An e-commerce giant headquartered in the west coast. A household name for people worldwide, they have come up with path breaking innovations that revolutionize online customer experience.
Having undergone a recent divestiture, there was a pressing need for a fast, reliable way to ensure the separation was smooth. Data consistency and integrity was top most priority, but so was time.
The scope and goals of the project included:
The industry itself is highly regulated and required setup migration projects to be carefully controlled and audited. Reports had to be available in real time for business users.
Legacy data in Oracle EBS (their source) wasn’t consistent and complete.
In previous acquisitions, the users had performed setup migrations, but with limited success for the amount of work involved. The time consuming process was affecting their bottom line, and users needed a repeatable, reliable setup migration process.
Given the constant inflow of users, data quality had taken a hit. The need to establish standards, improve quality and data governance were of top priority.
The number of source and target instances made this a rather challenging scenario, one apt for dataZap’s hub-and-spoke architecture. While there was an automated process available for copy & migration of setups from one instance to another, the transformations, validations & customizations for each instance were complex.
Business users had previously spent hours to ensure compatibility, and were unable to do the same in this situation. Had to learn dataZap on the go, and incorporate learnings from one iteration on to the next.
Overall, it was an exhilarating process of planning, doing, checking and adjusting. A lean-agile approach was adopted.
ChainSys was able to complete the setup migration for the divestiture in six weeks. The accelerated timeline was aided by dataZap’s preconfigured templates, which covered 80% of transformation, mapping, data quality, extraction and loading requirements. The additional 20% were configured (on dataZap’s code-free platform), to fit the university’s unique needs. Manual efforts were reduced to nearly 30% in the final iterations.
The approach to copy existing setups, and transform it into a new instance was followed, with a success rate of close to 97%. The process which was adopted is shown below at a high level.
dataZap - Pre-Configured Templates & Migration Engine to Extract, Transform, Pre-Validate, Load, Reconcile & Report.
dataZen - To 'Get Clean' and 'Stay Clean', and Introduce Master Data Governance.