/about
About
Independent analytics consulting focused on reliability, semantic clarity, and operational discipline.
[ peter putera ]
I run Dataroa, an independent analytics consulting practice focused on long-term system reliability.
I work with teams that already have data and dashboards, but struggle with platforms that become fragile, slow, or hard to reason about as they grow.
I build analytics systems with a pragmatic engineering mindset. The goal is not constant acceleration, but platforms that behave predictably under load, remain understandable to the people operating them, and do not require heroics to keep running. Automation-first delivery, governance, CI/CD, and semantic clarity are treated as architectural decisions, not optional layers added later.
Background
6 years of hands-on analytics work across retail, finance, and manufacturing. Most engagements involve Power BI semantic modeling, pipeline architecture, and platform governance at scale.
I have worked with datasets exceeding 1 billion rows, including import-mode models over 30 GB. I have redesigned semantic models serving 20+ downstream reports, managed portfolios spanning 100+ datasets and 250+ reports, and built CI/CD pipelines that handle ~30 automated deployments per month. Industries ranged from multinational retail chains to financial services and industrial manufacturing.
Before consulting independently, I worked in enterprise analytics teams where I saw firsthand how platforms degrade when operational discipline is treated as someone else's problem.
What sets this apart
I am comfortable building the CI/CD pipelines, API integrations, and automation tooling that most analytics consultants avoid. The parts of the stack that nobody else wants to own are often the parts that determine whether a platform stays reliable over time.
I work across the full delivery chain. From upstream data extraction through semantic modeling to deployment automation. This means fewer handoffs, fewer assumptions, and fewer gaps between what was designed and what actually runs in production.
Detail-oriented by default. Performance and ownership are non-negotiable. Semantic models are designed with clear responsibility, dashboards are never optimized in isolation from the platform beneath them, and operational concerns are addressed early, not postponed until something breaks.