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About 3,928 papers for “Database normalization”

METHODOLOGY FOR DATABASE NORMALIZATION USING ARTIFICIAL INTELLIGENCE

Aldeniz Rashidov, Fatme Rashidova · INTERNATIONAL SCIENTIFIC CONFERENCE - UNITECH · 2025

ABSTRACT This paper explores the process of database normalization using artificial intelligence (AI). Normalization is a key stage in database design, aiming to eliminate redundancy, minimize anomalies, and improve the efficiency of data storage and processing. The paper presents the fundamental theoretical concepts of normalization, includ-ing functional dependencies and normal forms, and analyzes the challenges associated with manual normaliza-tion in complex databases. The main focus is on the application of AI — through machine learning, expert sys-tems, and hybrid approaches — for automatically detecting dependencies, recommending optimal structures, and transforming tables. The paper provides examples of automated normalization, along with a discussion of the benefits and limitations of the approach, as well as potential directions for future research. The study demonstrates that integrating AI into the normalization process significantly enhances the design of efficient,consistent, and optimized databases.

Cited by 0

An Automatic Database Normalization – Primary Key Generation

Amir Hassan Bahmani, Mahmoud Naghibzadeh · 2008

Normalization is the most exercised technique for the analysis of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. A normalized database does not show anomalies due to future updates. It is very much time consuming to employ an automated technique to do this data analysis, as opposed to doing it manually. At the same time, the process is tested to be reliable and correct. This paper presents a new complete automated relational database normalization method. It produces the dependency matrix and the directed graph matrix, first. It then proceeds with generating the 2NF, 3NF, and BCNF normal forms. All tables are also generated as the procedure proceeds. One more side product of this research is to automatically distinguish one primary key for every final table which is generated.

Cited by 0

A Novel Automatic Relational Database Normalization Method

Emre Akadal, Mehmet Hakan Satman · RePEc: Research Papers in Economics

The increase in data diversity and the fact that database design is a difficult process make it practically impossible to design a unique database schema for all datasets encountered. In this paper, we introduce a fully automatic genetic algorithm-based relational database normalization method for revealing the right database schema using a raw dataset and without the need for any prior knowledge. For measuring the performance of the algorithm, we perform a simulation study using 250 datasets produced using 50 well-known databases. A total of 2500 simulations are carried out, ten times for each of five denormalized variations of all database designs containing different synthetic contents. The results of the simulation study show that the proposed algorithm discovers exactly 72% of the unknown database schemas. The performance can be improved by fine-tuning the optimization parameters. The results of the simulation study also show that the devised algorithm can be used in many datasets to reveal structs of databases when only a raw dataset is available at hand.

Cited by 0

Automating The Normalization Process For Relational Database Model

Radhika Grover, Srishti Hunjan, Dhiraj Patil Yuvraj · 2014

It has been estimated that more than 80 percent of all the computer programming is database related. Studies have shown that the vast majority of the content in the WWW resides in the deep web sources which store their content in backend databases which have been growing by leaps and bounds. Due to its great importance for database applications database schema design has attracted substantial research. Database normalization is a theoretical approach for structuring a database schema and it is very well developed but unfortunately, the theory is not yet understood well by practitioners. It has been difficult to motivate students to learn database normalization because students think the subject to be dry and purely theoretical. In this paper, a tool called Web Based Relational Database Design and Normalization Tool is proposed, which handles normalization for Relational Databases. The tool is suitable for relational data modeling in systems analysis and design and data management process. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency. It aims to provide relations normalized up to 3NF and provide an edge over the other tools already present to handle database normalization.

Cited by 0

Eliminating process of normalization in relational database design

T. Hussain, Shafay Shamail, Mian Muhammad Awais · 2005

The relational database design approach requires the process of normalization in order to minimize data redundancy and update anomalies in the relational schema. Algorithms defined in normalization theory depend upon various dependencies namely functional, multivalued, join and inclusion dependencies that should be carefully defined for a database application. Identification of these dependencies and a minimal cover is a complex and time consuming task for almost all practical problems. This work discusses how the normalization process can be eliminated from the required steps of database design. It explores various constructs of entity relationship diagram (ERD) and their transformation to relational schema. This work elaborates how un-normalized relations are created during the entity relationship (ER) model to relational schema transformation. A set of rules is presented which if followed at the stage of conceptual modeling would always generate a relational schema that satisfies normal forms up to Boyce-Codd normal form (BCNF), thus eliminating the need for normalization. The motivation behind this paper is to save the database designer's valuable time and effort otherwise required in defining dependencies, in finding a minimal cover and in normalizing a given relational schema.

Cited by 14

Relational Database Normalization vs Denormalization: A Performance Perceptive

Wumi Ajayi, Kikelomo Okesola, Deogratias Nteziryayo et al. · Asian Journal of Electrical Sciences · 2025

Relational database architecture has a significant impact on how data are managed, retrieved, and stored, making it essential for effective data management. Two key design strategies that influence the structure of a relational database are normalization and denormalization. Normalization organizes data into structured tables to eliminate redundancy and ensure data integrity. Although this approach simplifies updates, it may lead to performance degradation due to complex queries and frequent join operations. In contrast, denormalization improves performance by reducing or eliminating join operations, at the cost of increased data redundancy and storage requirements. This paper investigates the impact of these design strategies on database performance, with a focus on improving query efficiency by minimizing the number of joins required for data retrieval. Using SQL Server as the chosen RDBMS and applying it to a School Grades Management System, this study demonstrates practical implementations of normalized and denormalized schemas through structured queries. Furthermore, by presenting performance benchmarks supported by indexing optimization strategies, this work aims to guide database designers in selecting an appropriate design strategy that achieves an optimal balance between data integrity and system performance.

Cited by 0Open access

The Importance of Database Design and Normalization Process

Tülay Fenerci · SHILAP Revista de lepidopterología · 2014

Database management systems are major tools which provide management of or­ganizations’ operational data via computers. However their efficient usage de­pends on how well database tables are organized. When undesigned data is sto-red in the database there probably occur some problems such as data repeating and waste of storage space. In order to prevent such problems a normalization process is applied to tables.Normalization is a process of refining relations where relations are formed by gathering attributes. Hence problems such as repeating of data, dependency and combined relationships are solved with normalized base tables.Therefore database design is an important fact in efficiency of database ma­nagement systems.

Cited by 0Open access

Application of Database Normalization in Increasing Data Storage Efficiency

Marviola Hardini, Vertika Agarwal, Desy Apriani et al. · International Transactions on Artificial Intelligence (ITALIC) · 2025

Database normalization is a key process in relational database design that reduces redundancy and ensures data integrity. As data volumes increase, maintaining efficient and consistent storage becomes critical. This study investigates the application of normalization techniques from First Normal Form (1NF) to Third Normal Form (3NF) on a sample inventory database to evaluate their impact on storage efficiency. The process focuses on eliminating data repetition and optimizing table structures to enhance performance. Experimental results show that normalization reduces database size by approximately 30%, significantly minimizing redundancy. Smaller, more organized tables improve storage utilization, especially in large-scale systems. However, normalization can introduce query complexity due to increased joins, potentially affecting execution time. Despite this, the trade-off is considered acceptable given the gains in data integrity and storage optimization. This research emphasizes the value of normalization for scalable and maintainable systems. It also aligns with Sustainable Development Goals (SDGs), particularly Goal 9 (Industry, Innovation, and Infrastructure) and Goal 12 (Responsible Consumption and Production), by promoting efficient digital infrastructure and responsible data management practices. These improvements contribute to more sustainable, cost-effective systems in industries relying on large-scale data, such as e-commerce, healthcare, and finance. In conclusion, normalization is an essential tool for optimizing storage and ensuring data consistency in relational databases. Although performance trade-offs exist, they can be mitigated through indexing and query optimization. The study offers insights for database designers seeking to balance efficiency and system performance in data-intensive environments.

Cited by 0Open access

Database file normalization as an information science related activity

George McMurdo · Journal of Information Science · 1982

Normalization is a technique for determining the optimal logical design of an integrated database, based on the obser vation that certain groupings of entities exhibit better proper ties in storage operations than do other groupings containing the same data. The basic principles of normalization theory are reviewed and the advantages it offers are illustrated. The author concludes by discussing the feasibility and desirabil ity of a division of labour in database administration with information scientists and computer scientists respectively managing the logical representation of the database and the physical maintenance of the database.

Cited by 3

Developing a knowledge management support system for teaching database normalization

Lei Zhang, Roland Kaschek, Kinshuk Kinshuk · 2005

In tertiary education some students find it hard to learn database design theory, in particular, database normalization. To address this learning dilemma, a prototype system was implemented to aid in exploring the potentials of knowledge management in teaching database normalization. This paper presents our findings based on the educational knowledge management (KM) system analysis, design, prototype implementation and evaluation.

Cited by 5