Data Migration Framework
Customer Company Size
Large Corporate
Country
- Worldwide
Product
- CloverDX
- Workday
Tech Stack
- Data Migration
- Data Validation
- Data Ingestion
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Professional Service
Applicable Functions
- Business Operation
Services
- Data Science Services
- System Integration
About The Customer
The customer is a leading Workday Implementation Partner that provides consulting services to clients across the world. They specialize in implementing Workday for their clients and are experts in Human Capital Management (HCM). The firm serves a geographically and vertically diverse client base. As they operate with Workday as a single target system, their project engagements share many common characteristics and similar challenges. However, due to the increasing project load, the firm realized the need for a different strategy that would allow them to build a reusable migration approach.
The Challenge
The consulting firm was facing challenges with the quality of legacy data during the migration process to Workday. The poor quality of data was slowing down project delivery and taking valuable time away from the firm’s more critical objectives. The firm required a framework that would quickly identify and report data issues. Reconciliation of data in Human Resources was crucial for compliance with legal and regulatory concerns. The firm was looking for a solution that would simplify the data migration process and allow consultants to recoup time they were spending on the manual work.
The Solution
The solution was a data ingestion framework built by CloverDX's services team. This framework validates and transforms arbitrary customer data into a Workday‑friendly format. It directly supports Applicants, Hire Stack, Payroll History, Payroll Comparison, and Suppliers modules. The framework isolates and hides most of the complex processes, and consultants need only to configure inputs and project specific variables. Data quality checks were built into the framework, ensuring that consultants promptly identify faulty data. Workflows within the solution provide easy to understand error descriptions that can be shared back to the client. The solution is powered by a single node CloverDX Server running the automated data analyzer, database loader, and reconciliation.
Operational Impact
Quantitative Benefit
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