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Intelligence & data

Numbers your team actually trusts.

Pipelines, a warehouse and dashboards where every metric has one definition — so meetings stop being about whose figure is right.

Discuss this project 5–9 weeks to a warehouse and first dashboards

The short version

The problem is rarely a shortage of data. It's that revenue means three different things depending on which dashboard you open, the nightly job failed on Tuesday and nobody noticed, and the one person who understands the reporting spreadsheet is on leave.

We build the boring layer that fixes it: reliable ingestion, tested transformations, metrics defined once in version control, and alerts when a pipeline breaks. Then dashboards on top that people actually open.

Typically built with

Python dbt Airflow PostgreSQL BigQuery Snowflake Metabase TimescaleDB

What's included

How we approach data analytics & engineering

Ingestion that doesn't fail silently

Scheduled and streaming pipelines with retries, backfills, and alerts when a source stops sending.

Metrics defined once

Business definitions live in version-controlled models, so every dashboard and export agrees on what a number means.

Tested transformations

Data quality tests run on every load — nulls, duplicates, referential breaks and volume anomalies caught before they reach a report.

Dashboards people open

Built around the decisions your team makes weekly, not a wall of every chart the tool can render.

What you get

Delivered at the end

  • Warehouse with modelled, documented tables
  • Ingestion pipelines with monitoring and alerting
  • Dashboards for the decisions you actually make
  • Data dictionary so definitions outlive the project

Right fit

This is for you if

  • 01 Teams where reporting is manual and monthly
  • 02 Companies with data in five systems and no single view
  • 03 Products that need usage analytics they can rely on

Not quite what you need? Tell us the outcome you're after — if a different service or a smaller piece of work would get you there faster, we'll say so.

Ask us instead

How we work

A clear path from idea to impact

  1. 01

    Discover

    We map your goals, users, and constraints into a sharp, prioritized scope.

  2. 02

    Design

    Architecture and interfaces are prototyped and validated before a line ships.

  3. 03

    Build

    Engineers deliver in tight sprints — you see working software every week.

  4. 04

    Scale

    We launch, monitor, and harden — then grow the system alongside your business.

Questions

What clients ask about data analytics & engineering

The things that come up most on the first call. Anything else, just ask — we answer straight.

Ask a question (205) 370-4351
  • Do we need a warehouse, or is a spreadsheet fine?

    If one person can maintain it and the numbers are never disputed, a spreadsheet is fine and we'll say so. The moment two teams disagree about the same metric, you've outgrown it.

  • Can you work with the BI tool we already pay for?

    Yes. Looker, Power BI, Metabase, Tableau — the modelling layer underneath is what matters, and it's portable if you switch tools later.

  • How do we know the numbers are right?

    Tests run on every load and fail loudly. We also reconcile against a source you already trust — usually finance — before anything is declared production.

Often paired with

All services

AI & Machine Learning

LLM features, computer vision, and predictive models wired into real production systems.

View service

Web App Development

Fast, secure, scalable web applications with modern frameworks and clean architecture.

View service

Custom Software Development

Tailored platforms engineered around your exact workflows — not off-the-shelf compromises.

View service

Next step

Let's scope data analytics & engineering

Thirty minutes with the engineer who'd lead it. You leave with a scope, a number, and an honest read on whether it's worth building.

Book a free call (205) 370-4351

Prefer email? support@zeetek.net