importance of data migration and standardisation

In data migration why data cleansing and standardisation is critical

Preparing for a data migration can be a real daunting project for any organisation looking to update or change solutions. However, it is essential to understand its critical facets to ensure a seamless ERP (Enterprise Resource Planning) Software transition. In this blog we will outline three key elements: Data Cleansing, Data Mapping, and Validation/Testing, to help you migrate ERP software more effectively.

In this episode of the ERP Readiness video series, our CEO Rob Jurcec, discuss the critical requirements for data migration.

What are the challenges associated with data migration?

The complex process of moving data from one system or storage location to another is known as data migration. While technology elevates efficiency and accessibility, yet organisations should be alert to inherent challenges. Here are some of the key challenges associated with data migration:

1. Data Integrity: Ensuring the integrity of data during migration is crucial. The risk of data corruption or loss during the transfer process is a significant challenge. It is essential to have robust data validation procedures in place to minimise the risk of data integrity issues.

2. Compatibility: Compatibility issues between different systems or platforms can pose a significant challenge in data migration. If the target system does not support the same data formats or structures as the source system, it can lead to data loss or data transformation errors. Thorough testing and validation are necessary to ensure seamless compatibility.

3. Downtime and Disruption: Data migration often requires a certain amount of downtime, which can disrupt normal business operations. Minimising the impact on day-to-day activities is crucial. Planning and scheduling the migration during off-peak hours can help mitigate downtime and minimise disruptions.

4. Time and Resources: Data migration can be time-consuming and resource-intensive, depending on the complexity and volume of data. Adequate planning, budgeting, and resource allocation are essential to ensure a smooth migration process.

5. Data Security: Data security is a critical challenge during data migration. Transferring sensitive or confidential information without proper security measures can increase the risk of data breaches or unauthorised access.

How can data migration risks be managed?

Data migration is vital for businesses, shifting essential information from one system to another. However, it also comes with its fair share of risks with this process. For you to ensure a successful data migration process, it is crucial to have strong risk management strategies in place, just in case. Here are some key steps to manage data migration risks:

1. Thoroughly assess the existing data: Before initiating the data migration process, it is crucial to conduct a comprehensive assessment of the existing data. This involves figuring out the categories of the data, their level of sensitivity, and any potential migration-related risks.

2. Plan and prioritise: Develop a well-defined migration plan that outlines the specific steps involved, the order of migration, and the timeline. Prioritise the migration based on the criticality and importance of the data, ensuring that any potential risks are addressed early on.

3. Conduct a data quality audit: Ensure that the data being migrated is accurate, consistent, and complete. Conduct a data quality audit to identify any inconsistencies or errors, and take the necessary measures to rectify them before migration.

4. Perform thorough testing: Test the data migration process extensively before executing it on a larger scale. In order to find and address any potential problems or hazards, this includes evaluating the migration of a small selection of data.

5. Backup the data: Prior to the migration, ensure that a reliable backup of the data is created. This serves as a failsafe in case any data is lost or corrupted during the migration process.

Data cleansing and standardisation best practices

When you’re moving data from an environment location to another, cleanliness isn’t optional; it’s imperative, that’s because dirty data can confuse analytics, disrupt reports, and weaken decision-making. Before migration, a good strategy for preparation is to backup your data before extraction, conduct a thorough data audit, try to find mistakes, discrepancies, and duplicates in your current dataset. This will reduce storage requirements and improve computing power workloads by the smaller size of data you are extracting. A clean, standardised data set not only enhances operational efficiency but also ensures reliable reporting and data-driven decision-making.

Remember, accurate data is the essence of your ERP software application.

The need for data mapping

Migrating data from legacy systems involves more than just a ‘copy-paste’ operation. Every system has its own distinct data structure that you should consider. That’s where data mapping and transformation come in. Data mapping defines the format between fields in your source system and those in your new ERP solution. This essentially serves as a blueprint for transferring your data between the two solutions so they are speaking the same language.

Don’t forget to backup your data before initiating the migration process, it is crucial to back up your data to prevent any potential loss or corruption. Create a comprehensive backup plan that includes regular backups of your data throughout the migration process to ensure data integrity and minimise any potential risks. Properly executed, these steps minimise risks like data loss or corruption, ensuring a smooth migration process.

Validation and testing: Your safety net

Before your fresh data in your new solution goes live, it should go through a comprehensive validation and testing phase. Conduct data reconciliation to confirm source and target system consistency. Validate integrated processes within your selected ERP to ensure they function as expected. By completing comprehensive testing you can identify discrepancies early, mitigate operational impact, and set the stage for a smooth transition.

You need to give your attention to data cleansing, meticulous data mapping, and rigorous validation, this ensures your business leverages the full capabilities of any ERP implementation.

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