Category: Case Study – Data Engineering
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Leveraging Data Engineering to Optimise Real-Time Fraud Detection
A fast-growing fintech company struggled to detect fraud in real-time due to limitations in their data infrastructure. They were processing vast amounts of transaction data but lacked the automated pipelines and real-time capabilities necessary to identify suspicious activity as it happened. The company needed a robust data engineering solution to build scalable pipelines, improve data…
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Implementing Data Engineering to Support AI-Driven Product Development
A rapidly growing SaaS company faced challenges in feeding reliable data to their AI-driven product development efforts. Their data pipelines were not scalable, and inconsistent data quality was slowing down the development of AI features, such as recommendation systems and predictive analytics. The company needed a robust data engineering solution to automate data collection, improve…
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Automating Marketing Data Pipelines for Multi-Channel Campaigns
A large telecommunications provider was struggling to manage data from multiple marketing channels, including email campaigns, social media, and customer interactions. The siloed nature of the data made it difficult to create a unified view of customer engagement, which limited their ability to run effective, personalised multi-channel marketing campaigns. The company needed a data engineering…