Do you know that the world generates approximately 328.77 million terabytes of data daily?
Data has undoubtedly become the lifeblood of our digital age, powering businesses, government, and our daily lives.
With such an enormous volume of data circulating, isn’t it super important to safeguard it?
That’s where data scrubbing and data recovery save the day.
This article is all about data scrubbing and recovery — two critical processes that help ensure the safety and integrity of our precious data.
Here, we’ll explore what they are, how they are different
from each other, and why we need these preventative approaches to data management.
Basics of data scrubbing
Imagine there’s a huge library filled with books. Over time, some of these books may become dusty, pages torn, or words illegible.
The same thing can happen to the data stored in your storage devices. Consider the data as the books in the library. It can deteriorate and lead to errors and corruption.
Here comes the data scrubbing as a proactive approach.
Data scrubbing is finding and rectifying your data’s errors, inconsistencies, and inaccuracies. Just like a librarian who goes through each book, ensuring they’re in perfect condition.
In data scrubbing, there are various techniques involved. Some of the most common ones are given here:
- Data validation: Validation of data involves checking it to ensure it conforms to predefined rules and standards. For example, it might check that email addresses in a database have the correct format.
- Data cleansing: Cleansing of data means removing or correcting inaccuracies in data. For example, it can fix misspelled names or delete duplicate records.
- Data enrichment involves adding missing information from external sources to make your incomplete data useful. For example, adding country codes before phone numbers for leads if their locations are known.
Data scrubbing is very helpful in improving data quality and leads to better decision-making. Moreover, it helps organizations maintain regulatory compliance, a crucial aspect in this data-sensitive landscape.
Basics of data recovery
When you accidentally lose your data due to any reason, data recovery comes as a hero to rescue it.
It’s a reactive approach that is used in cases when data has already been lost or compromised.
Data recovery involves retrieving lost or damaged data from backups or other resources.
Here are some common methods of data recovery:
- Backup and restore: It’s the most common form of data recovery. It involves taking regular backups of your data; in case of data loss, you can restore it from these backups.
- Disaster recovery plans: These comprehensive plans outline the steps to recover your data and restore operations during a disaster such as a fire or cyberattack.
- Data forensics: This method is often used in legal or investigative contexts where specialized techniques are used to recover data.
Data recovery is undoubtedly a lifesaver in the event of data loss, but you should also remember that it has its limitations and challenges.
First, 100% data recovery is impossible, especially when it’s been overwritten or the storage device is damaged.
Second, the process can take a very long time to recover data in cases of extensive loss.
Comparison between data scrubbing and data recovery
Since you understand what data scrubbing and data recovery is, let’s compare the two to understand their differences:
- Proactive vs. reactive method: Data scrubbing is proactive, meaning it prevents errors and issues before they cause any problems. On the other hand, data recovery is a reactive process used after data loss.
- Cost implications: Data scrubbing is usually more cost-effective in the long run because it prevents data loss, which can be expensive to recover. Data recovery can cost you significant amounts, especially in complex cases.
- Data integrity: Data scrubbing ensures data accuracy and consistency, which helps maintain high data integrity. Data recovery may result in compromised data quality, as the recovered data might not be in its original state.
By comparing the two, we can conclude that it’s better to implement data scrubbing in your system rather than wait for data to get damaged and recover it.
Data scrubbing for data recovery preparedness
You don’t need to choose one between the two. You can use both to complement each other. By implementing robust data scrubbing processes, you can reduce the possibility of data loss, which reduces the need for extensive data recovery efforts.
This collaboration of the two can be exemplified in the case of data scrubbing in Synology systems. Synology — a lead provider of NAS (Network-Attached Storage) solutions, emphasizes data scrubbing as a proactive measure to maintain data health and reduce the risk of data loss.
A preventative approach to data management
You can combine data scrubbing and recovery for improved effectiveness in your comprehensive data management strategy.
Here’s how to create one:
- Data classification and prioritization: Classify your data based on its importance and sensitivity, as not all data is equal. Make sure to prioritize the critical data.
- Data lifecycle management: Define stages for your data, from the time of creation to deletion. Also, implement policies and procedures accordingly.
- Regular data audits: Conduct routine audits to identify and rectify errors and inconsistencies. This proactive approach will drastically reduce the need for data recovery.
- Implement data protection best practices: Utilize encryption, access controls, and data backup solutions to protect your data from external threats and internal mishaps.
- Employee training and awareness: Ensure your staff understands the importance of data protection and their role in maintaining data integrity.
As the world depends more and more on data, the significance of data protection cannot be overstated. Both data scrubbing, as well as data recovery, are crucial in safeguarding our invaluable information assets.
On the one hand, data scrubbing acts as a proactive measure that prevents many data issues; on the other hand, data recovery acts as a safety net when things go wrong.
You can implement both methods together for a preventative approach to your data management strategy.