Symake helps you build a modern data lakehouse on Databricks — from reliable pipelines and clean, governed data to analytics and machine learning — so your teams stop wrestling with data and start making decisions with it.
We bring every source — apps, databases, files, and live streams — onto a single governed lakehouse, then keep it clean, reliable, and ready for analytics and AI. No more scattered copies, no more arguing over which number is right — just one trusted foundation your whole business runs on.
Databricks is a big platform, and getting real value from it takes more than switching it on. Symake covers the full journey — from architecture and pipelines to analytics, machine learning, and the governance that keeps it all trustworthy — so your raw data turns into decisions your business can act on with confidence.
We design and stand up a modern lakehouse on Databricks, shaped around your data, your teams, and the way your business actually makes decisions — so the foundation is right from day one.
We build reliable ingestion and transformation pipelines that move, clean, and shape data at any scale — automated, monitored, and resilient, so your data keeps flowing without constant firefighting.
With Delta Lake at the core, your data becomes clean, versioned, and dependable. Every change is tracked and auditable, so teams always know exactly what they are working with and can trust it.
Beyond nightly batches, we build streaming pipelines that bring data in as it happens — so dashboards, alerts, and models reflect what is going on in your business right now, not yesterday.
We help you build, train, and deploy machine-learning models on Databricks and keep them running in production — with the tracking, retraining, and monitoring that turn experiments into lasting value.
We turn your governed lakehouse into dashboards, reports, and live insights your teams can rely on — connected to the tools they already use, powered by data everyone agrees is correct.
With Unity Catalog we put clear lineage, fine-grained access, and auditability in place — so the right people see the right data, sensitive information stays protected, and compliance is never an afterthought.
We move you from legacy warehouses and tangled data lakes onto Databricks smoothly — migrating pipelines, data, and reports with minimal disruption so your teams keep working throughout the transition.
We tune compute, storage, and queries so your platform stays fast and your cloud bill stays predictable — getting the most out of every cluster instead of paying for wasted capacity.
Most data problems aren't about tools — they're about trust. We build a single, governed lakehouse so your whole business works from data it can rely on.
Engineering, analytics, and machine learning all draw from the same clean, governed data — so reports finally match and no one argues over which number is right.
Clear lineage and fine-grained access control with Unity Catalog mean the right people see the right data — and every action stays fully auditable.
Reliable pipelines on Delta Lake keep data trustworthy, so dashboards, reports, and AI models run on a foundation that scales as your teams grow.
A clear path from scattered data to a governed lakehouse your whole business can trust — five focused stages, each building on the last.
We review your data, goals, and stack, then design the right lakehouse architecture.
We build reliable ingestion and ETL pipelines on Delta Lake.
We build analytics and machine-learning models on your governed data.
We ship to production with security, access, and governance in place.
We tune performance, manage costs, and support you as you scale.
Tell us what you want your data to do, and we'll build the Databricks foundation to make it happen.
A lakehouse combines the flexibility of a data lake with the reliability and performance of a data warehouse. On Databricks, it gives you one governed platform for engineering, analytics, and machine learning.
Yes. We migrate from legacy warehouses and data lakes to Databricks, moving your pipelines and data across with minimal disruption to your business.
Yes. We build, train, and deploy machine-learning models on Databricks, taking them from experiment all the way to production use.
We use Unity Catalog and best-practice controls for security, access, and governance, so the right people see the right data and every action is auditable.
Databricks runs on the major clouds, so we work with whichever platform you already use — and help you keep performance high and costs under control.
Absolutely. We can lead the build, work side by side with your engineers, or hand over a clean, documented platform your team runs itself. We also share best practices so your people grow more confident on Databricks along the way.
It depends on your data and goals, but many teams see a working lakehouse with real pipelines in a matter of weeks, not months. We start with a focused first use case that delivers value quickly, then expand from there.
Get in touch for a short discovery call. We'll review your data and goals, then propose a clear plan to build or improve your Databricks lakehouse.