Is your data house in order? Today, business leaders know that data powers the decisions that shape business outcomes and drive innovation. However, as the volume of data grows, ensuring its accuracy, consistency, and reliability has become an increasingly urgent challenge. According to , 64% of organizations now say data quality is their top data integrity challenge in 2025, compared to 50% in 2023—a clear indication that this problem is intensifying.

fleur-dQf7RZhMOJU-unsplash

8 Popular Data Quality Tools (Compared By Use Case)

Boston Children’s Hospital (BCH) is a world-leading pediatric medical center that plays a pivotal role in advancing children’s health globally. As artificial intelligence becomes more deeply embedded in clinical workflows—from diagnostics to predictive care—the value of AI in healthcare has never been higher. But to harness AI’s full potential, organizations must first establish a strong foundation of trusted, well-governed data.

boston-skyline

Inside Boston Children’s Hospital’s AI-Ready Governance Overhaul

In the modern enterprise, data has become both the foundation and the fuel for innovation. Yet, all too often, organizations treat data as an afterthought. They assume that once it’s collected and stored, it will simply work. The reality is vastly different: undetected entry errors, special characters in free‑text fields, or subtle schema drift can silently corrupt your pipelines. This leads to poor decisions, misaligned strategies, and wasted resources. 

tim-schmidbauer-E8F-reiR14w-unsplash

How to Address Data Quality Challenges in Large-Scale Data Environments

This year at the Databricks Data + AI Summit 2025, the energy was electric. As part of Alation’s team on the show floor, I had the chance to engage with hundreds of data leaders—from curious prospects to seasoned practitioners. Whether demoing at our booth, connecting with partners, or collaborating with American Airlines to prepare their breakout session, one thing was clear: the AI era is officially here—but only for those ready to simplify data complexity.

Screenshot 2025-06-16 at 11.37.17 AM

Databricks Data + AI Summit 2025: Key Takeaways 

The data product lifecycle follows established product development principles, where teams specify, design, develop, release, update, and maintain products throughout their operational lifespan. Best practices for defining and building data products follow common product development lifecycle models, making the potential applications virtually limitless for organizations ready to embrace this approach.

gidlark-abItvV1ihOM-unsplash

What Is the Data Product Lifecycle?

The metadata management market is exploding. Valued at $11.69 billion and growing at 20.9% annually through 2030, organizations worldwide are recognizing that metadata isn't just documentation—it's the nervous system of modern data architecture. Yet despite massive investments in data catalogs and governance tools, most data teams still struggle with the same fundamental problems: data discovery takes too long, AI projects stall due to data quality issues, and compliance remains a manual nightmare.

manuel-nageli-NsgsQjHA1mM-unsplash

What is Metadata Orchestration? The Complete Guide for AI & Data Teams

In the age of AI, one truth has become impossible to ignore: AI is only as trustworthy as the data it’s built on. And not all data is created equal. At the heart of enterprise success with AI, analytics, and compliance lies a subset of data that matters most—Critical Data Elements (CDEs).

logan-voss-FiNA200yGbk-unsplash

Turn CDE Policy into Practice with Alation + Blue Altair

At this year’s Snowflake Summit in San Francisco, thousands of data leaders gathered to explore how AI, cloud innovation, and modern data strategies are reshaping the enterprise. Alation was there, spotlighting real-world stories of data transformation from customers Boston Children’s Hospital, O’Reilly Auto Parts, Swire Coca-Cola, and Fortune Brands Innovations.

SnowSummit2025

Snowflake Summit 2025: AI, Data Trust, and Metadata in Action

As AI evolves from predictive models and chatbots into intelligent, goal-seeking agents, the conversation around Agentic AI is just getting started. 

jorge-mallo-cqK6Ysfhhb0-unsplash

Building Smarter Enterprises with Agentic AI: Key Takeaways from Data Science Connect

Subscribe to our blog

Gene-Arnold

Product Architect

Gene Arnold

Snowflake and Alation Partner to Drive Quality, AI-Ready Data

Snowflake-and-Alation-Partner-to-Drive-Quality-AI-Ready-Data-Featured-Module-647x357-2x

Alation-numbers-station

Alation Acquires Numbers Station: Enabling AI to Understand Structured Data at Scale

Reinventing the Role of Data Catalogs and Governance in the Era of Agents

Alation-Agentic-AI-Platform-Release-Blog-Hero-647x357-2x (2)

Blog hero image for Meet Alation’s New Data Products Builder Agent

Data Digest

Alation Acquires Numbers Station: Enabling AI to Understand Structured Data at Scale

Reinventing the Role of Data Catalogs and Governance in the Era of Agents

Alation’s New Data Products Builder Agent: Build Better Data Products—Faster

Filter by