This is our story of co-creating an intelligent automated solution with a wearables technology leader to successfully migrate vast quantities of data from a legacy environment to a cloud platform.
Digital and wearable technologies are revolutionizing healthcare delivery with the sheer volume and velocity of data they generate. However, storing and managing such data in a legacy environment can be difficult. A cloud infrastructure with massive storage and computational capabilities is better suited to the workload.
However, moving from a traditional environment to the cloud is complex and prone to pitfalls. A well-planned and automated data migration strategy is necessary to successfully execute the transfer and secure the data.
Migrating data from enterprise systems to a cloud platform to implement a cloud-first data strategy that would reduce costs, maximize data monetization and improve data analytics.
The company was migrating data manually, which was complex, costly and fraught with delays. Technical differences in the data storage format between the two systems meant that identifying and mapping the target data model accurately, reconciling data and validating schema had to be done with painstaking care to ensure data integrity and consistency.
The scale of the undertaking added to the challenge, as the company had acquired high volumes of supply chain operations data across enterprise systems. Each step of the migration was slow, error-prone and lacking in visibility.
Leveraging Triange NxT, a key pillar of WNS Triange (our AI, analytics, data and research practice), to co-create a solution that could move large datasets from the old platform to the cloud.
Our team of data engineering experts defined a strategy that employed extensive automation, including a custom-built, AI-enabled migration accelerator. The accelerator dynamically created the target data model, schema, partitions and optimal system resource usage for speedy data migration.
Key aspects of the Python-based solution included:
Map and design an automated data structure for the new cloud environment, which helped reduce errors and the time required to implement the migration. Key outcomes included:
40 percent reduction in migration timelines
30 percent acceleration in time-to-market for new products
30 percent savings in managed services cost
Timely decommissioning of all legacy systems
Significant reduction in data reconciliation effort
WNS Triange (formerly WNS Research and Analytics practice) powers business growth and innovation for 120+ global companies with Artificial Intelligence (AI), analytics, data and research. Driven by a specialized team of over 4000 analysts, data scientists and domain experts, WNS Triange helps translate data into actionable insights for impactful decision-making. Built on the pillars of consulting (Triange Consult), future-ready platforms (Triange Nxt), and domain and technology (Triange CoE), WNS Triange seamlessly blends strategy, industry-specific nuances, AI and Machine Learning (ML) operations, and intelligent cloud platforms.
Driving a futuristic edge are WNS Triange’s modular cloud-based platforms and solutions leveraging advanced AI and ML to provide end-to-end integration and processing of data to actionable insights. WNS Triange leverages the combined strength of WNS’ domain expertise, co-creation labs, strategic partnerships and outcome-based engagement models.
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