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Data and its application to key initiatives is the core of any successful business in today’s world. To keep up with their competitors, organizations across the board are working to better leverage their data, but many of them are challenged by the fact that a large portion of their data is unstructured. While this data is still valuable, it can be challenging to access and make proper use of it in enterprise applications and systems.

SEE: Data migration testing checklist: Through pre- and post-migration (TechRepublic Premium)

To ensure organizations can take full advantage of their unstructured data, they must often migrate and/or transform it into an organized and accessible format.

This data migration process is critical for businesses of all sizes. Whether moving data from an on-premises environment to the cloud or consolidating multiple databases, proper data migration is essential to maintain data integrity, reduce downtime and increase efficiency. In this guide, we’ll discuss how your company can handle the complexities of migrating and managing unstructured data.

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What is unstructured data?

Unstructured data is a type of information that is not organized in any predefined manner, which means it does not have a preset data model or schema. It may consist of text, images, audio, video, web pages or social media posts. This type of data cannot easily be analyzed due to its non-uniformity and cannot be stored in a relational database management system.

SEE: 5 tips to improve data quality for unstructured data (TechRepublic)

Because unstructured data is often in large volumes and from multiple sources, it requires more effort to analyze and extract value from it. To properly manage this type of data, it must be converted into structured data for better analysis and reporting.

Unstructured data migration plan

A comprehensive data migration strategy for unstructured data prevents subpar results and ensures a successful transition to the new system. Data migration teams need to consider the following factors when migrating unstructured data.

  • Data sources and target: Identify where data is coming from and understand the current data format and structure, as well as the required formats and structures of target systems.
  • Data quality: Define data quality criteria, assess and clean existing data, and identify any data validation rules that need to be implemented.
  • Data transformation: Determine the data transformation requirements and processes, such as field format conversion, data enrichment and data mapping .
  • Security: Ensure data security during the migration process and in the new database, as all sensitive data must be encrypted both at rest and in transit.
  • Timelines: Establish realistic timelines and goals for the migration.
  • Testing: Test the data and validate its accuracy before and after migration.
  • Documentation: Document the data migration process and results.
  • Maintenance: Establish ongoing maintenance and monitoring for migrated data.

Unstructured data comes in varying formats, versions and source systems. The key challenge lies in ensuring the data is moved effectively while still preserving data quality, accuracy and integrity .

7 best practices for migrating unstructured data

Creating an effective data migration plan optimized for unstructured data involves several best practices that need to be followed:

1. Perform a full data inventory

Before you begin your data migration project, create a comprehensive inventory of all the data that needs to be migrated, including the data’s name, location, size, format and complexity. This data inventory will help you determine the scope of your migration project and identify any data that may not be suitable for migration. When conducting an inventory, you should answer several key questions:

  • Where is this unstructured data located?
  • What types of files and folders do I have?
  • How many files need to be migrated?
  • What format is the data in?
  • What is the cost of storing this data?
  • Is any data sensitive or confidential?
  • What applications access this data?

Knowing the answers to these questions before you begin a migration project can help you develop a comprehensive migration plan. This will help ensure that the new system can support all the required processes and functions for your unstructured datasets.

2. Assess data quality

The quality of your data will have a direct impact on how successful your migration is.

To assess data quality, you should first examine the data’s structure. You’ll need to ensure that all data is properly organized, labeled and formatted. You should also examine any external factors that affect data quality, such as errors in source files or duplicate entries.

Once you have evaluated the data’s structure, you should look for any possible inconsistencies. Check for incorrect spelling, typos and any other errors that could affect the accuracy of your migration. You should also ensure that all data is up-to-date and accurate.

3. Ensure compliance

It is critical to ensure that your unstructured data complies with applicable laws, regulations and industry standards such as HIPAA, GDPR, GxP, PCI-DSS and SOX. To maintain compliance at all stages, you’ll need to ensure that the data migration process meets all relevant requirements for the laws that apply to your business.

SEE: Data governance checklist for your organization (TechRepublic Premium)

To begin, make sure you have the right security measures to protect data in transit and storage. This might include encryption at rest and in transit as well as other technical safeguards.

Additionally, it’s important to follow privacy best practices, such as ensuring only authorized personnel have access to the data. Have plans in place to manage both user and system access rights. Identity management tools can be used to streamline access management processes.

4. Monitor and manage your data

Monitoring and managing your data throughout the entire pre- and post-migration process is important. It not only ensures initial migration success but also helps to identify and address issues as quickly as they arise.

To effectively monitor and manage your data, you should set up an automated system that alerts you when issues develop. This could be a monitoring system that detects outages or a system that alerts you to potential security risks.

Additionally, you should create a process for regularly reviewing your data and the systems in which it resides. This will help you identify potential issues early on and address them before they become larger problems.

5. Test, test and test some more

Testing is a critical step in any successful data migration project. With thorough testing, you avoid introducing errors and unforeseen issues that can put your data at risk and cause lengthy delays in the process. It’s important to set up an extensive testing regimen to ensure data migrates successfully and accurately.

The first step in the testing process is to perform a complete pre-migration test. This should include all of the data sources and destination environments as well as validate the accuracy of all scripts and transformations you’ll use during the migration. By doing this before starting the actual migration process, you’ll better understand any potential problems that could occur.

SEE: Data migration testing checklist: Through pre- and post-migration (TechRepublic Premium)

The second step is to perform a post-migration test. After the migration is complete, you should thoroughly review migrated data to ensure it is accurate and complete. This should include validating that all fields are mapped correctly, that no data has been lost or corrupted, and that all business rules have been applied correctly.

Finally, you’ll need to conduct ongoing tests after the migration is complete. This will ensure any changes or updates made during the migration process do not introduce new errors into the system. Continuous testing will also help identify performance issues or scalability limitations that may arise over time.

6. Have a rollback strategy

A rollback plan allows you to restore the original state of your data should any issues arise. It is also essential to back up your data in multiple locations and test the restore process periodically to confirm it works properly. When developing your rollback plan, consider the following:

  • What will be the mechanism used to restore the data?
  • Will you use existing tools or create your own?
  • What is the timeline for restoring the data?
  • How often will you test the restore process?
  • How will you handle any potential conflicts between versions?
  • How will you communicate the plan to stakeholders?

SEE: Best backup software (TechRepublic)

Having a comprehensive rollback plan in place will give you peace of mind and allow you to recover quickly from any problems that may develop during the migration process. It is also essential to document the entire process so stakeholders know the plan that’s in place.

7. Migrate to the cloud

Moving unstructured data to the cloud can provide many benefits, such as increased storage , cost savings, scalability, flexibility and security. Migrating to the cloud can be a great way to store and manage unstructured data specifically, especially due to its flexible formats and the many managed service providers that can help with data management. With the right provider and proper security measures, you can easily keep your unstructured data safe and secure in the cloud.

Steps for migrating unstructured data

The goal of migrating unstructured data is to properly store and protect data while making it more accessible to the right users. If not done right, it can lead to data loss and new system inefficiencies.

To help make sure your migration plan is successful and appropriately set up for unstructured data migration, here are the basic steps to follow:

Analyze your data

Start by identifying your data types and determine how much data you need to migrate; this is especially important if you plan to move your data to the cloud.

Clean up your data

Once you’ve inventoried your unstructured data, you’ll want to clean up any unnecessary or outdated information so the data you are migrating is accurate and up-to-date. This includes removing any duplicate data and checking data for accuracy and integrity.

Establish a migration plan

This includes understanding the project’s scope, setting up a timeline and determining the best migration tools and strategies. It’s also important to document any risks associated with the migration.

Prepare for the migration

Make sure all systems are properly configured for the migration and users are adequately trained to use the new system or platform. You should also consider backing up any existing data before beginning the migration. At this point in the process, you’ll especially want to pay attention to your unstructured data. Is it in a format that will be compatible with the new system? What changes need to be made to prepare it for migration?

Perform the migration

Execute the migration plan according to your timeline. Monitor the migration process to ensure it is going as planned and troubleshoot if new problems arise.

Complete the migration

Review your results and ensure all data was migrated correctly. With unstructured or previously-unstructured data, take an even closer look. Does this data still make sense in the context of the new system? Has it been altered in such a way that it is no longer usable?

If your data team follows these steps for migrating unstructured data, you can expect to have a migration that is equal parts quick and effective, no matter how many obstacles you may run into.

Read next: Top cloud and application migration tools (TechRepublic)