Chaos to Cohesion | The Art of Data Migration
  • Astrinos Andreadakis
  • 07 November 2023

Chaos to Cohesion | The Art of Data Migration

 

In the world of data migration, adhering to best practices is essential to prevent common pitfalls that can lead to data loss or compliance issues.

Transferring data from one system to another involves several crucial factors that require careful consideration. The fundamental objective of any data migration is to 'do no harm'; in essence, this means maintaining the security, accuracy, and integrity of the information being transferred.

System transformation and the associated data migration are typically undertaken to improve data quality and processes and instil confidence in the data being used across the organisation, leading to valuable insights.

Executing this transfer demands careful planning and extreme care, as even the slightest mistake can cause significant issues down the line. Therefore, it is vital to clearly understand the necessary steps and approach the process with clarity.

 

Key Elements in Data Migration:

Let's delve into the key elements involved in any data migration:

Data Governance
Often overlooked, aligning data governance with the migration is essential. It involves formalising the roles and responsibilities of data owners during and after any data migration. It ensures that data is consistently managed and used appropriately. During a migration, governance structures should be formalised to determine data ownership, compliance requirements, and security measures.

Best Practice: Establish a data governance framework before starting the migration to avoid ambiguities regarding data ownership and control.

Assessment & Planning
A comprehensive assessment of the current data landscape and stakeholders is crucial. Legacy systems and processes often result in data silos and hidden data sources. Before migrating data, organisations should conduct an in-depth audit to understand the types of data, dependencies, and the overall impact on business operations.

Best Practice: Identify redundant, obsolete, and trivial (ROT) data that should not be migrated, reducing system clutter.

Data Cleansing
This requires a common-sense approach to what and how can be cleansed. Detailed analysis and prioritisation are necessary to ensure your data is clean and useful. This step is crucial because poor-quality data can lead to inaccurate reports, operational inefficiencies, and poor decision-making in the new system.

Best Practice: Implement automated tools to cleanse data efficiently and avoid manual errors.

Data Profiling
This involves profiling all data and data sources to identify risks, priorities, ongoing use, and the needs of data owners. By profiling data, organisations gain insights into data accuracy, completeness, and relationships between different datasets.

Best Practice: Use data profiling to identify gaps and inconsistencies that need resolution before migration.

Data Mapping
Source-to-target mapping can be a detailed and tedious process. Collaborating with the right partner can make this process smoother and less daunting. Without accurate mapping, data can become disorganised, leading to missing information, mismatched records, and incorrect field placements.

Best Practice: Work closely with experienced data specialists to create a detailed mapping document that aligns with business needs.

Testing
Thorough testing throughout the planning, design, execution, and maintenance stages is crucial for a successful migration. Testing should include data integrity checks, functionality validation, and performance benchmarking.

Best Practice: Conduct multiple rounds of testing, including pre-migration, migration, and post-migration testing, to detect and resolve issues early.


Data Migration Strategy Infographic

 

Avoiding Common Data Migration Mistakes

1. Lack of Clear Objectives

Without well-defined goals, organisations may move unnecessary data, overcomplicate the process, or fail to achieve the desired business outcomes.

Solution: Set clear objectives that align with organisational needs, such as improving data quality, consolidating systems, or enhancing reporting capabilities.

2. Poor Stakeholder Engagement

Data migration affects multiple departments, yet key stakeholders are often not involved early enough in the process.

Solution: Engage stakeholders from IT, operations, compliance, and business units to ensure alignment and gather insights on data dependencies.

3. Insufficient Data Cleansing

Migrating inaccurate or duplicate data from legacy systems results in inefficiencies and user frustration.

Solution: Perform thorough data cleansing before migration to ensure only high-quality data enters the new system.

4. Inadequate Testing

Skipping or rushing through testing phases can lead to data corruption, integration failures, and system downtime.

Solution: Implement a rigorous testing plan, including unit testing, system testing, and user acceptance testing, before final deployment.

5. Underestimating the Complexity

Data migration is often more complex than anticipated, especially when dealing with large datasets or multiple integrations.

Solution: Allocate sufficient time and resources and consider partnering with experts to manage complex migrations effectively.

 

Asking the Right Questions: Creating the Perfect Customer View

While data migration should be simply a means to an end, it's essential to answer some fundamental questions in advance. Creating the 'Perfect Customer View' and asking the following questions can be a helpful exercise:

  • Why are we doing this?
    Presumably to meet a specific organisational objective or as part of an overall strategy.

  • What do we need to know?
    To gain the most valuable insights, it is important to focus on the key aspects of our customers, members, stakeholders, or donors.

  • What data do we currently have, and where is it located?
    A lot of the time, you might have lots of data, but it's spread throughout the organisation across disparate silos and systems.

  • What's missing, and how can we bridge the gap?
    Obtaining relevant data and insights may seem effortless, but you might not have all the information you need. Have you thought about how you can collect the necessary data? Can your new and improved processes and systems be of assistance in this regard?

 


Armed with a clear Data Strategy, some organisations engage fully during a Data Migration with precise objectives in mind. Others aim to move their existing data to new systems, often leading to the repetition of past mistakes.

Despite its daunting nature, data migration, with the right partner and full engagement from key stakeholders, can present a tremendous opportunity for transforming systems, data, and organisational culture. The journey from data chaos to data cohesion necessitates careful planning, meticulous execution, and close collaboration.

Most of these questions should be part of an overall Data Strategy or your Organisational Strategy and objectives - perhaps we can tackle that in a future article…