Custom data migration remains quite an obscure topic since there is little helpful documentation regarding this subject. Thus, it may become a challenging task to customize your data migration for the first time. Considering the nature of client-side software programs, it is impossible to test potential permutations of datasets the users have. Also, you can find it hard to fix any problems that can occur during the data migration process.
At the same time, application migration or consolidation always serves as an efficient business driver. It means replacing or augmenting legacy systems with new apps that share the same dataset. Today, custom fields migration is crucial for companies that seek to move from on-premises infrastructure to the cloud. That allows optimizing or transforming their business.
What is a data migration process?
Data migration serves as a one-time process of moving internal information from one storage location to another. The particular process can involve preparing, extracting, and, if needed, transforming the data. Besides, migration projects always require high-quality preparation, strategy, and quality control.
From an ideal viewpoint, you can complete custom data migration with no information loss. And you can avoid manipulating manual data minimally or re-create it. To ensure the success of the process, you need to apply a data backup system. Also, a good option is to use a method to test obtained results. Data migration is complete if the original information storage is shut down.
The process of data transfer is traditionally a component of a larger business project like:
- The replacement of an old software system with a new one;
- The expansion of storage system capabilities;
- The introduction of a new system that functions in conjunction with the existing one;
- The transformation of organization’s data into one centralized information storage solution;
- The migration of data to cloud storage;
- The compliance with new rules is based on a merger, which means that all data must be stored in one system.
A migration tool is a software used for managing or automating the migration of elements in a changing system. For example, it refers to moving an app to a new operating system. That allows facilitating the migration of on-premise services to the cloud, supporting visualization, or providing other changes. Besides, migration tools help catch various licensing problems occurring due to introducing a software program into the new environment.
What is a data migration strategy?
A data migration strategy helps improve the performance of the overall migration project. Also, it provides a company with a competitive advantage. If your IT professionals cannot migrate data appropriately into target systems, that will lead to duplicate efforts and errors. Thus, applying a wrong strategy means that issues related to the original source may appear in the new system.
In addition, incomplete strategies may cause missed deadlines, over-expenditure, and failures related to data transfer. In this case, your team should prioritize the migration process for ensuring successful outcomes.
All data migration strategies must include:
- Knowledge of a data switch. Teams need to conduct an audit on all source-target information. That allows checking data quality and preventing potential issues during transferring.
- Maintenance and protection. After some time, the information deteriorates and transforms into an unreliable one. Thus, your team has to apply data management strategies for optimizing data quality.
- Data governance. Tracking and reporting the quality of the organization’s data is crucial. That allows understanding data integrity better. Meanwhile, all apps that generate data must be intuitive and automated, which ensures a successful result.
Related: The Team Effectiveness and Different Roles in Teams That Win
Custom data migration serves as an essential element of the company’s brands. It refers to upgrading and consolidating databases and other apps. Thanks to an efficient data migration strategy, organizations can ensure data integrity, reduce costs, and eliminate manual effort.
What are the challenges of custom data migration?
Although data transfer has been widely used in the IT industry for many years, different issues still occur. Here we describe some critical challenges of custom data migration.
Data format
Users must provide their profile information in a valid CSV-formatted file and follow specific rules. For example, they must delimit fields in commas. Or they need to enclose fields that contain commas or line breaks using double-quotes. Thus, the data format issue appears when users create profile data. Typically, it refers to representing gender or date and time information.
Deduplication
Deduplicating user records in a relevant source file may become a challenging task. All customers must understand the business logic for handling collisions in data. Besides, they should consider:
- What data can identify the record uniquely?
- Do they have a timestamp for determining more recent data?
- Should they overwrite, ignore, or set to NULL blank values in a CSV file during the merge of duplicate records?
- Should they merge, update, or replace plural elements?
Downtime
A period of downtime is required by a big bang data migration strategy. It means that both employees and clients cannot access the database. Downtime results in a profit loss and inconvenience for companies that perform outside the typical schedule.
Mapping models
When adding new versions of your data models, you should select models they must base on. If your migration is lightweight, the persistent store provides automatic determination of mapping models for you. But if your migration is heavyweight, you need to create them. That is because you cannot make changes to the new models which heavyweight migrations do not support.
History consistency
Sometimes, you can linearize migrations manually when you have two development branches connected. During the edition of migration dependencies, you may accidentally create history inconsistency. It means that you have applied a migration without its several dependencies. Such a situation serves as a strong indication that confirms the incorrectness of dependencies.
How to plan custom data migration?
Custom data migration planning requires implementing some critical steps. Below, we describe how to customize your data migration process efficiently.
Build workflow
If the process allows it, you can iterate a workflow wherever possible. That allows making it much simpler for your users. An appropriate workflow may involve numerous actions hidden in transitions. From a technical standpoint, you should provide your workflow with different functionalities and make them available for users.
Clean database
Your team should address any issues regarding the database before transferring information. This process may require applying specific software programs or other tools provided by third-party vendors.
Develop mapping
When conducting custom data migration, you need to map information from the legacy systems to relevant cloud schema attributes. Also, you have to transform data into the format used by a cloud platform. Such mappings and transformations may be determined thanks to using a specific mapping table.
Schedule data switch
After picking the data migration approach, engineers should set the budgets required for completing the task. Besides, they have to schedule a data switch, set timelines, and provide management with this information.
Conclusion
Custom data migration may present a suite of complex issues for modern companies. It can be challenging to move big data appropriately and apply the correct migration software tools. After all, businesses cannot copy and paste process information to integrate millions of data units into one storage location.
But to provide an efficient data transfer process, organizations should implement specific migration strategies. That allows obtaining more knowledge about data integration and various migration tools. When you find it complicated to move data with no damage or loss, you can apply some best practices. Ultimately, the first step for each company is to understand the nature of custom data migration better.
