engblogs

A pragmatic guide to business analytics that shows how data, analytics and machine learning transform raw information into actionable insights across descriptive, diagnostic, predictive and prescriptive analytics, powered by modern visualization and scalable data architectures.

Technical deep-dive into UNC6201's zero-day exploitation of Dell RecoverPoint for Virtual Machines, detailing BRICKSTORM's replacement with GRIMBOLT, the C# Native AOT backdoor, and VMware pivot techniques.

Leverage Databricks Model Serving to achieve low-latency, high-throughput real-time inferences at high QPS by deploying models behind route-optimized endpoints and applying scalable, production-grade best practices.

Technical overview of how The Marketing Cloud, Databricks Clean Rooms, Adstra, and Stagwell enable privacy-first identity resolution and secure first-party data enrichment for omnichannel marketing.

Global queries in BigQuery enable querying distributed data across regions with a single SQL statement, eliminating ETL and enabling secure, governance-friendly multi-location analytics.

Explores self-proving models that certify their outputs to a verification algorithm via interactive proofs, using transcript-based learning and verifier-feedback-driven learning to guarantee correctness with high probability and detect incorrect results.

Strategies to drastically reduce Out-of-Memory Errors in Apache Spark deployments at Pinterest.

Capsight transforms Caper’s edge-captured, multimodal store data into a self-improving data-to-model flywheel—accelerating AI training through AI-assisted annotation and distributed learning to dramatically shorten end-to-end cycles.

Databricks AppKit and Replit enable rapid, production-grade development and deployment of data- and AI-powered enterprise apps on Databricks, with built-in governance and secure integration across data sources and models.

Practical guide to German possessive pronouns, showing how gender and case determine endings, base forms, and usage patterns for singular and plural nouns.

Proposes Krites, an asynchronous, LLM-judged caching policy for tiered LLM architectures that expands static cache coverage by validating near-threshold prompts with an LLM and promoting verified matches into the dynamic cache, boosting static hits without increasing critical-path latency.

Shows how Agentforce replaced fine-tuned models with a constrained, multi-stage DSL to deliver deterministic, high-accuracy Flow generation at scale across 461 billion monthly executions, with validation at every stage and metadata discipline.