Do we have to migrate the warehouse to a new platform?

Not necessarily. Most of the pain comes from models, pipelines and ownership rather than from the platform. We measure where the time and the errors actually are, and a platform move happens only when the numbers argue for it.

Will reporting keep running while the work happens?

Yes. The existing reports keep running against the current models while the new ones are built beside them, and each report is cut over only once its numbers reconcile against the old path.

Which platforms do you work with?

Snowflake, Databricks, Azure Synapse and Data Factory, BigQuery, Redshift and Postgres, with Power BI, Qlik and Tableau above them. We have delivered on Azure and moved analytics workloads to AWS without breaking the daily reports.

What does the assessment cost?

The operational diagnostic is free and read-only. It returns where the reporting time goes, which models are duplicated, what is unowned, and a scoped plan with a fixed price for the work that follows.

Custom Software | Delivered in 6-10 Weeks

Modernize the warehouse without stopping the reports that run on it.

Old models, hand-built pipelines and a reporting layer nobody owns are why leadership waits days for a number and still gets two answers. We rebuild that layer around the sources you already run, in a scoped sprint rather than a replatforming program.

Request a data diagnostic See our data engineering work

6-10

weeks to the first reconciled model

2011

building data platforms since

40+

engineers

The Core Problem

The warehouse is not slow. It is unowned.

Reports disagree because the same measure is defined three times in three places. Loads fail quietly and are noticed when a number looks wrong. Nobody can say which model is authoritative, so every question routes to the one analyst who remembers.

Replatforming is sold as the answer, and it moves the same undefined measures onto a faster engine. The work that changes the outcome is defining the measures once, giving every model an owner, and making a failed load visible the moment it fails.

Before & After

What changes for the people who read the numbers

The shift is from a warehouse that is queried by specialists to one that leadership can rely on without asking anyone.

Today	After the sprint
Four systems give four answers to the same question	One set of numbers, reconciled against the sources they came from
A failed load is discovered when a report looks wrong	The load fails loudly, with an owner named and a runbook attached
The same measure is defined in the ERP, the BI tool and a spreadsheet	Defined once in the warehouse, consumed everywhere else
Month-end reporting is a week of manual assembly	Assembled by the pipeline, reviewed rather than rebuilt
Only one person knows how the model works	Documented models, tests on the critical measures, an owner per domain

Why 3ALICA

We work against your sources, not a green field

The warehouse stays online. New models are built beside the current ones, and a report moves across only once its numbers reconcile with the old path.

Take one example. A luxury eyewear brand ran on four systems that each held part of the picture: the online store, inventory, finance and marketing. Each gave a different answer to the same question, and month-end reports were assembled by hand from all four, so the number leadership saw depended on which system it came from. We built the warehouse layer on Azure Data Factory and Azure Data Warehouse over the NetSuite and Shopify data it already had, with Power BI on top. What the business got was not a faster report. It was a single set of numbers across sales, inventory, finance and marketing that leadership starts from, and a foundation solid enough that new questions become new reports rather than another rebuild.

The Process

Four steps, and you can stop after the first

The diagnostic is free and read-only. Everything after it is scoped and priced before work starts.

Week 1

Diagnostic

We read the warehouse, the pipelines and the reports as they are: where the time goes, which models duplicate each other, what has no owner, and which measures disagree.

Week 2

Model and plan

One agreed definition per measure, an owner per domain, and a written plan with the platform decision made on the numbers rather than on a vendor relationship.

Weeks 3-8

Build beside, then cut over

New models and pipelines are built alongside the current ones. Each report moves only when its numbers reconcile with the old path, so nothing goes dark.

Weeks 9-10

Hand over

Tests on the critical measures, alerting that names an owner, documentation your team can work from, and a walkthrough with the people who will run it.

Outcomes

What you own at the end

The deliverable is a warehouse your team runs without us, not a dependency.

One definition per measure

Margin, inventory and revenue mean the same thing in the ERP, the BI tool and the board pack.

Reporting that survives month-end

Assembled by the pipeline and reviewed by a person, instead of rebuilt by hand every cycle.

Failures that announce themselves

A broken load raises an alert with an owner and a runbook, rather than surfacing as a wrong number days later.

Get in touch

Start with one problem worth solving

Tell us the outcome you need and the systems involved. In 15 minutes we can say whether there is a useful first step, or why there is not. No pitch either way.

Email us directly

sales@3alica.com