Data redundancy is like a two-edged sword.
This raises concerns about implementing data redundancy in database management.
What Is Data Redundancy?
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Data redundancy is the process of storing your data in more than one place.
you’re able to store the data sets in the same database or different systems.
Keeping multiple data sets means that your data will occupy more space.
If you don’t arrange them properly, they could litter your gadget.
There are two kinds of data redundancy: accidental and intentional.
Accidental data redundancy is the process of duplicating data sets in your system by mistake.
This could be a result of human errors or technical issues.
Intentional data redundancy refers to the process of duplicating data deliberately within your system to improve your operations.
Instead of relying on one data set, you have more options at your disposal.
Imagine not being able to find your car key when you need it.
Having a spare key will save you the trouble of searching for it endlessly and possibly missing your engagement.
This is a typical example of intentional data redundancy.
You have another set of the same data to work with if the original is unavailable.
Is Data Redundancy the Same as Data Backup?
When the emphasis is on data loss, data backup comes to mind, not data redundancy.
Data redundancy offers you a real-time solution to data failure.
you’re able to easily pull up the other copy of your data without suffering downtime.
Data backup, on the other hand, doesn’t function in real-time.
Should you lose your data, you could experience downtime before the saved copy comes into play.
4 Advantages of Data Redundancy
Data redundancy is helpful in database management.
Higher Efficiency
You work better when you could easily access files and data in your system.
Such quick access is time-saving.
You get things done faster without wasting time looking for information.
Quick access helps you accomplish more work in little time.
Data Security
Losing your data to a cyberattack can be damaging.
Data redundancy helps tosecure your databaseby giving you more than one piece of a single data set.
This will relieve you of the consequences of data loss.
Data Quality
Maintaining high data quality is necessaryto ensure data integrity.
Such loopholes may go unnoticed without multiple data sets, as there would be no basis for comparison.
you’re able to jump into the same information and continue your work without significant delay or obstruction.
4 Disadvantages of Data Redundancy
Data redundancy can cause some drawbacks in your operations.
To be on the safer side, you better be aware of the setbacks for better database management.
Larger Storage
Duplicating data sets requires more storage space to keep them in.
You’ll need a large storage option to manage your increasing data sets.
Complex Management
Managing your data sets effectively requires dedication and attention to detail.
You must ensure that all variables are in good condition.
Data redundancy leaves you with more data sets to cater to.
The many moving pieces can be complex, creating room for errors and mistakes.
As mentioned earlier, data redundancy creates a need for more storage space.
This means you’ll be spending more on storage, andcloud storage servicesdon’t come cheap.
If you are working with a tight budget, the additional storage can be a financial burden.
Data Corruption
Data corruption is a serious concern when you are dealing with data.
The more your data sets, the higher the chances of corruption.
Ensure that you’re able to account for every data set you duplicate.
Otherwise, they might harm your system due to changes in their original conditions.
Double-check your system regularly to check for accidental data redundancy.
For example, your system might be underperforming due to excess data sets you aren’t aware of.
