Category: Analytics

Insurance fraud remains a significant challenge for the insurance industry because fraudulent claims can increase loss costs, reduce trust, and consume investigation capacity that could otherwise be focused on serving customers. Traditional fraud detection approaches typically rely on rules-based controls, manual investigation triggers, historical claim patterns, and structured-data-only analysis. These approaches are useful for known […]

Specification-driven composition addresses a common scalability bottleneck in data pipelines. Data pipelines often start as simple scripts, but as they grow, you duplicate transformation logic and small changes cascade across multiple workflows. Copying and modifying data transformation logic across scripts leads to workflows that become difficult to manage at scale. Tracking what each pipeline does […]

Avanse Financial Services, India’s leading education loan providers, migrated to a cloud-native lakehouse architecture using Amazon SageMaker Unified Studio, which unified their data engineering, analytics, and artificial intelligence (AI) workflows in a single governed environment on AWS. In this post, we walk through their migration journey so you can adapt their approach to your own environment.

In this post, we show how to build a comprehensive scalable user search layer on top of Amazon Cognito using AWS Lambda, Amazon DynamoDB, and Amazon OpenSearch Service.

This post explores how Oldcastle used AWS services to transform their analytics and AI capabilities by integrating Infor ERP with Amazon Aurora and Amazon Quick Sight. We discuss how they overcame the limitations of traditional cloud ERP reporting to deploy real-time dashboards and build a scalable analytics system. This practical, enterprise-grade approach offers a blueprint that organizations can adapt when extending ERP capabilities with cloud-native analytics and AI.

The global real-time payments market is experiencing significant growth. According to Fortune Business Insights, the market was valued at USD 24.91 billion in 2024 and is projected to grow to USD 284.49 billion by 2032, with a CAGR of 35.4%. Similarly, Grand View Research reports that the global mobile payment market, valued at USD 88.50 […]

This two-part series shows how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. This post covers the process of collecting features in real-time and batch ingestion into an online store, and the technical approaches for stable operation.

Organizations managing large audio and video archives face significant challenges in extracting value from their media content. Consider a radio network with thousands of broadcast hours across multiple stations and the challenges they face to efficiently verify ad placements, identify interview segments, and analyze programming patterns. In this post, we demonstrate how you can automatically transform unstructured media files into searchable, analyzable content.

In this post, we follow Nielsen’s journey to build a robust and scalable architecture while enjoying linear scaling. We start by examining the initial challenges Nielsen faced and the root causes behind these issues. Then, we explore Nielsen’s solution: running Spark on Amazon Elastic Kubernetes Service (Amazon EKS) while adopting serverless concepts.

This post was co-written with Shyam Narayan, a leader in the Accenture AWS Business Group, and Hui Yee Leong, a DevOps and platform engineer, both based in Australia. Hui and Shyam specialize in designing and implementing complex AWS transformation programs across a wide range of industries. Enterprises that operate out of multiple locations such as […]