Strategies for Successful Data Migration

    With global data volumes now measured in zettabytes and growing rapidly, traditional enterprise IT systems increasingly will have a harder time scaling with it, leading to replacing servers and devices or moving to the cloud. Regardless of which path your business decides to take, data migration is inevitable.

    However, data migration is a complicated and often expensive process. You will need the right approach to migrating data without error, including well thought-out strategies and appropriate tools.

    Also read: Best Cloud Migration Vendors & Services

    What is Data Migration?

    Data migration refers to the process of transferring data from one storage system to another. It begins with data selection and preparation, during which extraction and transformation takes place. Following this step, permanent data is moved from the old storage system and loaded onto an appropriate data store. Then, the data migration ends with decommissioning the old storage system.

    Data migration typically falls into one of two categories:

    • Cloud Migration: Data or applications are migrated from a physical storage system to the cloud or between two cloud environments.
    • Data Center Migration: Data is migrated from one on-premises data center to another for upgrading or relocation.

    After decide where you’re going to migrate, next you need to determine what you need to migrate:

    • Storage Migration: Data is moved from one physical storage solution to another.
    • Database Migration: Structured, or database managed, data is moved using a database management system.
    • Application Migration: Data is migrated from one computing environment to another to support a change in application software.
    • Business Process Migration: Business applications and data related to business processes and metrics are migrated.

    Why Do You Need Data Migration?

    Organizations opt to upgrade their storage systems and consequentially migrate data for several reasons that ultimately help them gain a competitive advantage. Database migration helps companies overcome storage limitations and can facilitate better data management features and processing speed. On the other hand, storage migration is chiefly focused on upgrading to support new technology.

    Other scenarios where you might find the need for data migration include:

    • You want to upgrade to a new infrastructure to make up for size constraints.
    • You want to optimize the overhead costs of running a data center.
    • You need to merge new data following an acquisition.
    • You need to relocate your data center.
    • You want to implement a disaster recovery solution.
    • You want to move an application to the cloud, for reasons ranging from ease of maintenance and access to cost

    Strategies and Precursors to Data Migration

    Strategizing in advance will help you save on costs and prevent downtime to ensure business continuity. It is essential to consider your limitations and understand the overall scope of your data migration project. There are two key factors that you need to consider before launching a data migration project, namely the size and time.

    • Data Size: Most datasets are too big to be simply uploaded to the cloud and will need to be shipped on physical devices. This is primarily because of speed and cost constraints. You can send data below 10TB through standard drives, while larger data in the petabyte range will need specialized devices meant for data migration.
    • Time Constraints: Bandwidth, network speed and limitations, and dataset size are key considerations when calculating how much time a data migration will take. If data needs to be shipped on physical devices, that time should also be taken into account.

    After considering data size and time constraints, you can formulate your project budget and timeline. You also need to decide on the tools and framework for database migration. This will give you an overview of the entire process of data migration.

    In addition, you will also need to decide on the migration approach, i.e., to pick between the big-bang approach and doing it in one go or the trickle approach–where you migrate in phases with both systems operating side-by-side.

    Also read: 5 Cloud Migration Strategies

    Key Steps to Data Migration

    Data migration is one of the most critical projects your company will undertake, requiring careful efforts at every step. The reason behind the complexity is that you do not want to compromise data quality, as data-driven businesses will suffer errors in core operations otherwise.

    After planning, there are roughly five more stages to data migration:

    1. Data preparation involves some key actions targeted at making the data suitable for the migration. Beginning with auditing, an automated process is run to analyze data quality and inform you about inconsistencies, duplicate entries, or poor health. Next, you back up files and establish access levels.
    2. Data mapping involves matching the data field between the source and the new destination.
    3. Execution is where data is extracted, processed, and loaded to the destination.
    4. Testing is ideally a continuous process in data migration, especially when you are migrating data in phases. Once the entire migration process is complete, you need to run another iteration of automated testing, fix the issues, and proceed to go live.
    5. Auditing the data again once it is live is necessary to ensure successful completion. You should also run timely audits and monitor the system’s health.

    Tools of Migration

    There are numerous tools that can assist you through the migration process. And many cloud providers offer their own set of tools. Other tools, including several free and open-source applications such as Data Loader by Salesforce, are also available. Like the migration types, the migration tools can be self-scripted, on-premises, and cloud-based. Other major tools include Amazon’s AWS Data Pipeline, IBM Informix, and Microsoft Azure CosmosDB.

    Also read: Successful Cloud Migration with Automated Discovery Tools

    Challenges in Data Migration

    Data migration is inherently complex, and there are likely going to be several challenges when carrying out this project in your organization.

    • Failing to include concerned parties might disrupt your business activities and the data migration process in general. Keep them updated on a weekly basis about the progress.
    • Lack of data governance or clarity about who has access to the data in the source system can create confusion and hamper data quality. A clearly defined data governance framework is essential to overcome this challenge.
    • A generic and unproven migration method might do more harm than good. Always look for a reliable testimonial-backed service provider, and pick an experienced team.
    • Insufficient skills and inadequate tools can both lead to unexpected delays and cost you valuable time. Give it due to research and ensure that the team assigned with data migration is sufficiently trained and has all the necessary tools.
    • Planning is indispensable. It might not be sufficient by itself to guarantee successful migration, but it is necessary.

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    Ready to Migrate Your Data?

    While data migration might not sound too daunting in theory, it is a complex process with many variables that must be figured out beforehand. Therefore, you’ll need a specialized team to execute and monitor the data migration process and treat it like a major project.

    You can also take advantage of several premium and open-source applications to help you with your data migration. Like the migration types, migration tools can be self-scripted, on-premises, and cloud-based, giving you plenty of flexibility to proceed with your data migration in a way that’s best for your company.

    Although it is a major undertaking, you can proceed without hesitation once you have given it due thought.

    Read next: Top 7 Data Management Trends to Watch in 2022

    Kashyap Vyas
    Kashyap Vyas
    Kashyap Vyas is a writer with 9+ years of experience writing about SaaS, cloud communications, data analytics, IT security, and STEM topics. In addition to IT Business Edge, he's been a contributor to publications including Interesting Engineering, Machine Design, Design World, and several other peer-reviewed journals. Kashyap is also a digital marketing enthusiast and runs his own small consulting agency.

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