Data warehousing & modelling
A warehouse that people can actually query. Clean dimensional models, tested transformations and documentation that stays in sync with the code.
Data analytics consultancy · Gent
From raw source to a decision you can trust.
I design and build the full data chain: the warehouse, the models, the dashboards and the project that ties them together. One person who understands every layer, so nothing gets lost between them.
Services
Every layer of the data stack, under one roof.
Bring me in for one piece, or for the whole chain. Either way you get someone who knows what happens upstream and downstream of the part you asked for.
Dashboards & self-service BI
Reports that answer the question the business is asking. I build in the tool you already own and set it up so your team can extend it without me.
Data governance & lineage
Know where every number comes from. Ownership, definitions and lineage from source table to dashboard tile, so a changed field never breaks a report unnoticed.
Project & backlog management
Data projects fail on scope more often than on code. I run the backlog, translate business needs into stories and keep delivery predictable.
AI & MCP
Put AI to work on your own data.
AI assistants are only as good as the data they can reach. With the Model Context Protocol (MCP), assistants such as Claude or Copilot can query your warehouse, read your dbt documentation and use your BI definitions, safely and with the right permissions.
I connect the two worlds: a solid data foundation and AI that can use it.
MCP servers for your data
I set up and build MCP servers that expose your warehouse, models and business definitions to AI assistants, with access control and audit in place.
AI on a governed foundation
Clear definitions and lineage are what make AI answers correct. I make sure the assistant uses the same "revenue" as your dashboards.
Practical AI in the data team
Generated documentation, SQL and dbt assistance, data quality checks and automated workflows that save your team real hours.
Advice and first steps
Not sure where AI fits? We start with one use case, test it on your own data and decide together what is worth scaling.
Toolkit
Tools I work with every week.
No preferred vendor. I pick the tool that fits your landscape and your team's skills.
Transformationdbt, SQL, incremental models, tests and docs
VisualisationQlik Sense, Power BI, Tableau
WarehouseAmazon Redshift, SQL Server, cloud data platforms
IntegrationERP and CRM replication, API and file ingestion
AIMCP servers, AI assistants, LLM-driven automation
DeliveryBacklog management, functional analysis, handovers
-- models/marts/consultant.sql select 'Jan' as consultant, 'data everything' as role, skill, years_hands_on from {{ ref('vitsam_skills') }} where skill in ( 'dbt', 'sql', 'qlik', 'power_bi', 'tableau', 'data_modelling', 'mcp', 'ai_integration', 'project_management' ) order by business_impact desc
Approach
How a project runs.
Understand
We start with the decisions you need to make, then trace back to the data that supports them.
Model
I design the data model and agree on definitions, so "revenue" means the same thing everywhere.
Build
Pipelines, dbt models and dashboards, delivered in short iterations you can review along the way.
Hand over
Documentation, lineage and training, so your team owns the result when I step back.
About
Hi, I'm Jan.
I'm a data analytics consultant based in Gent. I like to call myself a data everything guy: I've designed warehouse architectures, written the SQL, built the dashboards and led the teams that deliver them. Today that also means connecting AI to the data, so it gives answers you can rely on.
That range is the point. Most data problems sit between layers, where the model doesn't match the report or the backlog doesn't match the business. I work across all of them.
analytics architect→project lead→team lead
Contact
Got a data question that needs an answer?
Send a short note about your situation. I'll reply within two working days.