Greg Hochard

Default alt text
August 26, 2025

AI-Driven Data Provisioning Is the Future of Pharmaceutical Breakthroughs

In the pharmaceutical industry, speed is everything. The faster you can develop a new drug, test it in a clinical trial, and get it to market, the better the outcomes are for the patients and the business alike. But that all hinges on the ability to access data. Without insights,...

Default alt text
August 21, 2025

Quantifying the ROI of Data Governance: How to Get Buy-In

Default alt text
April 24, 2025

Data Product Provisioning: The Manual vs. Automated Debate

Despite advances in cloud technology, 64% of data leaders report facing significant challenges provisioning timely and secure data access. Data governors and stewards are caught in the middle of this dilemma, tasked with ensuring that data products are readily accessible and valuable, while also being secure and compliant. Traditional methods...

Default alt text
April 22, 2025

Beyond Workflows: Why Data Products Need a Data Marketplace 

Companies today are only as successful as their ability to put data to work. They invest heavily in pipelines and workflows to create valuable data products for analytics and AI. Yet, data product owners and data governors often realize something crucial is missing: a simple, secure way to find and...

Default alt text
April 17, 2025

Transitioning from Data Schemas to Data Products with the Immuta Data Marketplace

The Immuta Data Marketplace solution marks a shift in how data is accessed and utilized internally: Moving away from exposing raw tables and schemas, and toward delivering polished data products. Why does this transition matter? Raw data alone doesn’t guarantee value – and raw data alone doesn’t equal success. Data...

Default alt text
April 8, 2021

Why Your Data Governance Strategy Is Failing (And How to Fix It)

Loading the Elevenlabs Text to Speech AudioNative Player… At-a-glance: Data governance strategies typically fail due to manual processes and legacy tools, inability to scale, data classification issues, silos and fragmentation, reactive approaches, lack of clear KPIs and executive buy-in, and failure to adapt to AI. By embracing automation, decentralizing data...

Ready to get started?