PURPOSE OF NORMALIZATION: Why It Is Used So Much?
PURPOSE OF NORMALIZATION: Why It Is Used So Much? Data normalization rearranges data in a database so users can use it for further querying and analysis. Put simply, it is the process of pure data development. This includes eliminating redundant and unstructured data and matching data across all records and fields. Normalization defines the rules for a relational table to determine whether it satisfies normal form.
Also See: Relational Data Model
PURPOSE OF NORMALIZATION: Why It Is Used So Much?
WHAT IS NORMALIZATION
Normalization is the process of structuring and managing data relationships to minimize redundancy in a relational table and avoid redundant database anomaly properties such as inserts, updates, and deletes. It helps to split large database tables into smaller tables and create relationships between them. It can remove redundant data and make it easy to add, edit or delete table fields.
Learn more about what is Normalization?
PURPOSE OF NORMALIZATION
- Improved overall database organization
Once standardized, your database will be structured and organized in a logical way for all departments in the company. With more organization, duplication and localization errors are minimized and outdated versions of data can be updated more easily.
- Data Consistency
Data consistency is essential for all teams in the company to stay current. Data standardization ensures consistency across development, research, and sales teams. Consistent data also improves workflows between departments and standardizes their information assets.
- Reducing Redundancy
Redundancy is an often overlooked issue in data storage. Reducing redundancy will definitely help reduce file size, thus increase data analysis and processing time.
Also See: Difference Between DBMS and RDBMS
- Cost Reduction
Cost reduction through standardization is the culmination of the above benefits. For example, if file size is reduced, data storage and processors do not need to be as large. Additionally, increased workflow due to consistency and organization will assure that all employees can use database information as quickly as possible, saving time for more tasks.
- Increased Security
As standardization requires more accurate location and consistent organization of data, security increases significantly.
- A more modest information base can be maintained because normalization eliminates duplicate information. In general, this reduces the size of the information base.
- Guarantees better performance attributed to the previous point. As information databases become smaller, the flow of information becomes faster and more limited, improving response time and speed.
- Narrower tables can be considered as normalized tables are modified to have smaller segments to accommodate more page information records.
- Fewer files per table means faster media allocations (file changes).
- Also includes the ability to join only required tables.
Also See: Data Abstraction in DBMS
CONCLUSION
In summary, data normalization is an essential activity for anyone dealing with big data. Not only is it important to get high-quality data, but also to get it through standardization. Analysts, recruiters, and investors will all benefit from data standardization.
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