Data Engineering

#data-engineering

Reimagine 2025 Recap: Unlocking AI-Ready Data, One Agent at a Time

We’re entering a new era where humans and AI collaborate through shared understanding, not just shared tools. This means data teams are facing a new mandate: stop preparing for AI, and start working with it. At Reimagine 2025, Collate’s virtual summi...

Introducing AskCollate: Talk with Your Data for Faster, Smarter Work

Most data teams still spend hours chasing tables, fixing quality issues, or verifying reports, rather than analyzing data to drive business impact. The problem isn’t the value of data. It’s that it’s hard to find, understand, and trust across scatter...

Announcing Collate 1.9

Building on the robust Model Context Protocol (MCP) integration introduced in version 1.8, we've continued focusing on delivering features needed by modern data teams. Today, we’re announcing Collate 1.9 of our managed OpenMetadata service that addre...

MCP Sample Uses in Collate

Introduction We recently introduced Model Context Protocol (MCP) in Collate, the details of which are covered in this blog. A visual run-through is available in this YouTube video. This blog is going to run you through some of those examples to show ...

Data Diff in OpenMetadata and Collate

In large-scale data operations, data is continuously transformed, migrated, and replicated across different systems. Ensuring the consistency of this data—especially between systems like OLTP databases and OLAP warehouses—is a challenging but crucial...

Simple, Easy, and Efficient Data Quality with OpenMetadata

Data quality and reliability are two top priorities for organizations. Many organizations have made considerable investments in Data Quality initiatives. With the current crop of tools, success has been limited due to tool disconnect, lack of collabo...