July 7, 2022

A Guide to Data Migration

Technology has advanced in all spheres at an unprecedented pace during the past two decades. As did, the migration of data. It seems that data is always in need of migration. Whether it’s from legacy systems onto the latest, on-premises to cloud, or operational to archive, data is always on the move.

In most businesses, data migration is a regular business process. Whether it’s implementing a new system or shifting information to a more secure location, a solid data migration strategy can make a big difference for executive teams and IT departments.

Recent Gartner data indicates that about half of all data migration projects will either exceed predetermined budgets or hurt the overall business. This is due to the fact that data migration projects are complex, time-consuming, and require the participation of multiple systems, technology, and tech teams.


What is Data Migration?

Data migration involves moving data between different types of file formats, databases, or storage systems from one location to another, from one format to another, or from one application to another. This generally occurs when new systems are introduced or data storage is moved. It is often more than just moving data between systems. A data migration can involve more complex processes such as data mapping and re-formatting.

Key Factors for Data Migration:

Regardless of the type of data migration you undertake, you will need to consider the following key factors:

  • Data Integrity
  • Business Impact
  • Cost
  • User Experience and Impact
  • Potential Downtime
  • Data Assessment
  • Data Quality


Types of Data Migration

There are six main data migration types:

1. Storage Migration:

This involves moving physical blocks of data between different types of hardware (such as tapes or disks).

2. Database Migration:

This kind of data migration is used to move a database from one vendor to another, or to upgrade the software currently in use for the database.

3. Application Migration:

The process of migrating data occurs when a company switches from one framework to another system or vendor. Each application can have different operating systems, virtual machine settings, and management tools during development and implementation. It is therefore crucial that this software communicates with the other.

4. Business Process Migration:

When a merger or acquisition occurs, business management tools that are used to manage the company’s business practices will need to be replaced or updated. This can require data movement from one store to another, or from one database to another.

5. Data Center Migration:

The data center is a physical infrastructure in which organizations store critical applications and data. Therefore, migration of data centers can refer to many things, from relocating existing computers to transferring all digital assets, including business applications and data, to new storage and servers.

6. Cloud Migration:

As mentioned above, cloud migration encompasses all the above-mentioned scenarios that involve moving data from on-premises to the cloud. According to Gartner, cloud computing will attract over 45 percent of IT spending by 2024 and drive a growing number of IT decisions.


Understanding the Challenges You May Have to Face

According to industry analysts, around two-thirds of Fortune 1000 companies are involved in data migration or data conversion projects at any given time. However, 70 to 80% of these projects fail, resulting in billions of dollars in losses. Data migration is inherently risky. The process of migrating legacy data to a new environment requires more than just technical expertise.

Below are a few tips for preparing for potential challenges you might face:

  1. Ignoring the importance of data quality
  2. Lack of awareness of data quality issues among business users and high-level executives
  3. Absence of a cohesive migration plan that binds everything together
  4. Poor Execution
  5. Lack of organizational planning
  6. Defective target system
  7. Lack of awareness of data privacy


The 7 R’s of Data Migration

Consider these seven critical characteristics when planning your data migration strategy:

  • Robust: Handle all phases of data migration efficiently, from data extraction and transformation to authentication and loading into the destination system, even when data volume is high.
  • Resilient: Easy to modify and handle problems in the operating environment.
  • Rapid: Efficient process execution by utilizing the existing source or destination facilities.
  • Reporting: During the migration process, progress pointers should be provided.
  • Reconciliation: Verify that the process has been completed.
  • Recoverable: When a failure occurs, the data should be retrievable.
  • Reusable: Process modules should be reusable, including transformation utilities, error control, data cleaning procedures, etc.


Data Migration Strategies

The two most common methods for Data migration are:

1) Big Bang Migration: This approach involves moving all the data at once from a source environment to a target environment. The main disadvantage of this approach is that all live systems are taken offline during the data migration process.

  • Less costly
  • Less complex
  • Less time
  • All changes happen once

2) Trickle Migration: Also called iterative migration or phased migration. Using agile techniques, the data migration process is divided into sub-processes with their own goals, timelines, scopes, and quality checks. Data is migrated in small increments by running the old and new systems simultaneously. Therefore, there is no downtime and your customers can access your services 24/7.


Less chance of unexpected failures No downtime is required


More expensive Needs extra effort and resources because you have to keep two systems running


Data Migration Tools

There are three types of data migration tools:

  • On-premise tools enable intra-organizational data transfers with hardware installed on-premise
  • Open-source tools are community-developed tools available for a low price or for free
  • Cloud-based tools that move data between systems and applications


Process for Data Migration

The data migration strategy will be determined by the needs and goals of the organization, but there is a common data migration plan that can be followed. To ensure a successful data migration, here are the key steps to take:

Pre-migration planning: Evaluate the existing data assets, create a data migration plan, explore and assess the source and target systems, their operation environments and adaptability, estimate the budget and resources needed for the project, and set timelines.

Perform Data auditing and profiling to examine and cleanse the full scope of data to be migrated.

Migration design: It’s here that organizations define their migration approach – a big bang or a trickle. As part of the migration design process, technical specialists, developers, and data engineers – write scripts to make the data transition possible.

Execution: This is where migration – or data extraction, transformation, and loading – takes place. Downtime must be considered when planning the execution. It is important to select the right projects, specify the data types to be migrated, provide user mapping details, and check the source and target templates before flipping the switch.    

Testing & Validation: The migration testing and validation process ensure that data in the target system is accurate and valid. In addition to testing and go-live, it is equally important to establish a process or system to audit the migrated assets and data to ensure accuracy.


Final Words:

Even if it does not happen now, every enterprise will want to successfully move their data in the future in order to improve their ability to navigate the digital landscape and build tangible business solutions.

From strategy to development, execution, and testing, ZoftSolutions, a reliable digital transformation Company in Canada can handle the entire migration process between complex systems, ensuring a fast and secure transition. By partnering with qualified computer scientists and data migration experts, we plan, implement, and complete your data migration projects quickly and efficiently.


Tags data migration digital transformation