Data Analytics: Why Data Normalization
Open accessAbstract
The two maestros Artificial Intelligence and Machine learning are ruling the data filled world with good analytics. Many of these domain skills are used in the industry to analyze and interpret the data beyond what it actually is. Supporting the known saying find the horse before the cart is ready is what it mean to normalize the data before getting it analyzed. This article focus on what normalization actually is, why normalization is needed before data analysis and how data normalization is done.
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AI can personalize individual users' data normalization and transformation processes by learning their behavior patterns.
“AI can also personalize individual users’ data normalization and transformation processes by learning their behavior patterns [202].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [202]
AI plays a crucial role in improving the data normalization and transformation of wearable technology.
“Moreover, AI plays a crucial role in improving the data normalization and transformation of wearable technology [14,202].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [202]
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Cites
Normalization: A Preprocessing Stage
Patro, S. G. K., & Sahu, K. K. (2015) · IARJSET · doi:10.17148/iarjset.2015.2305 · Cited by 1,594 · see citing works
Principal component analysis for clustering gene expression data
Yeung, K. Y., & Ruzzo, W. L. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.9.763 · Cited by 1,276 · see citing works
Data Mining: A Preprocessing Engine
Al-Shalabi, L., Shaaban, Z., & Kasasbeh, B. (2006) · Journal of Computer Science · doi:10.3844/jcssp.2006.735.739 · Cited by 616 · see citing works
Standardization and Its Effects on K-Means Clustering Algorithm
Usman, D., & Mohamad, I. B. (2013) · Research Journal of Applied Sciences Engineering and Technology · doi:10.19026/rjaset.6.3638 · Cited by 417 · see citing works
Barbaree, H. E., & Mewhort, D. J. K. (1994) · Behaviour Research and Therapy · doi:10.1016/0005-7967(94)90144-9 · Cited by 23 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- SB Kotsiantis, D Kanellopoulos, PE Pintelas."Data preprocessing for supervised learning". International Journal of Computer Science. Vol 1 (2), 111-117.
Cited by
Sorted by citations
The emergence of AI-based wearable sensors for digital health technology: a review
Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works
- Authors
- K. Dhana Sree, D., & C. Shoba Bindu, D.
- Venue
- International Journal of Engineering & Technology
- Publisher
- Science Publishing Corporation
- Published
- 2018-09-25
- Volume
- 7
- Issue
- 4.6
- Pages
- 209
- ISSN
- 2227-524X (ISSN-L)
- OpenAlex
- W2958928493
- Cited by
- 22
- References
- 5
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 4 · 2023: 5 · 2022: 4 · 2021: 2 · 2020: 1
- FWCI
- 1.21
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Engineering & Technology (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- data normalization, data preprocessing, data analysis, machine learning, artificial intelligence, data quality
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