What Intelligent Data Migration Is—And Why You Need It
Data migrations are an all-too-common project that IT departments face as companies change and data grows. Migrations become necessary when moving to the cloud, changing storage providers and when an organization’s structure changes—such as during a merger or acquisition.
A traditional data migration happens when the data that is moving is simply “lifted and shifted” to the new storage system. Certainly, IT departments have thoughtfully looked at their data landscape to attempt to eliminate unnecessary storage and try to improve the labeling and categorization of their files as much as possible. But there are great tools that help automate this process and make it structured and efficient – and what better time to clean up your data than during a migration?
Defining Intelligent Data Migration
The clean-up process comes with the addition of artificial intelligence-based (AI) discovery and classification. Specifically, AI that is pre-trained to discover and identify the various types of information that an organization has within their unstructured data and provide classification on how critical that data is to the business and data privacy regulations – then using that information to plan a migration project. This capability is what is fueling the new term “intelligent data migration.”
The definition of an intelligent migration is capitalizing on the ability to surface greater insight into your data to execute a more efficient and lower-risk migration.
Solutions that help you execute an intelligent data migration are able to utilize the attributes of the content such as document type, file size, age, and access rights to determine where that content should be living in the new repository – or if it should be moved there at all. When content is unstructured, this information is difficult to obtain without AI-based discovery and classification. A solution with AI can scan the content and recognize patterns that make it a resume or an invoice, which greatly improves the classification accuracy.
This level of intelligence in understanding your data improves the end-user experience and the security of the migration. Additionally, it significantly lowers costs in unneeded data storage and lowers the risk of data privacy violations.
Why You Need Intelligent Data Migration
If you’re going to be doing a data migration, it just makes sense to approach it with the right tools to make a more informed and intelligent transition. Intelligent migration is something every company can benefit from, but there is no question that certain organizations are more at risk than others. Some examples include companies that have yet to move to the cloud and have been collecting large amounts of data on legacy servers. Chances are that there is a lot of unknown, unstructured data that needs to be understood – dark data. Decision-makers typically know that there is a lot of obsolete or sensitive data, but they don’t know where it is, and therefore are fearful of moving to the cloud to make that data more accessible.
Fundamentally, every organization has unstructured, risky data; they simply don’t know what it is or who has access to it. Whether you are beginning to plan your migration now, or just know it will happen in the future, it can’t hurt to start uncovering your dark data so that you can better protect your business and meet data privacy regulations.
The Risk of NOT Doing Intelligent Data Migration
All companies today operate in a regulated environment when it comes to data. Certain industries, like healthcare and financial services, have been regulated for decades. But now all companies are facing data privacy regulations from almost any region they may operate in. The risk of not properly protecting sensitive data comes from the potential for a data breach, but also the potential for large fines from failing to meet the data privacy regulations.
While many of these laws are still new, there are many companies that have already been fined significant amounts of money historically. The largest so far has been the GDPR fine to Amazon in 2021 of $877 million.
The biggest GDPR fines also include Google, which has been hit twice with GDPR fines totaling $65 million. The GDPR has fined an estimated 1,000 companies in the past 2 years with cumulative fines of $1.25 billion.
It’s just the beginning of regulations and fines around data privacy and companies can’t afford to continue storing, let alone migrate, data that they don’t understand.
Intelligent Data Migration Has an Amazing ROI
Gaining a better understanding of your data by doing an intelligent data migration sounds like a good thing, but the benefits go far beyond cleaning house. There are significant cost savings and financial risk reduction that makes for a powerful ROI case.
Here are several financial benefits:
- Lower storage costs – Getting rid of data and migrating less over to your new storage system saves money. Many productivity platforms have storage quotas and going over those quotas can be costly. You don’t want to be paying a top-tier rate for managing legacy, unused archival content. Deleting obsolete data and archiving unused data in cheaper archival storage saves the IT budget significant money.
- Lower migration costs – The project of data migration can be a lengthy, resource-intensive endeavor. By understanding your data upfront and eliminating unneeded data, you are actually reducing your migration timeline which reduces costs. And, since the AI-based data discovery and classification is automated and doesn’t need to be trained, this eliminates much of the upfront auditing effort.
- Improved productivity – Making better decisions about where data is stored and who has access to it can dramatically improve business operations. Many times companies have siloed data storage that prohibits collaboration and or the ability to leverage data to improve efficiency. Proper classification and labeling of data helps you surface content for users in a more productive fashion. While harder to measure, this is a benefit that is clearly felt in the organization and one that often produces new revenue opportunities or resource cost reductions.
- Avoidance of fines – Identifying and classifying your sensitive data allows you to properly store and protect it so you can comply with state and federal mandates. Penalties can either be avoided completely, or they can be reduced by having this level of classification. It truly helps companies manage and reduce their financial risk and exposure to data privacy regulations.
- Reduction of legal liability – If an organization is involved in litigation, an eDiscovery happens that identifies all available documentation related to the case. This content is then placed on legal hold and can potentially be used against the organization in the lawsuit. Regularly identifying data that the company no longer needs so that it can be legally disposed of can help reduce potential future legal liability.