Services
About Mphasis
Our client is a leading Tier-1 US-based global logistics enterprise with diversified services spanning air, land and freight, servicing over 100 countries, is undertaking a multi-year, multi-cloud organization wide transformation to bring in data and intelligence in their core operations.
THE REQUIREMENT
The logistics giant turned to us to provide a superior integrated cloud environment with governed and secured data that would support the development of decision science capabilities and solutions. They also wanted us to enable business partner capabilities with the use of GCP tools and infrastructure.
We were the strategic partner in enabling the client to move to Google Cloud roadmap planning, implementation of Cloud standards and leading practices, and Cloud Ingress and Egress costs planning.
Our team built flexible workspaces for self-service BI, exploratory analysis and AI/ML on GCP, and ingested unstructured data on Google Cloud Storage. Automated data pipelines (CI/CD) and reusable parameterized load tasks and graphs in Ab-Initio were developed to handle thousands of source tables.
Deploying predictive analytics, we extracted insights on price and propensity to purchase. We created ML models in BigQuery using AutoML and SQL, and established Cloud DataLab for data exploration, analysis, visualization, and machine learning. Additionally, we transformed financial reports into JSON and performed sentiment analysis with Google’s ML APIs.
We also acted as a strategic partner in the move to Google Cloud roadmap planning, implementation of Cloud standards and leading practices, and Cloud Ingress and Egress costs planning.
Significantly improved turn-around time ~80% for the task
High levels of accuracy
Reduced tagging and research effort ~70%