2 hours ago
sigma rahman
RE: Week 5 Discussion
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Data normalization involves tabes and their relationships that evolve from the tables, these tables also have data that can be optimized at different levels of use and extraction, however, in order to design and protect the data/tables we have to remove any redundancy and of course inconsistent information/data, that I have noticed in several of my own work experiences. Where we have data in table formats that are often inconsistent, redundant and also missing. There are many factors that are required in order to have normalized data/tables, that is: identifiable sets of data, having different tables for different criteria, having primary and foreign keys, From all these in my opinion, the two most important factors are removing data redundancy and data inconsistency are the main factors that can affect the entire database.
As per my two choices of factors, that includes data redundancy elimination, I found several online resources depicting the elimation of it, from personal experience also, below are some of the ways to do so:
- Leveraging master data
- Normalizing databases
- Deleting unused data
- Data management
Reference: Online resources:
- What Is Data Redundancy & How Can You Avoid It? https://datachannel.co/blogs/what-is-data-redundancy-how-can-you-avoid-it/
- Data Redundancy: What Is It and How to Avoid It? https://coresignal.com/blog/data-redundancy/
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