Harnessing Big Data Platforms for Deeper Financial Insights
You harness big data platforms for deeper financial insights by unifying market, transactional, and operational data in a governed environment where streaming analytics and AI workloads run close to the data. When this is done with disciplined cost controls and tight governance, you shorten time-to-analysis, improve risk responsiveness, and scale decisioning without turning your cloud bill into a surprise. This article breaks down what a “big data platform” means in real financial work, where warehouses still win, and how lakehouse-style stacks change the operating model for analytics and AI. You will also get practical architecture patterns for running Databricks and Snowflake together, guidance for market data onboarding, and the operational guardrails that prevent cost and reliability failures. What Is A Big Data Platform In Finance, And How Is It Different From A Traditional Data Warehouse? A big data platform in financial services is less about a single product and more about an...