“It’s just a quick ask.” Anyone who has worked with data has heard this phrase—a seemingly simple request: “Can we get a slightly modified report?” “What’s the regional breakdown for this other region?” “Just pull the data.” It sounds like something that should take minutes, maybe hours
The way we handle data is fundamentally broken. Across industries, businesses are trapped in a cycle of centralization—pushing everything into a data lake, warehouse, or some shiny new “lakehouse.” Why? Because getting data out of systems is so painful that the instinct is to store it all in one
Data is the lifeblood of modern business, driving everything from customer insights to operational efficiency. Yet, despite all the shiny tools, tech, and talent, most companies are stumbling. They’ve built impressive systems, but when it comes to making data work, they’re failing. Badly. Let’s be clear: this
Does your organization struggle with data sprawl? Do you have valuable information scattered across a myriad of different silos, tools, and personal computers? Are you dealing with duplicates or inconsistently named datasets that complicate the data management process? Or perhaps, your dilemma is having numerous different datasets with the same
Data integration tools are notoriously complex, and most organizations already have a substantial amount, so you're probably wondering... How long will it take to introduce this into my data stack and data operations workflows? TLDR - not long at all. Here’s why... No on-prem setup or software
At Matterbeam, we've developed an innovative model that addresses the pervasive complexity hindering effective data utilization in today’s companies. Our model moves away from traditional data pipelines, instead offering a framework built on the principles of immutability, transformation, composability, replication, domain-driven design, and streaming. For those who
