Advice for Organizations Considering Intelligent Data Migration
Data migration projects can arise from the desire to lower storage costs and gain accessibility or due to a merger or acquisition. The transitions might entail moving from on-premises to the cloud or from one cloud storage provider to another. Regardless of the motivation or destination, the common thread in organizations approaching these projects is the desire to better understand the data they have so they can make better decisions about where the data should go, how it should be labeled, and who should have access to it. This is where an intelligent data migration solution can help. Using artificial intelligence, the solution can discover and classify your unstructured data at scale, and automate the labeling and moving process.
If you are looking toward an upcoming data migration, here are four key tips to make sure you are prepared to take action to lower risk in your organization.
1) Give Yourself Enough Time
Time is critical when it comes to executing an intelligent migration. A common mistake organizations make is to start looking at strategy, partners, and tooling after the project has started and deadlines are set. The deadline for migration is often the end of an existing contract with a cloud service provider. And if that deadline is looming, it may force the migration team to skip important steps or simply do a lift-and-shift to move the content quickly.
The problem with this is that you are perpetuating your problems and increasing risk. You will still be paying for storage of data you may not need. If you have unstructured sensitive data, you may be giving more, or the wrong people, better access to it. Fundamentally, you need to ensure you have time in your project to understand your data and make decisions on where that data is best suited before you start moving it.
The forward-thinkers will start the “intelligent” part of the migration before they even have a migration need. There is nothing stopping an IT organization from getting a solution for data management and migration that has a solid, pre-trained artificial intelligence that can crawl through their structured and unstructured data to provide new insight. This would allow the organization to make smart decisions about data storage and access that will better protect them from data privacy regulations now and in the future as migrations happen.
2) Evaluate Risk Exposure and Tolerance
An intelligent data migration is going to uncover sensitive data that you might not have known existed. The hard part is figuring out what the right thing to do with that data is. This may be different for different types of organizations that are under different regulations. Before you begin your migration, you need to determine how you want to label and classify certain types of content. With this determined, you can configure the intelligent data migration solution to automatically classify and label data according to these conditions.
In order to figure this out, you need to have a handle on the industry-specific regulations and data privacy regulations pertaining to the regions you operate in. For instance, if you are a healthcare business, you need to factor in HIPAA compliance and if you operate in Europe, you need to understand the GDPR. You can find a comprehensive list of all data privacy regulations here. Work with your legal team to create an understanding of how you need to handle data, including its labeling, storage, and permissions, so you can be ready to configure and act on the data assessment.
3) Look for Opportunities to Expose Data for Business Improvements
On the flip side of better restricting and protecting sensitive data is the concept of making data more accessible for collaboration and business intelligence. Take the time to talk to the various business units to determine what data they’d like to have access to. You can also work with data analysts to see what data could be leveraged for business intelligence platforms that are not currently accessible or in the correct format today.
Uncovering opportunities will help you to configure the intelligent data migration solution to provide appropriate labeling and access to this data automatically. Taking the time to do this can bring incredible gains for the business—both in improved productivity, but also many times in creating new revenue opportunities from better data insights.
4) What if You Have a Deadline Forcing a Traditional Migration?
Sometimes you can’t change the deadline and a more traditional migration approach is the only option. It’s not ideal, but you can still assess and clean up your data after the move.
Without a looming migration deadline, you can take advantage of an intelligent enterprise data management solution and perform the same assessment with automated discovery, labeling, and classification of your data. The key steps here will be to delete or move unneeded data to cheaper archival storage. Then with the data you have left, you’ll need to pay close attention to access rights to ensure that sensitive information is not available to all.
The overall goals are the same with this approach as with intelligent migration, you’re just doing it after the move versus before. But the effort is worth it to lower your costs with your new cloud service provider and more importantly, to lower your risk of violating data privacy regulations.
You Don’t Need a Migration to Start Intelligent Data Management
It doesn’t matter if you know your migration deadline or you’re not sure if or when you’ll need to migrate. The bottom line is that every organization has unknown, unstructured data that they need to get a better handle on. Data privacy regulatory bodies are starting to hand out very large fines and companies need to ensure they are as compliant as possible to reduce or hopefully avoid fines.
The amount of data that organizations are creating is rapidly growing in volume. This means that the problem of unknown data is only getting bigger. It just makes sense to start working with an intelligent enterprise data management solution (that could also help with migration as needed). Enterprise data management is an ongoing need before, during, and after migration. The more you understand your data, the better you can stay compliant and lower data risk.