Data Migration Checklist: 6 Tasks to Execute
Data Migration Checklist: 6 Tasks to Execute
Progressing into the future requires salient solutions, but as an IT leader, you know this! If you have, let’s say an old legacy software or application, it’s time for a data migration checklist. Check out the 6 items necessary for your flight to the cloud.
What is Data Migration?
Data Migration is the process of safely transferring data between various formats, computing environments, and storage systems. This intimate process requires data being moved from one location, application, or system to another to ensure highly available data, integrity, and usability in a new environment. This is an integral process in numerous scenarios, such as system upgrades, cloud migrations, mergers, and consolidations.
First, it is imperative to understand a few key areas for your planning and preparation process to kickstart your data migration checklist.
Data Migration Key Aspects
- Storage Migration: This is where data is safely moved from one storage device to another, which could typically include on-prem storage to a cloud storage solution.
- Database Migration: This is where data is transferred between different database systems and could include changes to pertinent items like database schemas.
- Application Migration: Shifting data and application functionality from one environment to another occurs here, such as moving from a legacy system (mentioned above) to a modern application system.
- Cloud Migration: An all-encompassing approach that involves moving data, applications, and services from on-prem infrastructure to a cloud-based environment.
Now that we know several aspects of data migration, let us dive into the data migration checklist and the six things you must know for a successful migration process.
- Objective Setting
The planning stage will all depend on the type of data you want to move and the quantity of that data. If you have smaller data sets, it will require a different strategy that does not have as many moving parts and components as larger data sets. Additionally, you must understand what systems, applications, and users will be affected as a result of the migration. Ask yourself:
- Is this migration necessary?
- What’s my budget?
- What data needs to be migrated?
- Is the data old and needs cleansing?
- Will there be compatibility issues?
Ask yourself questions like these to keep yourself prepared. There are conventional processes for the planning phase, like sorting files and ensuring no redundancies.
- Migration Type
There are a few different approaches that can be instituted for data migration.
a. Big Bang Migration: This is where all data is transferred from the source system to the target system in a singular operation of high intensity.
- The migration is done all at once, typically during a scheduled period of downtime.
- The process is expedited since it’s completed in one operation.
- It requires extensive planning and testing to ensure a smooth process. There is also a higher risk of issues arising during the migration that could affect the entire dataset, which may cause a mass disruption.
b. Phased Migration: This is where data is broken down into smaller, manageable segments, leading to different parts of data being migrated in phases over a longer duration.
- Potential issues are mitigated because data is migrated in stages.
- Risk is also minimized because problems are addressed in one phase before the next occurs.
- The process takes much longer as data is transferred in multiple steps.
- Easier to manage and troubleshoot issues but requires continuous management and coordination. There may also be consistency issues as the source system is being utilized during migration.
c. Parallel Migration: This involves running the older system (the source) and the new (target) systems in unison during the transitional period, ensuring data can be migrated and validated in real time.
- Since both systems are active, there is a fallback in place in case issues begin to occur. Downtime is also reduced as systems remain functional.
- As data is being migrated, it can be checked and validated.
- To ensure a consistent flow, careful coordination is required.
If you have larger data sets, it may be wiser to consider the Phased Migration approach since data is not transferred all at once and is considered less risky. If you have smaller data to work with, the Big Bang Migration is often considered the most suitable strategy because the process is straightforward, expedited, and requires fewer resources. Ensure you understand all the associated risks and challenges you are sure to encounter during your data migration.
- Data Assessment
Next, assessing data is a critical migration step. Known as data profiling, this involves analyzing the source data and understanding its structure, volume, and quality while successfully identifying data dependencies and relationships. Some key considerations are listed above, but you should know what direction you want to head in by now. You will want to cleanse any data that has duplicates, errors, and inconsistencies while standardizing data formats and values to ensure your model of consistency. Mapping the data from the source system to your target system while defining transformation rules (this is if the data structures differ) will ensure your data is migrated accurately and transformed as needed.
- Tools/Technologies
The selection process for the proper tools and technologies is integral for a successful data migration journey. Your project must undergo strategic evaluation of various data migration tools that have different considerations (such as volume, complexity, and compatibility). After a thorough assessment is completed, it is imperative to select the tools most suitable to handle the volume of your data and its associated challenges and complexities. There are different tools for specific migration needs. You will need to consider tools relevant to your needs. Here’s a few you can consider:
ETL Tools:
- Informatica
- Talend
- Microsoft SSIS (SQL Server Integration Services)
- IBM InfoSphere DataStage
Data Quality Tools:
- Trillium
- Melissa Data
- Talend Data Quality
Data Integration Platforms:
- Matillion
- SnapLogic
- Pentaho
Cloud Migration Tools:
- AWS Database Migration Service (DMS)
- Azure Data Factory
- Google Cloud Data Transfer Service
Database-specific Tools:
- Oracle Data Integrator (ODI)
- SAP Data Services
- MongoDB Atlas Data Lake
Open-Source Tools:
- Apache NiFi
- Apache Kafka
- Apache Sqoop
- Design & Testing
Any good migration plan will require comprehensive designing and testing methods to address potential issues before the actual migration takes place. Developing a plan for migration must outline several ancillary steps, which include extraction, transformation, and loading of data. Additionally, necessary tasks and responsibilities must be assigned to the right people and roles must be understood. An MSP (Managed Service Provider) offers you the right people at the right cost, so you don’t have to worry about migration headaches. With a well-structured testing plan, criteria can be established for data validation and quality assurance purposes. These plans include unit tests, system tests, and user acceptance tests, ensuring data is migrated accurately and meets the necessary standards.
- Execution
Now that a plan has been devised, assessed, designed, and tested, execution is ready to occur. Data is extracted from the source system. Various techniques can be used for data extraction, such as full or incremental extraction. This is done while ensuring data integrity.
Then data is transformed to match the schema or parameters of the target system. Transformation rules are applied to convert the data into the target format and the data is loaded into the target system. This process includes inserting transformed data into the proper tables or data structures in the target system for accuracy and efficiency. Validation checks are performed throughout the execution phase to verify the migrated data is accurate and complete. Careful, continuous monitoring and proper management will be needed to address any reoccurring issues (like bottlenecks and data latency) and pounce on them to minimize potential disruptions.
Next, some optimization techniques may be instituted to catalyze proper performance. This can include tweaking data transfer speeds, performing database tuning configurations, and leveraging parallel processing where possible to expedite the migration process.
Some post-migration activities include...
- Final validation processes to ensure data accuracy and completeness
- Resolving any remaining data issues
- Setting up support channels for user queries/issues
- Documenting the migration process
- Ensuring stability and performance of the new system
- Planning for updates
Conclusion
As an intensive and multifaceted process, data migration necessitates thorough planning, risk assessment, and careful execution. While there are more steps involved meant for professional data veterans, you can ensure a successful data migration by adhering to a careful planning process. If your team lacks the optimal experience needed for this transition, it is imperative to incorporate outside perspectives to ensure a smooth process.
That’s where an MSP like DataStrike comes in handy. With best-in-class monitoring and management in coordination with an on-shore delivery model you can rely on 24x7x365, we ensure a smooth data migration process by becoming an extension of your team. Data migration is no joke, and our team of certified professionals will provide the services listed above with power and precision to deliver you an electrifying experience unlike any other. Click here for more info on our data migration services.
About DataStrike
DataStrike is the industry leader in 100% onshore data infrastructure services and enables companies to harness IT changes as a catalyst for growth. With a network of highly specialized experts, strategic partnerships with the world's biggest technology providers, and a platform agnostic approach, DataStrike provides innovative solutions and practical guidance to accelerate digital transformation initiatives and drive better business outcomes for small-to mid-sized businesses. Click here to learn more about our service offerings.
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