Data Mapping and Transformation for ERP Migration Training Course

Data Mapping and Transformation for ERP Migration Training Course

Introduction

Migrating to a new Enterprise Resource Planning (ERP) system is a critical, complex undertaking that hinges on the successful movement of data from legacy systems to the new platform. The greatest risk lies not in the software implementation, but in the Data Migration process itself, specifically the intricate stages of Data Mapping and Data Transformation. In a world driven by Data Integrity and Regulatory Compliance, a flawed migration can lead to major operational disruption, inaccurate reporting, and financial penalties. Data Mapping and Transformation for ERP Migration Training Course addresses this fundamental challenge, providing the essential, high-impact skills required to execute a seamless ERP transition and establish a foundation for future Digital Transformation.

This intensive training provides a best-practice framework for navigating the technical and governance complexities of any major ERP rollout. Participants will master ETL/ELT principles, develop robust Data Cleansing methodologies, and create comprehensive Source-to-Target Maps with advanced transformation logic. By focusing on real-world Case Studies from successful and failed migrations, this course ensures practical proficiency in managing data quality, mitigating risks, and achieving Stakeholder Alignment. By the end, attendees will be equipped to serve as vital contributors to a high-quality, first-time-right ERP go-live, accelerating Business Process Optimization and maximizing the ROI of the new system.

Course Duration

5 days

Course Objectives

1. Master Source-to-Target Data Mapping principles for complex ERP data models.
2. Design and implement advanced Data Transformation Logic to meet new system requirements.
3. Apply Data Profiling techniques to assess and benchmark Data Quality in legacy systems.
4. Develop a robust Data Cleansing and Data Validation strategy prior to extraction.
5. Execute an effective Extract, Transform, Load process for mass data movement.
6. Ensure end-to-end Data Integrity and Data Reconciliation between source and target systems.
7. Identify and mitigate critical Data Migration Risks and complexities during cutover planning.
8. Define and manage Master Data Management (MDM) requirements within the migration scope.
9. Navigate Regulatory Compliance for sensitive data during migration.
10. Automate mapping and transformation tasks using modern Data Integration Tools.
11. Document clear Data Lineage to track data flow and support auditing requirements.
12. Facilitate effective Stakeholder Alignment and data ownership across business departments.
13. Lead the final Data Validation and User Acceptance Testing (UAT) for a successful go-live.

Target Audience

1. Data Migration Specialists/Analysts.
2. ERP Implementation Team Members.
3. Data Governance/Quality Managers.
4. Business Intelligence (BI) Analysts.
5. Master Data Management (MDM) Team.
6. IT/System Integration Specialists.
7. Key Business Stakeholders.
8. Project Managers/Program Leads.

Course Modules

Module 1: Foundational Concepts & Migration Strategy

• ERP Migration Lifecycle and the critical role of Data Migration.
• Defining the Data Migration Strategy
• Understanding Master Data, Transactional Data, and Configuration Data.
• Case Study: Analyzing a failed "Big Bang" migration due to poor planning and data scope creep.
• Key Risk Mitigation and Dependency Management.

Module 2: Data Profiling & Quality Assessment

• Techniques for Source System Analysis and Data Discovery.
• Applying Data Profiling tools to measure completeness, consistency, and uniqueness.
• Identifying and prioritizing data to be Cleansed versus data to be Archived.
• Case Study: A manufacturing firm using data profiling to reduce customer master duplicates by 40% before migration.
• Establishing clear Data Quality Rules and Acceptance Criteria.

Module 3: Core Data Mapping Techniques

• Developing the Source-to-Target Mapping Specification document.
• Mapping data entities, fields, and values between dissimilar data models.
• Handling One-to-Many and Many-to-One relationships and complex keys.
• Case Study: Mapping complex general ledger accounts from an old system with a flat structure to a new multi-dimensional ERP structure.
• Best practices for documenting transformation logic and business rules.

Module 4: Advanced Data Transformation

• Designing and applying transformation logic
• Implementing data Standardization and Normalization rules.
• Managing Historical Data transformation and archiving strategies.
• Case Study: Transforming global customer addresses and phone numbers to a single, standardized format for a new CRM module within the ERP.
• Handling data enrichment and derivation requirements.

Module 5: ETL/ELT Process and Tools

• Overview of Extract, Transform, Load and Extract, Load, Transform methodologies.
• Selecting the right Data Integration Tool
• Designing the Staging Area and interim data structures.
• Case Study: Comparing the performance and complexity of an ETL and an ELT approach for a large-volume retail ERP migration.
• Developing and optimizing extraction and loading scripts.

Module 6: Data Validation and Reconciliation

• Creating a multi-stage Data Validation Framework
• Techniques for Record Count Verification and financial Data Reconciliation.
• Designing data comparison reports and discrepancy resolution workflows.
• Case Study: A financial services company using three-way reconciliation to ensure regulatory compliance on financial data.
• The role of User Acceptance Testing (UAT) in data sign-off.

Module 7: Data Governance & Compliance

• Establishing Data Ownership and data stewardship roles in the new ERP.
• Integrating Data Governance policies into the migration process.
• Managing sensitive data and ensuring Regulatory Compliance throughout all stages.
• Case Study: Implementing masking and anonymization transformations to ensure GDPR compliance during testing phases of a European HR system migration.
• Defining and maintaining Data Lineage for auditing and transparency.

Module 8: Cutover & Post-Migration Activities

• Developing the Cutover Plan and managing final migration timelines.
• Performing the last-mile migration and system switch-over.
• Post-Go-Live Data Monitoring and Hypercare Support strategies.
• Case Study: Review of a successful two-day cutover weekend for a large supply chain ERP, detailing the rollback plan and communication strategy.
• Lessons Learned documentation and establishing ongoing Data Quality Maintenance procedures.

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.