The multinational credit card and payment services provider faces challenges with their Data Science team in conducting long-term historical analytics on vast data using a shared Hadoop infrastructure. Hadoop, while excellent for distributed cost-effective storage and handling unstructured data, often involves lengthy data preparation, slow query execution, and resource contention, limiting efficient data exploration and AI model training. SQream DB offers a complementary solution that integrates with Hadoop to overcome these limitations. It is a GPU-accelerated analytics database designed for large-scale, complex data workloads.

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