3 verified briefings on Data Architecture. Each story includes a plain-English summary, why it matters, and the concrete action engineering teams should take.
Traditional BI semantic layers standardize business metrics for reports and dashboards. However, to ground AI models effectively, a new 'context layer' is needed. This layer provides deeper business context, relationships, and operational data, ensuring AI applications generate accurate and reliable insights.
Managing numerous schemas in data pipelines like Kafka and Flink can become complex and costly. An InfoQ article explores this "schema proliferation" and suggests a consolidation strategy to simplify queries, reduce maintenance, and make systems more scalable and resilient.
NASDAQ handles up to a trillion messages daily across its 26 business lines. To manage this massive scale, the company built a governed intelligence layer using dbt and Databricks. This modern data stack enables them to ensure data quality, security, and accessibility for decision-making.