Codnity Data · Managed data warehouse

Data Warehousing + AI

We build and run a data warehouse for your business. It pulls data from your tools every night, cleans and structures it with dbt on a PostgreSQL database, and serves it to Power BI and an AI assistant you can ask in plain language. You get one set of numbers everyone works from, without hiring a data engineer. Hosted in the EU, on one flat monthly subscription.

Flat monthly price, no per-query bill Power BI + AI assistant EU-hosted, refreshed daily

Book a demo →See how it works

Built by Codnity Data · trusted by growing companies

How it works

How your data gets from your tools to a report

Connectors read from your tools on a schedule. dbt cleans and structures the data through three layers, and Power BI and the AI assistant read the finished tables. We build and maintain every step.

Your data sources

CRM & Sales

Accounting

Project management

Web analytics

Spreadsheets & more

Pulled in nightly

Managed data warehouse · PostgreSQLCentralized & secure

RawYour data, exactly as it arrives

clean · standardize

StagingCleaned & standardized

structure · join · test

Marts · business-readyClean, structured tables ready to report on

Read by

How you use it

Power BIDashboards and reports, all reading the same tables.

AI Assistant (Claude)Ask a question in plain language, get a chart or a written answer.

Future appsThe same tables can feed new tools you add later.

⟳ refreshed automatically every day

Ingestion - pulled from your tools on a scheduledbt - cleans, structures and tests the dataOutputs - Power BI and AI read the finished tables

What it is

What a data warehouse is, and what “as a service” means

A data warehouse is a single database that collects data from all your business tools, cleans it, and stores it in a structure built for reporting and analysis rather than for running an app. “As a service” means you do not build or run it yourself: we set it up, connect your sources, model the data, and maintain it for a monthly fee, and you read the results in Power BI or by asking the AI assistant.

It is the clean, modeled layer that Power BI and the AI assistant read from. The difference from a plain database is that the data is already joined, tested and business-ready, and we build and run the whole thing for you.

The problem with scattered data

When your data lives in ten tools, the numbers never quite match

Most companies keep their data in separate tools: a CRM, an accounting package, a project tool, web analytics, and a pile of spreadsheets. Each one holds part of the picture, and none of them agree. Pulling it together by hand is where the time goes, and where the errors creep in.

📤

Reports are built by hand

To make one report, someone exports a file from each tool and pastes it together in a spreadsheet. It takes hours and has to be redone next month.

⚠️

The numbers disagree

Sales, finance and operations each define revenue or a customer differently, so the totals from two tools rarely match, and no one is sure which is right.

🕒

Month-end takes days

Because the data is gathered manually, closing the books and producing the monthly numbers is slow, and the figures are already out of date by the time they land.

📉

There is no history

Spreadsheets get overwritten, so comparing this quarter to last, or spotting a trend, means digging through old files, if they still exist.

🔗

Reports break quietly

A renamed column or an edited cell breaks a report, and often no one notices until a decision has already been made on the wrong figure.

What you get

What our Data Warehousing + AI service includes

Every setup is scoped to the tools you already use. These are the parts we build, connect and run for you.

🗄️

A managed PostgreSQL warehouse

A dedicated database for your business, hosted in the EU. It is yours alone, not a shared tool, and you can export everything in it at any time.

Dedicated PostgreSQL instance
EU-hosted and GDPR-compliant
Role-based access and an audit trail
You own the data and can export it
We start under NDA, read-only

🔄

Automated pipelines and dbt models

Connectors pull data from your tools on a schedule. dbt then cleans it, joins it and tests it through Raw, Staging and business-ready layers, the same way large data teams work.

Connectors for CRM, accounting, project tools, web analytics, spreadsheets
Refreshed every day (more often on higher tiers)
dbt: Raw to Staging to Marts
Automated tests catch bad data before a report does
Full history kept for trend analysis

📊

Power BI dashboards

Power BI connects straight to the finished tables, so reports open quickly and every report is built on the same figures. No Microsoft Fabric licence required.

Native PostgreSQL connection (Import or DirectQuery)
Dashboards that all read one set of tables
Drill down from a total to the underlying rows
Works with the Power BI you already use

🤖

AI analytics, powered by Claude

Type a question the way you would ask a colleague. The assistant answers from your warehouse, not from the model’s general knowledge, and shows the chart behind the answer.

Ask in plain language, no SQL
Get a chart, a table or a written summary
Answers drawn from your governed data
No waiting on an analyst to run it

🛠️

Setup, monitoring and support

We design the data model, connect your sources and keep the whole thing running: nightly refreshes, monitoring, and changes as your tools and questions change.

Done-for-you setup, usually live in a few weeks
Refreshes monitored daily
New sources and model changes handled for you
A foundation ready for tools you add later

What changes for your team

What a managed warehouse changes, day to day

The point is not the database. It is what stops happening once your data is in one place, and what your team can do instead.

Everyone uses the same number

Because every report and the AI read from one modeled set of tables, finance, sales and operations stop arguing about whose figure is correct.

Reports take minutes, not days

The data is already gathered and cleaned each night, so producing the monthly numbers or a one-off analysis is a matter of opening a dashboard or asking a question.

You do not hire a data team

Building and running a warehouse normally needs a data engineer and an analyst. We do that work, so the cost is a monthly fee instead of two salaries.

The bill is the same every month

The price covers the warehouse, the daily refreshes and the maintenance. It does not go up because you ran more reports, the way pay-per-query platforms do.

It grows without a rebuild

When you add a tool or a new question, we extend the same warehouse. The dashboards and AI keep working; nothing has to be started over.

Know the difference

Data warehouse vs database vs data lake vs data mart

These four terms get used interchangeably, but they do different jobs. Here is the short version. Most companies reporting across a few tools need a warehouse.

	Data warehouse	Database	Data lake	Data mart
Purpose	Reporting and analysis (OLAP)	Running an app day to day (OLTP)	Storing raw data to explore later	One team's slice of the warehouse
Data	Cleaned, structured, with history	Live, current records	Raw, any format	A cleaned subset
Who uses it	The whole business, for reporting	The application and its users	Data scientists and engineers	A single department
Best when	You report across several tools	You need fast reads and writes	You keep raw data for ML	One team needs its own view

A spreadsheet is none of these. It has no automated pipelines, no shared source and no query engine, which is why it stops working once several tools and people are involved.

Use cases

What teams use it for

Finance and leadership

A P&L and cash-flow view that updates every day
Consolidation across entities and currencies
Board and investor numbers that reconcile

Retail and e-commerce

Sales and stock in a single view
Marketing spend against revenue by channel
Demand and inventory forecasting

Operations and SaaS

Churn and retention from product and billing data
Utilisation and delivery against plan
Pipeline and revenue in one place

Who builds it

Built and run by Codnity Data

Codnity Data is a Baltic, EU-based data team. We build financial and operational reporting on Power BI, dbt and PostgreSQL, and we run your warehouse with the same stack and the same rigor we bring to that work.

EU-hosted and GDPR-compliant. Your data stays in the EU and stays yours.
NDA first, read-only to start. We sign a mutual NDA and begin with read-only access to your sources.
You can leave with your data. Export it any time; there is no lock-in.
One monthly fee. Warehouse, refreshes and maintenance are all in it.

Elvijs Veide

Founder, Codnity Data

Scopes and oversees every warehouse we build, personally.

Book a demo

See it running on your own data

Send us the tools your numbers live in. We will show you what one warehouse would pull together, what you could ask the AI, and what the setup would involve, before you commit to anything.

A look at your current tools and data
What a single source of truth would cover
A walkthrough of Power BI and the AI assistant
A clear, flat-price scope

FAQ

Questions about data warehousing, dbt, PostgreSQL and the AI

Straight answers on what it is, how it works, and how the service is run.

What is data warehousing?

Data warehousing is the practice of collecting data from all your tools into one central, structured store, cleaned and optimized for analysis and reporting rather than day-to-day transactions. It gives everyone one trusted, always-current set of numbers to report from, instead of scattered spreadsheets.

What is data warehouse as a service (DWaaS)?

Data warehouse as a service is an outsourcing model where a provider configures, builds and manages the data warehouse for you, and you provide the data and pay a subscription. You get a single source of truth connected to your BI and AI tools without provisioning servers, writing pipelines or hiring a data engineer.

How does the AI assistant work?

Because your warehouse is one clean, governed source, the AI assistant (powered by Claude) lets your team ask business questions in plain language and get charts, reports and answers back in seconds. Answers are grounded on your governed warehouse data rather than the model’s general knowledge, so there is no SQL and no waiting on analysts.

What is dbt and how is my data cleaned?

dbt (data build tool) is the industry-standard framework for transforming data inside a warehouse. It cleans, structures, joins and tests your data with version-controlled, documented logic, so your models are reliable and repeatable. In your warehouse, dbt turns Raw data into Staging, then into business-ready Marts.

What database and tooling do you use?

Your warehouse runs on PostgreSQL, and data is cleaned, structured and tested with dbt, the industry-standard transformation tool. Data moves through Raw, Staging and business-ready Marts layers, and refreshes automatically every day.

How often does my data refresh?

Automatically every day as standard, with more frequent or near-real-time refresh available on higher tiers. Your data flows in from your sources, is transformed with dbt, and is ready in Power BI and the AI assistant without any manual exports.

How long does setup take?

Most warehouses go live in weeks, not months. We connect your sources, build the dbt models and dashboards for you, and start with a data audit under a mutual NDA. Timelines depend on how many sources you have and how complex your reporting is, which we scope up front.

Is Excel a data warehouse?

No. Excel is a spreadsheet, not a data warehouse. It has no automated data pipelines, no single source of truth and no query engine, so it breaks down once several tools and people are involved and edits start overwriting each other.

What is the difference between a data warehouse and a data lake?

A data warehouse stores cleaned, structured data that is ready for reporting and dashboards (schema-on-write). A data lake stores vast amounts of raw, unstructured data for data scientists to explore later (schema-on-read). Most growing teams need a warehouse, not a lake.

Can Power BI connect to the warehouse?

Yes. Power BI connects natively to the PostgreSQL warehouse and reads clean, pre-modeled data, so reports load faster, agree with each other and stop breaking. You can use Import mode for speed or DirectQuery for live data, without buying Microsoft Fabric.

Do I need a data team to run it?

No. That is the point of the service. We design, build and maintain the warehouse, pipelines, dbt models and refreshes for you, and keep it monitored and running, so you get the reporting backbone of a much bigger company without the headcount.

How much does it cost?

A predictable flat monthly subscription covers the warehouse, the daily refreshes, the connectors and the ongoing maintenance, so your reporting just works. There is no per-query metering and no surprise cloud bill on top, unlike consumption-priced platforms such as Snowflake or BigQuery, where a busy month costs more than a quiet one. Pricing is scoped to how many data sources you have - book a demo and we will quote it.

Is my data secure and GDPR-compliant?

Yes. Your warehouse is a dedicated, secure, EU-hosted PostgreSQL instance, GDPR-compliant, with role-based access and an audit trail. We start under a mutual NDA with read-only access, and you own your data and can export it at any time.