Have you considered what might happen to your company if you were to lose your important data? You will lose your stakeholders; your customers and your business will end and no one will count on you with their credentials.  According to our research, data breaches cost businesses more than $5 million. So let’s take a tour in knowing what data masking, its types is and why every business needs data masking to protect its data. 

Understanding data masking

Data masking is a strategy for creating a falsified but authentic replica of your company’s sensitive information. The purpose is to protect classified material while also suggesting a functioning replacement when relevant data is not required, like in marketing presentations, employee training, or application debugging.

Why data masking is the need from the hour?

The main purpose behind using the data masking process is to create a substitute version of data that is difficult to identify and also altered simultaneously. Moreover, the protection of sensitive data is possible with data masking. You need not worry about the credibility of the data that stays conserved and consistent across the available databases. There is no alternation in the usability of data.

Various Types of data masking are available today 

1. Static data masking 

Creating a sanitized copy of your confidential data can be called static data masking. The actual copy is separated from the dummy version shared to the target location. In process of static data masking, a partial or full copy is made for the original data. 

2. Dynamic data masking

This data masking is done when there are consent problems. For instance, let’s state as a business owner you want to allow owners to see a particular set of information from your data and want others to see a masked version of it. So your core team members get to see the original data and the others see only what you want them to show.

3. Deterministic Data Masking

It is a procedure of substituting data in the column with similar data if in a similar row, table, repository, or model/server type.

For instance, in a database, there are numerous records, each having a field holding 1st name. With deterministic masking, the 1st name is always substituted with a similar value – “Lynne” becomes “Denise” – regardless of where “Lynne” seems in the record.

4. On-The-Fly data masking 

When information is transmitted from one location to the next, such as practice or creation, this masking is used. This masking is suitable for enterprises that constantly install software or require difficult interfaces.

Due to the difficulty of maintaining a stable replica system of masked data, this approach would only communicate a part of disguised documents whenever it is required.

5. Statistical data obfuscation data masking

Multiple significant records might be kept secret in the production archives using statistical data obscuration methods. Privacy preservation is a strategy for sharing information about trends in a set of datasets without exposing data from the data set’s real members.

Best Practices of Data Masking

1. Establish the Spectrum Of the project

Organizations must think about what data is to be sealed, who is allowed to view it, where it sits, both in operational and non-operational areas. Although that might seem straightforward in theory, given the complex nature of processes and considerable parts of the business. This approach may necessitate a significant amount of hard work and must be built as a distinct phase of a project.

2. Maintain Referential Integrity

When data masking is used it ensures that two tables in the database maintain a relationship. This helps that data to get synced when there is updation or deletion of files in the database.

In large businesses, it is impractical to use a single strategy across the entire organization. Due to funding requirements, multiple IT admin methods, or different confidentiality needs, each branch of a company maybe ought to establish its specific data masking.

When working with a certain set of information, make sure that the enterprise’s numerous data masking technologies and processes are arranged. This will eliminate issues in the future when information has to be transferred among the company divisions.

3. Protect the Data Masking Methodologies

It is essential to think about how to preserve the data-creation methods, along with other data collections or dictionaries needed to obfuscate the data. These methods should be considered very confidential since only qualified members ought to have full rights to the actual information. Massive chunks of secret info can be changed if anyone discloses which repetitive obfuscation strategies are employed.

Division of tasks is a recommended practice for data masking that is specifically mandated by certain rules. For instance, Info-Tech management employees choose which methods and techniques will be employed in particular. However, distinct algorithm configurations and datasets should be available only to information holders in the appropriate division.

With the help of Salesforce Data Migration Tools, you can protect your Sandbox Data

Salesforce Data Migration tools seem to be a comprehensive data protection tool for Salesforce administrators and programmers. Rather than manually protecting information and using it for a sandbox org, administrators may utilize Data Mask to instantly hide the data inside a sandbox. Administrators and coders can use Data Mask to hide confidential info within sandboxes, including overall revenue or Personally Identifiable Information.

To disguise critical information incomplete or selective sandboxes, Salesforce Data Migration tools like data Mask employs platform-native encryption methods. Based on the importance of the information, the masking operation authorizes you to hide selective or complete confidential information with various stages of masking. You won’t be able to reveal your sandbox information after it’s been hidden. 

This permanent technique confirms that now the information is not copied in an easily decipherable or recognized way into a new location. This has zero effect on your data logs, so you can simply replenish the information from logs and establish a different sandbox org whenever you lose your opinion.

According to the importance of the information, you can choose numerous stages of data masking:

• Random letters should be used to replicate personal information in your sandboxes.
• Replace sensitive information with terms that have been properly translated.
• Sequence masking is used to substitute confidential information.
• Erase any confidential information.
• Sections that usually hold PII or any other confidential information should be hidden.
• Data Mask provides several tiers of hiding to assist in keeping critical production information obscured inside a sandbox. You may substitute confidential information in your sandboxes using randomized letters, identically mapped phrases, or erase it.
• Salesforce Data Migration tools like Data Mask seems to be up-to-date tool that must be deployed in your production org. The masking method is then performed on every new sandbox generated using the production org. You must activate specific functionalities and establish user privileges within your production org before installing and using Data Mask. Salesforce updates automatically the bundle with extra features and security updates once you run it. Version 50.0 of the API is supported by Data Mask at the moment.
• There are two options for configuring the masking technique. Setup is in production, as well as the setting will reveal inside the sandbox whenever it is generated or updated. Alternatively, you may customize the hiding method in a preexisting sandbox.
• The data masking job may only be conducted in sandbox org once the information masking bundle has been started within your actual org. This prevents the production org’s information from being disguised unintentionally. After you’ve completed configuring your sandbox, you may begin masking your stuff. Modify or erase the information in your sandbox by running the mask every session.

Final thought 

Data masking is a great way in which you safeguard your confidential information and save your company from massive financial losses. If you are still in doubt,  try reaching out to isyncSF who found help you more to understand the importance the data masking and also suggest which type of data masking would be best for your business