The client needed high data processing, increased flexibility, and wanted to become a self-serve analytics-driven organization capable of leveraging industrial-grade analytics models.
Brillio proposed an AWS-based cloud data platform. For the implementation, we leveraged the Brillio catalog accelerator for one-time metadata creation, along with pyspark for data merge. We also helped with self-service data preparation capability using a template-based approach, and enabled metrics computed using Athena for automated feed to consumption layer – Tableau, data feeds, and APIs.
Brillio also implemented an automated test framework using APTA – Brillio testing accelerator to comprehensively manage data quality for effective build and maintenance, and future data science use cases using multiple domains of data addressed – business, product data, consumer data, lead data, marketing data, etc.
Following the implementation, the client immediately started seeing a significant improvement, from a 4x ROI increase – with a profit of $28 mil, to much more streamlined and optimized data operations.
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