Implementation of a new system is exciting, up until the data migration process experiences unexpected hiccups despite impeccable planning. Losing or doubting the accuracy of the data you’ve spent years collecting and organizing would certainly dampen that excitement, to say the least.
Since data migration is a critical process when upgrading to a new system or transferring data between different storage devices, systems, or formats, undertaking a detailed plan for the process is the initial first step. This step and those that follow are discussed in great detail in the article “Data Migration – The Why, The What, and the How.”
We’ll cover the broad headings again as a refresher anyway so we can move on to the external factors that impact this process below.
Data migration projects usually take place in 5 stages:
- Design a Strategy – Plan for THE size and scope of the data migration project.
- Assess and Analyze – Assess the size and format of data to formulate how much of that data needs migration, and start considering an ETL project plan.
- Collect and Cleanse Data – Cleanse all the collected data to remove duplications and redundancies.
- Sort & Validate Data – Sort the data depending on your migration approach.
- Migrate – Begin migrating data according to your initial strategy. Once complete, test your system for discrepancies or lost data.
External Factors Contributing to the Success of Data Migration Plan
Let’s get back to the topic at hand. As the title suggests, we’ll be discussing the external factors that indirectly affect the data migration process, and could mean the difference between its success and failure. Here’s how you can mitigate the factors affecting the migration process to achieve the best possible results.
A fully functional data migration process must include the following considerations:
Is Your Data Migration Project Getting the Attention It Needs?
Selecting a new enterprise-wide system is a strategic business undertaking that deals with new technologies and professionals. Migration is usually a small part of a much bigger project. An average business typically focuses on system configuration and other technicalities rather than ensuring the data that will populate the new system is fit for purpose. This approach affects the migration process.
Holistically speaking, out of the plethora of tasks, data migration falls low on the list of priorities by management that considers it to be a simple task of transferring data and does not find the high costs and administrative burden justifiable. Thus, data migration, the resources it requires as well as the difficulty of the task is often underestimated and put on the backburner until it’s too late. Make sure that doesn’t happen with you.
Understand Design Requirements of Data Migration Plan
A firm grasp of the design requirements is critical, namely migration priorities and schedules, replication and backup settings, and capacity planning. A simple miscalculation in this area can have lasting repercussions that may impact the cost. This is also the stage where the IT department decides which migration strategy is suitable for the project – Trickle or Big Bang. Selecting one that suits you best is highly subjective to the firm’s existing data and future requirements. Let’s have a look.
Big Bang – This type of migration initiates and completes full transfer within a limited time frame. Expect some downtime as the data moves and processes, however, the project execution is rather quick.
Trickle – This migration strategy conducts the project in multiple phases. The target and source systems run simultaneously, which keeps the migration running in real-time. This type of migration is more complex and time-consuming as compared to Big Bang, however, it takes lesser downtime and eliminates operational efficiencies.
Allocate Budget to Hire an Expert
Quite a few tech-firms prefer a hands-on approach and migration budgets simply don’t allow for an expert’s input. Nevertheless, unless the firm happens to have an in-house migration specialist, they will need to spend money to save money by hiring a data migration specialist.
Collaborate with the End Users
The data migration process should be considered a business project, rather than a technical set of steps, that involves end-users. Your staff or customers will have a stake in the migration and understandable anxiety over its success.
Involve them: Depending on the specific data rules you plan to implement, consider which data should receive priority to migrate first. In addition, try to understand and implement what your end-users are hoping for from the migration: Better performance? Analytics? A simpler way to issue requests?
By following this approach, you will experience a far unified and comprehensive migration project that takes into account the concern of the stakeholders, and saves considerable time and cost in the long run.
Migration Isn’t Done in One Go
It’s quite common for a data migration project to have multiple phases. This is a known engineering practice that breaks down the entire process of migration into manageable chunks. Instead of attempting to resolve migration, risk errors, and redundancies in one go. In some migration cases, the first attempt fails and needs to be restarted. Multiple phases provide checkpoints allowing you to perform integrity checks as the migration progresses.
When compared to data migration, storage migration is far simpler as you don’t need to update old storage and map it to new. However, migrating data between vastly different storage systems is the real challenge. You can use Astera Centerprise to migrate data from one system to another in a code-free environment. The software enables fast data migration with built-in data quality features, advanced transformations, and support for a wide variety of data formats.
Backup Source Data
With massive amounts of data and restricted storage space, some data can’t be backed up. Should the worst happen, you’ll experience data loss during migration. Ideally, you must be well prepared with backups to restore data and try again. Since most databases usually have terabytes upon terabytes of data it is understandable that you may run out of storage space. In such a case, arrange for more backup space without hesitating. You cannot put a price on data you’ve spent years accumulating.
Data Migration Doesn’t Make Old Systems Useless
It’s quite likely that your old system will continue to be in use alongside your brand new replacement. Taking the old system offline immediately can prove to be counterproductive as the new rollout may experience some hiccups until it’s completely operational for the end-user. So, make a transition strategy that will allow you to easily move from your previous process to the new one without any hindrances.
Always Plan for the Future
Once all the data has migrated successfully, attempt to test the migrated data again using a mirror of the production environment. Once it checks out, you may go-live carefully and carry out final tests. When the environment is operating smoothly, you can shut off the old systems.
By taking into account the factors that contribute to migration, you can also take initiatives to make your life easier post-migration of your data. Rather than spending costly resources for updating source data before migration, you can establish analytics and governance controls in this new environment. Continuously monitoring migrated data to look for unusual access patterns, orphaned work sets, and security can also help you in the long run in improving your business processes. This will ensure that your enterprise data is utilized to the fullest and is readily available when and where needed.