Sustainability often gets treated like a policy or a pledge. But real progress comes from concrete operational habits that IT teams can adopt directly and measure over time. The urgency is growing. The International Energy Agency projects that global data center electricity consumption will more than double to around 945 TWh by 2030, with AI the most important driver of that growth. That makes efficiency not only a sustainability goal, but an operating requirement.

Jumpstart the development of your context layer, and enable agents to reason across your entire business and provide trustworthy outputs.

Agentic analytics, embedded customer-facing reporting, and everyday business metrics now demand the same thing: performance at massive scale, and answers fast enough that a business user never notices the wait. Most generic databases were never designed for that combination. They assume a small population of analysts writing SQL and query latency measured in seconds, not AI agents and business users asking questions around the clock.

Until 2025, fitting a new table meant fitting a new model: engineer features, tune XGBoost, validate, repeat. Every CSV was a fresh problem, although tables share a great deal of structure. Tabular foundation models (TFMs) change the unit of work.

BigQuery augmented analytics Table-Valued Functions (TVFs) automate insight discovery and pattern explanation using AI, ML and statistical methods.

Every organization that adopts a cloud platform takes on a shared responsibility: the assurance that its vendors are secure, compliant, and resilient. This is where third-party risk assessments (TPRAs) come in with a systematic evaluation of a vendor's security posture, operational resilience, and compliance standards. TPRAs are a cornerstone of modern security and procurement programs because they provide structured, verifiable evidence of a vendor's security posture.

Push customer profiles, orders, products, and custom events into Ometria as they happen, and pull that same data back out into your warehouse or CRM, on schedule, with no engineering required. Ometria is a customer data and marketing platform built for retail and ecommerce brands. Marketing and CRM teams use it to unify customer profiles, track order history, and trigger lifecycle campaigns based on behavior like purchases, browsing, and loyalty status.

Analytics platforms are built to help organizations understand what their users are doing. Increasingly, they do much more than that: they connect behavioral data with customer context, power personalization, inform automated decisions, and provide intelligence to teams and AI systems. To do this well, analytics needs access to valuable data. That makes analytics more than a measurement layer. It makes analytics part of your security perimeter.

Analytics vendors claim their AI answers questions accurately, but almost none of them will show you how they checked. The standard move is a percentage with no denominator: "90%+ accuracy on internal benchmarks." No dataset you can download. No scoring method you can inspect. No competitor runs under the same conditions. You're asked to trust the grade without ever seeing the exam1 We ran the exam in public terms instead.