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MDI · Modern Data Stack

Modern Data Stack

The modern data stack conversation in most organisations starts with "we need Snowflake." It shouldn't. It should start with "what problem are we actually trying to solve and what does our current stack prevent us from doing?"

What we hear from operators

The problems we solve

01

The tool was bought before the architecture was designed

Snowflake or Databricks licences are purchased — often after a vendor demo or a board directive — before the data engineering team has designed the ingestion layer, the transformation model, or the semantic layer on top. The tool sits mostly idle, being used as an expensive substitute for what a well-configured cloud data warehouse already does. The gap between the licence cost and the business value is wide and growing.

02

Transformation logic lives in stored procedures nobody understands

Most organisations that have been running SQL-based analytics for more than three years have transformation logic buried in stored procedures, views, and scheduled jobs that predate the current team. Nobody fully understands them. Changes break things upstream. Testing doesn't exist. Introducing dBT isn't just a tooling decision — it's a process change that brings version control, testing, and documentation to transformation code.

03

Ingestion is bespoke, brittle, and constantly breaking

Custom-built ELT pipelines for every source system — each one slightly different, each one owned by the person who built it, each one breaking when the source system changes. Fivetran and Airbyte exist to solve this: managed connectors for 300+ sources, schema change handling built in, monitoring included. The decision to build vs buy these connectors is usually obvious in retrospect.

By market

Modern Data Stack — market-specific pages

Each page below covers what modern data stack looks like specifically in that market — the local ERP landscape, compliance context, and the operational patterns we actually see there.

Technology stack

SnowflakeDatabricksdBT (dbt Core / dbt Cloud)SQLMeshFivetranAirbyteApache SparkDelta LakePower BILookerMicrosoft Fabric

Start with a conversation, not a proposal

First call is 45 minutes. No deck. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like.