# Unwind Data — Full Context > Expert Data & AI consulting for scale-ups and enterprises across Europe. We help ambitious teams unlock value from their data infrastructure. --- ## Company Overview Unwind Data is a specialist Data & AI consultancy founded by Wesley Nitikromo, based in Amsterdam, The Netherlands. With over a decade of experience helping scale-ups and enterprises worldwide, Unwind Data provides senior expertise in data architecture, semantic layers, AI readiness, and governance — without the overhead of traditional consulting firms. ### Core Value Proposition - Improve return on data assets with modern Data & AI experts - Get data teams out of maintenance mode and make Data & AI capabilities a revenue driver - Direct access to senior expertise without big consultancy overhead - Vendor-neutral, tool-agnostic guidance ### Key Statistics - 50+ happy clients served - 95% of data teams haven't started on semantic layer (massive opportunity) - +300% LLM accuracy improvement with semantic layer grounding - 6:1 ratio — for every euro spent on AI, six should go into data infrastructure --- ## Services In Detail ### 01. AI Readiness Assessment (Entry Engagement) **URL:** https://unwinddata.com/services#ai-readiness-assessment **Tagline:** Understand exactly where you stand before you invest further. Most teams rush into AI tooling without knowing what their data can actually support. Our assessment maps your current data architecture, governance gaps, and semantic coverage — and delivers a concrete roadmap for what needs to happen before AI can be trusted in production. **Deliverables:** - Full audit of existing data models, metrics definitions, and tooling - Gap analysis: where hallucinations and inconsistencies will emerge - Prioritised roadmap with effort and impact estimates - Executive summary ready to align stakeholders **Best for:** Teams evaluating AI investments or struggling with unreliable AI outputs. ### 02. Semantic Layer Design & Implementation (Core Engagement) **URL:** https://unwinddata.com/services#semantic-layer **Tagline:** The infrastructure that makes AI outputs trustworthy. A well-designed semantic layer is the single highest-leverage investment a data team can make right now. It creates a shared business vocabulary — metrics, dimensions, hierarchies — that both humans and LLMs can rely on. We design, implement, and validate semantic layers that turn your raw warehouse into a reliable source of truth. **Deliverables:** - Semantic layer architecture designed for your specific stack (dbt Semantic Layer, Cube, LookML, Omni, or custom) - Metrics catalogue with certified, governed definitions - LLM grounding layer so AI tools query meaning, not just syntax - Documentation and knowledge transfer to your team **Best for:** Data teams preparing for AI-powered analytics or consolidating fragmented metric definitions. ### 03. Tool-Agnostic Data Strategy (Advisory) **URL:** https://unwinddata.com/services#advisory **Tagline:** Vendor-neutral guidance in a market full of vendor-biased advice. The modern data tooling market is noisy and moving fast. Most advice you receive is shaped by vendor incentives. We don't sell software — we help you make the right architectural decisions for your specific team, stack, and growth stage. From tool selection to build-vs-buy decisions to migration planning. **Deliverables:** - Independent evaluation of BI, semantic layer, and warehouse options - Architecture review and recommendations - Migration planning and risk assessment - Ongoing strategic advisory via embedded expert or retainer **Best for:** CTOs, Head of Data, and analytics leaders making major platform decisions. ### 04. Training & Team Enablement **URL:** https://unwinddata.com/services#training **Tagline:** Close the skills gap before it becomes a competitive gap. 95% of data teams haven't started on semantic layer or AI-ready data architecture. The bottleneck isn't budget — it's knowledge. We run bespoke training programmes for data engineers, analytics engineers, and business analysts covering modern data modelling, semantic layer fundamentals, and working with AI tools responsibly. **Deliverables:** - Custom curriculum built around your stack and team level - Hands-on workshops — not slide decks - Practical exercises using your actual data and tooling - Post-training support and Q&A access **Best for:** Data teams upskilling for the AI era. Particularly strong for dbt, LookML, and semantic layer tooling. ### 05. Managed Semantic Services (Ongoing Partnership) **URL:** https://unwinddata.com/services#managed-services **Tagline:** Keep your semantic layer accurate as your business evolves. Semantic layers aren't a one-time project. Metrics change, new products launch, business rules shift. Without active maintenance, your semantic layer decays — and with it, the reliability of every AI and analytics output that depends on it. We offer ongoing management of your semantic layer as a retainer service. **Deliverables:** - Dedicated expert with context on your business and data model - Continuous metrics governance and certification - New metric and dimension implementation as requirements emerge - Monthly health reports and semantic layer audit **Best for:** Teams that have built a semantic layer and need to keep it accurate and growing. --- ## Specialised Offerings ### MCP-Driven Data Consulting **URL:** https://unwinddata.com/mcp-driven-data-consulting Model Context Protocol (MCP) is an open standard allowing AI assistants like Claude to securely connect to databases, warehouses, and BI tools in real time. We design, implement, and govern MCP servers that turn your data infrastructure into a live context source for AI reasoning. **What we deliver:** - AI-powered infrastructure assessment with ROI projections - Seamless integrations leveraging dbt MCP Server and Omni MCP - Enterprise-grade solutions with access controls, audit trails, and data contracts - AI tool integration for Claude, Cursor, and MCP-compatible tools **Methodology:** Intelligent Discovery (3-5 days) → Accelerated Implementation (1-2 weeks) → Intelligent Optimisation (Ongoing) ### Omni Migration Services **URL:** https://unwinddata.com/migrate-to-omni Seamless migration from legacy BI (Looker, Tableau, Metabase) to Omni. Zero disruption, full knowledge transfer. - Typical timeline: 4-7 weeks - Native dbt two-way sync - 50+ migrations delivered - Financial, technical, and organisational benefits **Methodology:** Discovery & Assessment (1-2 weeks) → Connect & Implement (2-4 weeks) → Training & Enablement (1-2 weeks) → Optimisation & Support (Ongoing) ### The Semantic Layer **URL:** https://unwinddata.com/semantic-layer A semantic layer translates raw warehouse tables into business concepts — metrics, dimensions, hierarchies — that every tool and every AI agent can rely on. One definition, everywhere. AI that queries meaning, not syntax. Governance without gatekeeping. Interoperability by design. --- ## Engagement Process 1. **Discovery Call** — 30 minutes to understand your situation, stack, and goals. No sales deck. 2. **Tailored Proposal** — Engagement scoped specifically to your team. Clear statement of work within the week. 3. **Kick-off & Delivery** — We embed in your workflow (Slack, async, or on-site). Clear milestones, no surprises. 4. **Knowledge Transfer** — Every engagement ends with your team fully equipped to own and extend what we've built. --- ## Technology Expertise - **Semantic Layer Tools:** dbt Semantic Layer, Cube, LookML, Omni - **BI Platforms:** Omni, Looker, Tableau, Metabase, Power BI - **Data Warehouses:** Snowflake, BigQuery, Databricks, Redshift - **AI & MCP:** Model Context Protocol, Claude, Cursor, LLM grounding - **Data Engineering:** dbt, git-based workflows, data modelling - **Governance:** Metrics certification, data contracts, audit trails --- ## Recent Blog Posts ### The Open Data Stack: Parquet, Iceberg, Polaris, Ossie - URL: https://unwinddata.com/open-data-stack - Published: 2026-07-14T07:14:08.249+00:00 - Category: Data Foundation - Excerpt: Apache Parquet, Iceberg, Polaris, and Ossie now cover every layer of the data stack with open, vendor-neutral standards. Here is what each layer does, how they compose, and what it means for AI-ready data architecture. ### Apache Ossie: The Rename Is Not the Story - URL: https://unwinddata.com/apache-ossie - Published: 2026-07-14T05:02:36.424+00:00 - Category: Semantic Layer - Excerpt: OSI is now Apache Ossie (Incubating). The rename is cosmetic. The governance transfer to the Apache Software Foundation is the story — and what it signals for the semantic layer as infrastructure. ### Semantic Layer Consulting & Data Architecture in Amsterdam - URL: https://unwinddata.com/semantic-layer-consulting - Published: 2026-07-14T04:58:15.442+00:00 - Category: Semantic Layer - Excerpt: Unwind Data is an Amsterdam-based data consultancy specialising in semantic layer implementation and data architecture for scale-ups and enterprises building AI. Independent, vendor-neutral, and practitioner-led. ### AtScale vs dbt Semantic Layer: Enterprise vs Engineering-First - URL: https://unwinddata.com/atscale-vs-dbt-semantic-layer - Published: 2026-06-25T20:54:54.217+00:00 - Category: Semantic Layer - Excerpt: AtScale and dbt Semantic Layer both promise a single source of truth for metrics. But they represent two completely different architectural philosophies and serve two different organizational realities. Here is the head-to-head comparison that vendor demos will not give you. ### Snowflake Cortex Sense, CoCo and CoWork Explained - URL: https://unwinddata.com/snowflake-cortex-sense-coco-cowork - Published: 2026-06-08T23:39:56.568+00:00 - Category: AI Agents - Excerpt: Snowflake shipped Cortex Sense, CoCo Desktop, and CoWork at Summit 26. Cortex Sense is the context runtime that sits between the model and the data. Here is what each product does and why the three form a coherent agentic stack. ### Snowflake Horizon Context: What It Does to the OSI - URL: https://unwinddata.com/snowflake-horizon-context-osi - Published: 2026-06-02T21:39:52.65+00:00 - Category: Semantic Layer - Excerpt: Snowflake announced Horizon Context at Summit 26: a unified active context layer sitting on Horizon Catalog, serving AI agents, BI tools, and the Cortex stack from one place. Here is what it actually is, and what it does to the OSI question. ### Gartner Semantic Layer Warning: AI Agents Will Fail Without Context - URL: https://unwinddata.com/gartner-semantic-layer-agentic-ai - Published: 2026-05-12T07:16:00+00:00 - Category: Semantic Layer - Excerpt: Gartner formally warned that skipping semantic foundations will cause AI agents to hallucinate, waste budget, and create governance risk. Practitioners already knew this. Here's what the context layer is and what building it actually requires. ### How to Connect Your Semantic Layer to AI Agents: Architecture Guide - URL: https://unwinddata.com/semantic-layer-for-ai-agents - Published: 2026-05-11T16:57:29.396+00:00 - Category: Semantic Layer - Excerpt: AI agents connected directly to the warehouse break in production. Here is the vendor-neutral architecture guide for connecting your semantic layer to AI agents using MCP, OSI, and A2A. ### Looker Alternatives: The Architecture Decision Nobody Talks About - URL: https://unwinddata.com/looker-alternatives - Published: 2026-05-08T07:09:59.852+00:00 - Category: Semantic Layer - Excerpt: Evaluating Looker alternatives? The real decision is not which tool has better dashboards — it is what happens to your semantic governance layer when you switch. A vendor-neutral framework covering Omni, Lightdash, Sigma, Power BI, Metabase, Cube, and when NOT to leave Looker. ### The dbt Fivetran Merger: What It Means for Your Data Stack - URL: https://unwinddata.com/dbt-fivetran-merger - Published: 2026-05-02T12:01:47.049+00:00 - Category: Data Foundation - Excerpt: 80-90% of Fivetran customers already used dbt. The merger formalized what most data stacks were already doing — but the implications for open source, the Iceberg bet, and the semantic layer are worth thinking through carefully. ### Semantic Layer vs Text to SQL: The Architecture Decision - URL: https://unwinddata.com/semantic-layer-vs-text-to-sql - Published: 2026-05-02T12:01:43.751+00:00 - Category: Semantic Layer - Excerpt: Text-to-SQL accuracy nearly doubled between 2023 and 2026. The semantic layer still wins on determinism. But the real question isn't which benchmark wins — it's an architecture decision about where your business logic lives. ### Snowflake Semantic View Autopilot: The Complete Practitioner Guide - URL: https://unwinddata.com/snowflake-semantic-view-autopilot-guide - Published: 2026-04-27T20:50:06.901+00:00 - Category: Semantic Layer - Excerpt: How to get Snowflake Semantic View Autopilot working in production, not just in a demo. The decisions that matter, the limitations nobody mentions, and where SVA fits in your data architecture. ### Omni's $120M Series C Puts the Semantic Layer at the Center of AI Analytics - URL: https://unwinddata.com/omni-series-c - Published: 2026-04-23T13:16:03.164+00:00 - Category: Semantic Layer - Excerpt: Omni raised $120M at a $1.5B valuation today — with the semantic layer as the explicit center of their pitch and their moat. Here is why the framing matters as much as the number. ### Google's Agentic BI Era With Looker: Why I Think They're Making the Right Bet - URL: https://unwinddata.com/looker-agentic-bi - Published: 2026-04-23T07:30:20.483+00:00 - Category: AI Agents - Excerpt: Google announced the agentic BI era with Looker at Next '26: BI agents, a native MCP server, Gemini-powered LookML, and the Knowledge Catalog. Here is why I think this is the right move — and the one thing that still determines whether it works. ### Snowflake Semantic Views: The Practitioner's Guide to Setup, Autopilot, and Best Practices - URL: https://unwinddata.com/snowflake-semantic-views - Published: 2026-04-21T13:32:03.991+00:00 - Category: Semantic Layer - Excerpt: Snowflake Semantic Views are now the native semantic layer inside Snowflake, powering Cortex Analyst, AI agents, and BI tools from a single governed definition. Here is how to implement them correctly — including Autopilot, dbt integration, and the best practices that matter in production. ### Semantic Layer for Multiple BI Tools: The Architecture That Ends Metric Drift - URL: https://unwinddata.com/semantic-layer-for-multiple-bi-tools - Published: 2026-04-18T08:53:05.792+00:00 - Category: Semantic Layer - Excerpt: When you run Tableau, Power BI, and Sigma simultaneously, every metric gets defined three times — and diverges. A semantic layer for multiple BI tools is the only architecture that fixes this without replacing any of them. ### BI Migration Approach: What Actually Works and What Breaks - URL: https://unwinddata.com/bi-migration-approach - Published: 2026-04-18T08:51:07.668+00:00 - Category: Data Strategy - Excerpt: Most BI migrations fail because teams migrate dashboards instead of fixing the logic underneath them. Here is a honest account of what works, what breaks, and why the semantic layer is where every migration should start. ### Sigma vs Looker: The Semantic Layer Is the Real Decision - URL: https://unwinddata.com/sigma-vs-looker - Published: 2026-04-18T08:47:15.045+00:00 - Category: Semantic Layer - Excerpt: Most Sigma vs Looker comparisons debate visualizations and pricing. The actual decision is about the semantic layer — whether you need one, and where it should live relative to your BI tool. ### Semantic Layer Consultant: What We Do and When You Need One - URL: https://unwinddata.com/semantic-layer-consultant - Published: 2026-04-17T20:47:21.646+00:00 - Category: Semantic Layer - Excerpt: What does a semantic layer consultant actually do? When does it make sense to hire one versus building internally? And what makes an independent consultant different from the vendors pitching you tools? Here is the honest answer. ### Data Foundation for AI: What to Build Before the Model - URL: https://unwinddata.com/data-foundation-for-ai - Published: 2026-04-17T20:45:42.31+00:00 - Category: Data Foundation - Excerpt: Most AI projects fail before the model is ever the bottleneck. The real problem is the data foundation underneath. Here is what it takes to build one that actually supports production AI. **Full blog:** https://unwinddata.com/blog --- ## Contact - **Website:** https://unwinddata.com - **Email:** hello@unwinddata.com - **Book a consultation:** https://unwinddata.com/contact - **Office:** Miraplein 24, Amsterdam 1033XJ, The Netherlands - **Twitter/X:** @unwinddata