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Solution: We implemented an enterprise-grade Hadoop platform that ingests and harmonizes the retailer’s rapidly expanding customer data in near real-time. The new environment turns billions of raw records into a unified 360° customer view, surfacing deep behavioral insights. Marketing teams now tap this intelligence to launch hyper-personalized campaigns—lifting engagement and delivering measurable revenue gains.

Solution: We migrated the retailer’s click-stream and transactional data to a Cloudera Big Data environment built for elastic scale and low-latency analytics. Every web, mobile, and in-store interaction now arrives in real time, is unified into a single customer journey, and feeds live dashboards. Merchandising and marketing teams leverage this insight to spot trends, tweak promotions instantly, and meet evolving shopper needs—driving higher engagement and measurable revenue gains.

Solution: Successfully migrated the Green Plum Clusters to CDP 7.1.9, integrating Hive, Impala, Kudu, Kafka, Spark, and Scala. This modernization led to true real time capability with 40% improvement in data processing speed and scalability, ensuring more reliable and efficient trading operations. With more than 24 PB of data and 1M+ per second processing speed, this has helped the exchange with significant capabilities to generate new growth oppurtunities

Solution: Transitioned Customers Teradata, Datastage, and Hadoop stacks to Google Cloud, optimizing performance and reducing costs by 50%. Post-migration, Customer reported a significant reduction in data retrieval times, enhancing customer service responsiveness.

Solution: Implementing a CDP-based Hadoop Big Data system for a leading small finance bank in India, aimed at modernizing their enterprise data platform with a capacity of 2 PB. The solution is designed to provide the bank with a competitive edge by enabling advanced analytics capabilities, driving significant operational efficiencies, and enhancing compliance, controls, and risk management frameworks.