As organizations are digitally transforming their processes/workflows by shifting to the cloud or outsourcing their services to enjoy benefits like cost optimization, securing universal access, robust security and enhanced mobility, data migration has become an essential activity.
In fact, it has become the need of the hour to facilitate outcomes like quick delivery of services, query resolution, value addition, customer satisfaction and to strengthen the core activities of business enterprises.
However, the process of data migration is not as simple as it sounds and poses severe challenges in terms of enhanced security threats.
Why is data migration a risky affair?
The answer lies in a concept called “data gravity”. It is a phenomenon wherein the quantum and speed of a data-based software present in the system increase with an increase in the mass of data. The concept of data gravity is new, but the problems associated with it are gaining prominence due to the migration of data to a cloud-based infrastructure. Data gravity consists of three parameters:
- How data appeals to other data as it grows rapidly
- How data is being incorporated into a business
- How data becomes personalized over time
To move data and applications to another beneficial environment, Gartner has suggested “disentangling” information and applications as a method of overcoming data gravity. So, it is crucial to sort out applications and data complexities to fortify data mobility, data management, and data governance to prevent security leakage during the migration of data.
Challenges during Migration: Can we all be at risk?
Loss of valuable information during migration
The primary issue that may crop up when migrating data from one system to another is the loss of information. The loss of valuable data can be dreadful to businesses as well as individuals. However, this type of risks can be avoided through migration testing during the process.
Post-migration semantic risks
There are risks galore when data gets
migrated from one place to another – semantic risk being one of them. Also,
there are chances of errors creeping in when data may get saved in the wrong
location or folder accidentally. Such a semantic risk involving security
leakage can be detrimental, should you be dealing with currencies or numbers.
To evade such problems, it is better to undertake migration testing.
Risks of extended downtime
When the source system is not active, the process of moving data from one application to another takes longer than the anticipated timeframe. It poses a threat to the organization and its stakeholders. However, application security testing can help you to solve such challenges during migration.
Best applications for migration of data
It is always advisable to follow some
of the best practices during migration of data, regardless of the methods. Here
are some of them:
Backup before execution
Since loss of information can be one
of the major issues at the time of migration, it is crucial to maintain a
backup of resources before the execution of process. You need to make sure you
test all the resources before initiation of the migration process.
Follow a robust strategy
The migration process is difficult
and even disappointing at times, so you need to follow a robust strategy to
manage a challenging situation. Interference or implementation of too many
plans can jeopardize the whole process of data transfer.
Rigorous migration testing
Not only during the design and
planning phases but during implementation and maintenance as well, it is
crucial to test the migration of data to ensure you achieve the desired result.
Five Key Strategies to prevent Security leakage before initiating data migration
The strategy guiding the migration of
data may differ based on the goals and requirements of an organization. Here is
a list of strategies to ensure an error-free migration of data:
1. Assessment of sources
Before the process begins, you must
assess whether the transferred data would fit into the target system or not.
You need to scrutinize how much information is pulled over and how the overall
database might appear post completion of the process. For example, there may be
the presence of many fields that need not require to be mapped to the target
system. On the contrary, there may be missing data fields necessitating the
extraction of data from another location to plug a gap.
2. To design and plan the migrations
The design phase implies the type of
migration strategy an organization wants to employ- Big Bang migration strategy
or Trickle migration strategy. It also depends on the technical architecture
and detailed technique of the migration process. During this phase, it is
important to ponder over security plans for the pool of data.
3. Develop a migration solution
enough” approach is not really enough when it comes to data migration. It is
important to break the data into smaller subsets and create one type at a time
before testing. If you are working on a large migration process, it is vital to
test in parallel.
4. Perform a live migration testing
Performing a test during the build phase is not enough to ensure the accuracy of migrated data. You should always test the migration with real-time information to ensure the completeness of the application.
5. Final audit
Once the process gets over, you must set up an internal application to audit information, in order to validate the correctness of the migration process.
Data migration is a complicated process that involves the possibility of security leakage during the time of transfer. Choosing a proper implementation strategy and application security testing that align with the requirements of the businesses is vital to ensure the success of data migration with zero errors. Consequently, the process can ultimately deliver value to the organization in terms of ROI, performance, and security.