Pinewood.AI Expands Dealer BI Platform with New Modules
Pinewood.AI has added Accounting & Finance and Customer modules to its dealer Business Intelligence platform, completing the Core Insights tier. The new modules deliver live operational dashboards, automated reporting and unified metrics, aiming to replace manual spreadsheet processes. Pinewood claims dealers can save up to 10 hours per week by using the integrated financial and customer‑journey analytics. The solution is now offered across Core, Enhanced and Strategic Insight tiers for dealers and OEMs.
Big Data Analytics in U.S. Finance: From Frontier to Settled Discipline
Big data analytics in U.S. finance has moved from a frontier technology to a settled discipline, with cloud warehouses, lakehouses and streaming pipelines now commoditized. Proven use cases—Customer‑360, risk, fraud and regulatory analytics—consistently generate ROI, while speculative projects often bleed...
Architecting Petabyte-Scale Hyperspectral Pipelines on AWS
The article outlines a petabyte‑scale hyperspectral data pipeline on AWS that moves raw sensor cubes from remote fields to queryable tables using an S3‑SQS‑Lambda‑Batch ingestion flow, aggressive S3 lifecycle tiering, and an Apache Iceberg medallion lakehouse. Edge containers on NVIDIA...
Teradata Factory Offers an On-Prem Foundation for the Agentic Enterprise
Teradata announced the Teradata Factory, an on‑premises extension of its Autonomous Knowledge Platform built on Dell Technologies hardware. The solution unifies the full Teradata software stack—including AI Studio—under a single management plane and supports enterprise data warehousing, lakehouse, and GPU‑accelerated...
AI Success Depends on These Data Governance Metrics
Enterprises are realizing that traditional data‑governance dashboards, which focus on documentation and ownership, fall short for AI workloads. New metrics—such as lineage completeness, certified dataset usage, and pipeline observability—measure data trust at runtime, ensuring AI systems draw from reliable, up‑to‑date...
How Insurer Aviva Migrated 1.3PB of Siloed Data to Become "AI-Ready" In 7 Months
Aviva completed a lift‑and‑shift migration of 1.3 petabytes of siloed data from Oracle Cloud to Snowflake in just seven months, creating a unified data platform. The new architecture underpins its AI initiatives, allowing the insurer to launch AI‑driven services such as...
The AI Data Governance Gap that Keeps Getting Worse
Enterprises are rapidly embedding AI into products, but most overlook data governance. Production databases are routinely copied into dev environments, data lakes, and third‑party services without clear oversight, leaving real customer records exposed. The article cites a mid‑size lender where...
Your Data Engineers May Be More Influential than You Think
The role of data engineers has shifted from reactive ETL developers to owners of modern data platforms that power analytics, AI, and real‑time applications. Cloud‑native warehouses, tools like dbt, Airflow, and Fivetran, plus CI/CD practices have turned pipelines into software‑engineered...
Christophe Pettus: PARTITION MERGE/SPLIT, Once More With Locking
PostgreSQL 19 reintroduces the long‑awaited ALTER TABLE … MERGE PARTITIONS and ALTER TABLE … SPLIT PARTITION commands, allowing administrators to combine or divide partitions with a single DDL statement. The implementation opts for an AccessExclusiveLock on the parent table, meaning the table is completely...
From Bottlenecks to Breakthroughs, Enterprises Are Rethinking Analytics in the Lakehouse Era
Enterprises are abandoning fragmented data stacks in favor of open lakehouse architectures paired with next‑generation analytical engines. Legacy warehouses, OLAP tools, and streaming layers have become costly and brittle as petabyte‑scale data and real‑time use cases proliferate. Modern solutions such...
Ten Years of Beam: From Google's Dataflow Paper to 4 Trillion Events at LinkedIn
In August 2015 Google published the Dataflow paper that introduced a unified model for batch and streaming. The model became Apache Beam, now an Apache top‑level project that processes 4 trillion events per day at LinkedIn and powers workloads at Palo...
From Data Chaos to Discovery: Building the Data Foundation for AI-Ready Scientific Research
Life science organizations are overwhelmed by fragmented, petabyte‑scale data that hampers AI deployment. Legacy storage‑centric architectures force repeated copying, incurring a “data tax” that slows research and raises compliance risk. Experts argue that an AI‑ready data strategy—rooted in FAIR principles,...
Beyond IT: A Three-Stage Framework for Turning Data Governance Into Board-Level Strategy
Boards are now required to oversee data governance as a core component of operational resilience, driven by regulations such as the EU NIS2 Directive and DORA. The article proposes a three‑stage framework that first translates cyber risk into business language,...
Migrating Data Ingestion Systems at Meta Scale
Meta has completely overhauled its massive data ingestion pipeline that extracts petabytes of social‑graph data from one of the world’s largest MySQL deployments. The new self‑managed warehouse architecture replaced customer‑owned pipelines and was migrated in three disciplined phases—shadow, reverse‑shadow, and...
One Context Layer, or Many?
The article debates whether a single, centralized context layer or multiple distributed metadata sources should power AI agents in the modern data stack. It argues that while centralized catalogs offer convenience, they become stale and lossy for agents that need...