Databricks & Data Platform Services
Sales numbers live in one system and customer records in another. Billing has its own exports, support has its own dashboard, and spreadsheets fill the gaps between them. Once a month someone pulls it all together by hand. The report takes days, the dashboards go stale between refreshes, and when two numbers disagree, nobody's quite sure which one to trust.
What we build
Databricks workspace setup
We stand up your Databricks workspace and configure it for your team: user accounts and permissions, a working area for development, and a separate area for production jobs, so an experiment can never overwrite the tables your reports depend on. We document the setup as we go. You get a workspace your people can sign in to on day one, with notes an engineer who joins later can actually follow.
Data source integration
We connect the systems your data already lives in. Typical sources are the application database behind your product, billing and payment exports, marketing and support tools, and the spreadsheets that cover everything else. Each source lands in the workspace on a schedule, with no one exporting CSVs by hand. The integrations are code, so when a source changes shape, we update it, test it, and redeploy it like any other software change.
Data modeling
Raw tables are shaped for the software that produced them: cryptic column names, one business concept spread across six tables, and a "revenue" figure that changes meaning depending on which system you ask. We model the raw data into clean tables that match the way your business talks: customers, orders, revenue. Each concept gets one table and one definition, so anyone writing a report finds the number in one place and it means the same thing everywhere.
Incremental refresh pipelines
We build pipelines that refresh your data on a schedule and process only the records that are new or changed since the last run. That matters because full reloads get slower and more expensive as your data grows, while incremental refresh keeps runs short and compute costs steady. Your dashboard is already current when you open it in the morning, and it stays current as the volume behind it grows.
Reporting
The platform exists to answer questions, so this is where the work pays off. We build reports on the modeled tables, which means every chart and every export draws from the same definitions. The monthly report your team assembles by hand becomes a page that's always up to date, and when leadership asks a new question, the answer is usually a small change to an existing model instead of another week of spreadsheet work.
Who this is for
Companies standing up their first real data platform. You run a product and a handful of tools, each one holds part of the picture, and reporting works today because one person carries it. Usually something specific brings people to us: a board meeting where two decks showed different revenue numbers, a new tool that broke the monthly export, or an analyst who left with the spreadsheet logic in their head.
You want the sources connected, the numbers agreed on, and the refresh automatic, and you want that without having to hire a data team of your own first. We build the platform and we run it. If Amazon is one of your sales channels, that side of the work has its own page: analytics engineering for Amazon-channel businesses.
How we work
We're a software engineering team, and we treat data work like production software. Pipelines and models live in version control, changes go through code review, and everything ships with tests. AI writes the code at Ecliptic Ideas today, with senior engineers directing and reviewing every change, and data engagements run through exactly that process. When a pipeline fails, we hear about it from the monitoring we set up, read the code, and fix the cause.
After go-live we stay on. We watch the pipelines, fix what breaks, and connect new sources as your business adds tools, the same way we look after the long-lived products we operate. Our existing products page describes that retained approach.
Next step
Book an intro call, or tell us about your data through the contact page. Bring the one report your team assembles by hand, and we'll walk through where its data lives today and what it would take to make it refresh itself.
