The project is for a client who is a popular global design organization located in the USA, with branches all over the globe. They have a team of designers, engineers, teachers, and researchers who look at creating change through design, by building learning platforms and tools to unlock creativity. They create human-centered inventions, services, spaces, and associations that empower groups, cities, and even countries.

The client was keen to migrate all their systems onto a single unified enterprise application with the latest technologies, for better management and maintenance. The chosen unified solution was Workday – a best-in-class application for finance, HR, and more.

There were a few challenges that were sorted:

• Workday API’s complex & large XML responses
• Client needing reusable & dynamic code to reduce development efforts
• Shutting down multiple applications and migrating to Workday using Big Bang approach without impacting business & users
• Workday integrations
• New technology (PySpark & Workday’s inbuilt XXLT code base)

Looking at the challenges faced by the client, SPEC INDIA defined four teams.

• Data migration team for carrying out data migration activities – pulling data from Power BI reports, converting them into workday-acceptable formats, and sending data to workday.
• Data integration team taking care of all Workday-to-Workday integrations & third-party to Workday integrations. All these integrations to be built in Workday Studio and keep running at defined intervals.
• ETL team taking care of pulling data from Workday, transforming & processing data, and sending processed data to a data warehouse for reporting purposes. Most of the ETL development is done in Azure Databricks and scheduled in Azure Data Factory.
• Reporting team to generate Power BI reports for Biz Ops and other stakeholders.

The project was to replace third-party applications (from different vendors & for different purposes) with one enterprise application (Workday).  The client was using different SaaS-based applications for HR, Finance, Project & CRM modules which was bit costly and required more support efforts and cost.

Key Components

• Data migration from legacy applications to Workday
• Explore Workday’s public web API to send & receive Workday data
• Migrate legacy applications code (from U-SQL) to Databricks (PySpark)
• Write Workday integrations to sync data within systems
• Retrieve & process Workday data (HR, Project & Finance data) in Azure Databricks through PySpark technology
• Create Power BI reports from processed Workday data for BizOps people