Simor Consulting
Category: Data Architecture
A financial services firm running analytics on trade settlement data came to us with a specific complaint: their cloud data platform cost had tripled in eighteen months, and nobody could explain why.
A recommendation system team built their tenth model. Each model required feature engineering. Each feature engineering project started by copying code from the previous project, then modifying it for
Traditional centralized data architectures worked for BI but struggle with AI workloads. Centralized teams become bottlenecks as data volumes grow. Domain experts who understand the data are separated
Existing data infrastructure often cannot support ML workflows. The modern data stack offers a foundation, but it requires adaptation to become AI-ready. This article covers building a data architectu
Event-driven architectures treat changes in state as events that trigger immediate actions and data flows. Rather than processing data in batches or through scheduled jobs, components react to changes
# Serverless Data Pipelines: Architecture Patterns Serverless computing eliminates server management and provides automatic scaling with pay-per-use billing. These benefits matter for data pipelines
A semantic layer provides business-friendly abstraction over technical data structures, enabling self-service analytics and consistent metric interpretation. Implementing one involves technical challe
Data lakehouses combine lake flexibility with warehouse performance but introduce security challenges from their hybrid nature. Securing these environments requires layered approaches covering authent