Systems | Development | Analytics | API | Testing

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.

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.

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.

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.

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

Tabular Foundation Models (TFMs) move tabular prediction from task-specific Gradient Boosted Decision Trees (GBDTs), such as XGBoost and CatBoost, toward “table-native” models built on In-Context Learning (ICL). The training data becomes a contextual prompt, and the model produces zero-shot predictions in a single forward pass without parameter updates.

On its own, gen AI runs your performance analysis without a trusted data foundation, without your business context, and without built-in analytical methods, and that leaves its answers open to mistakes. Databox grounds AI tools in all three.

Qlik has been named a Leader in the IDC MarketScape: Worldwide Data Intelligence Platform Software 2026 Vendor Assessment. I'll say the obvious part first: we're proud of this. Independent recognition matters, and this one reflects work happening across every team at Qlik. But analyst recognition on its own doesn't help you run your data estate.