques: Run-length encoding, Huffman coding
Examples: ZIP, GIF, JPEG, MP3

Data Backups

Creates copies of data to prevent data loss in case of failure or disaster
Ensures data availability and recoverability
Reduces downtime and data loss risks
Strategies: Full backups, Incremental backups, Differential backups

Data Normalization

Organizes data to minimize data redundancy and inconsistencies
Goals: Eliminate data duplication and anomalies, Improve data integrity and consistency
Normalization rules: First normal form (1NF), Second normal form (2NF), Third normal form (3NF)

Description

Learn about the process of eliminating duplicate data to reduce storage capacity needs, including strategies and techniques such as exact and near-deduplication, and hash-based and content-based deduplication. Understand the benefits of data deduplication.