/ Blog

Product Updates & Insights

Data & Analytics Engineering: What Do Enterprises Really Need?

Enterprises don’t have a data tooling problem—they have a strategy problem. This post breaks down why modern stacks keep failing, why AI needs a real data foundation, and how AI-native platforms will redefine data & analytics engineering.

Thought Leadership

January 22, 2026

Data & Analytics Platform Engineering: How Did We End Up Here?

From legacy systems to modern stacks, data engineering has traded old pain for new complexity. This post reflects on 20+ years of lessons—and why AI-native platforms are poised to reset how data platforms are built and scaled.

Thought Leadership

January 22, 2026

Data & Analytics Engineering: What Do Enterprises Really Need?

Enterprises don’t have a data tooling problem—they have a strategy problem. This post breaks down why modern stacks keep failing, why AI needs a real data foundation, and how AI-native platforms will redefine data & analytics engineering.

Thought Leadership

January 22, 2026

Data & Analytics Platform Engineering: How Did We End Up Here?

From legacy systems to modern stacks, data engineering has traded old pain for new complexity. This post reflects on 20+ years of lessons—and why AI-native platforms are poised to reset how data platforms are built and scaled.

Thought Leadership

January 22, 2026

Data & Analytics Engineering: What Do Enterprises Really Need?

Enterprises don’t have a data tooling problem—they have a strategy problem. This post breaks down why modern stacks keep failing, why AI needs a real data foundation, and how AI-native platforms will redefine data & analytics engineering.

Thought Leadership

January 22, 2026

Data & Analytics Platform Engineering: How Did We End Up Here?

From legacy systems to modern stacks, data engineering has traded old pain for new complexity. This post reflects on 20+ years of lessons—and why AI-native platforms are poised to reset how data platforms are built and scaled.

Thought Leadership

January 22, 2026

Data & Analytics Platform Engineering: How Did We End Up Here?

From legacy systems to modern stacks, data engineering has traded old pain for new complexity. This post reflects on 20+ years of lessons—and why AI-native platforms are poised to reset how data platforms are built and scaled.

Thought Leadership

January 22, 2026

/ take the leap forward

The Future of Data Engineering Isn’t Coming—It’s Here.

Be the first to put AI Agents to work across your data stack.