Migrating Unstructured Data to the Cloud: Best Practices

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Most organizations and businesses should now recognize the vital importance of migrating data to the cloud. One of the biggest challenges that companies are likely to encounter in migrating their data to the cloud is transferring their unstructured data. 

Unstructured data already represents one of the largest problems to most enterprises when it comes to data management. That’s because unstructured data is more likely to take up a greater part of the budgets in IT departments and space in on-premise storage devices. When it comes to migrating unstructured data, the challenge is that most public cloud providers are not focusing on unstructured data migration, choosing instead to concentrate on accessibility and scalability. Fortunately, this is a challenge that is possible to overcome. 

Also read: Managing Unstructured Data Across Hybrid Architectures

What is Unstructured Data?

Unstructured data is simply any data that cannot be stored on an RDBMS, or relational database. Any data that can be stored on an RDBMS is referred to as structured data. This is data that is easy to analyze and search for because it adheres to pre-defined data models variables, such as numbers and text. 

Examples of structured data include names, addresses, dates, and financial data. It’s data that can be easily understood by and searched for in relational databases. 

Unstructured data, on the other hand, does not rely on pre-defined data models or variables, and thus cannot be efficiently stored on an RDBMS. Most data is actually unstructured data, and examples include rich media, audio, surveillance data, satellite imagery, word documents, emails, weather data, sensor data generated by IoT devices, and analytics generated by ML or AI algorithms. Most of this kind of data is stored in what is called a data lake, or a centralized repository that utilizes object storage for storing unstructured data. 

Also read: 6 Cloud Database Trends for 2022

Migrating Unstructured Data to the Cloud 

A recent survey found that over half of all surveyed business owners want to migrate most of their data either to a cloud or hybrid cloud environment. The process of unstructured data cloud migration will involve moving all of your unstructured data from your in-house IT infrastructure to a cloud storage provider, managed by a third party. 

Doing so offers a number of important advantages, including greater flexibility to expand (or reduce) storage requirements, lower costs, superior security and data recovery in the event of a hard drive failure, and the ease of accessing data from anywhere with an internet connection. 

Most businesses end up choosing a hybrid approach, meaning that some data is migrated to the cloud while other remains on-premise. With that said, organizations migrating their data to the cloud would be wise to keep the following four practices in mind:


Properly migrating data means first taking full inventory of your existing on-premise data, including how relevant it is, and if it contains any sensitive information that could be put at risk in the event of your company website becoming hacked or a data breach. 

Develop a classification taxonomy for properly organizing and prioritizing your data before beginning the migration process. If possible, try to use interactive tools that allow you to gain an overall view of your unstructured data based on the classifications developed in your taxonomy.


Data agility simply means being able to extract specific pieces of data quickly. In other words, it means ensuring your data storage is evolving just as quickly as the enterprise IT ecosystem as a whole is. 

Migrating data of any kind successfully always relies on steering clear of infrastructure inflexibility, which can result quickly in our rapidly changing ecosystem. It can only be a matter of months before currently data storage or migration solutions are rendered completely irrelevant. 


Make sure that any migration solution you utilize proves the integrity of your data to be migrated. Any data that is corrupted during the migration threatens the integrity of the other transferred data as well. Data migration solutions could come with strict auditing systems that can identify corrupt data and ensure compliance with standards such as the PCI-DSS security standards of the GDPR. Ensuring data integrity before and during the migration process could potentially save you thousands of dollars from fines or downtime. 


Relying on highly experienced data migration experts who specialize in unstructured data is essential. Either hire the services of an experienced professional, or otherwise ensure that you have access to a 24/7 support team from the migration service that you’re utilizing. Never embark on a data migration journey if you lack the expertise yourself. 

In order to successfully and accurately migrate their unstructured data on a large scale, companies need to focus on a strategy that revolves around taking proper inventory of the data to be migrated, agility and flexibility, having a strong 24/7 support system, and proving the integrity of the migrated data. 

Read next: Top Data Visualization Tools for Presenting Data

Nahla Davies
Nahla Davies
Nahla Davies is a software developer and writer. Before devoting her work full time to technical writing, she managed—among other intriguing things—to serve as a lead programmer at an Inc. 5,000 experiential branding organization whose clients include Samsung, Time Warner, Netflix, and Sony.

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