The last decade of data tooling has been obsessed with one question: Where should we store the data?
Snowflake vs. Databricks vs. BigQuery. Warehouse vs. lakehouse vs. lake. Billions in venture capital, all focused on the architecture of storage.
Meanwhile, analysts still spend less than 20% of their time actually analyzing data. The rest disappears into searching, preparing, and navigating between tools.
The Warehouse-Centric Worldview
Walk into any data infrastructure conversation today, and someone will ask within five minutes: "What's your warehouse?" The underlying assumption is intuitive: centralize and organize the data correctly, and everything else falls into place.
But access isn't the bottleneck anymore. The analysis workflow is.
The Numbers Tell a Different Story
Most organizations now have their data centralized. The warehouse wars produced mature, powerful infrastructure. Yet the productivity crisis in data teams has only deepened.
- Analysts spend their days preparing, not analyzing. A 2024 TDWI survey found that project teams spend over 61% of their time on data integration and preparation.
- Tool fragmentation fractures the workflow. Knowledge workers toggle between apps an average of 1,200 times per day, losing approximately 4 hours weekly.
- Knowledge disappears when it's needed most. Alation's State of Data Culture Report found 96% of companies lost critical institutional knowledge from staffing changes.
A Different Bet: The Workspace
What if we organized around the work instead of the infrastructure? Software engineering made this shift decades ago. Developers don't organize their thinking around the Git repository—they organize around projects and workflows.
A warehouse-centric platform asks: How do we make queries faster? A workspace-centric platform asks: How do we create a workflow where exploration naturally becomes automated analysis?
What Workspace-Centric Actually Means
For Individual Analysts: Start with the question, not the schema. Context persists across your analysis workflow. Your exploration today informs your work tomorrow.
For Teams: Shared understanding of what exists and why. Clear handoffs between exploration and automated workflow.
For the Organization: Business questions become visible. Knowledge capture happens where work happens. Reduced rework, faster time to insight.
What We're Building
At Veritly, we're building a data intelligence platform designed around this belief—where the analysis workflow is the first-class citizen, not the warehouse connection.
Join the Veritly waitlist to see how we're building the future of workspace-centric analytics.
