Agilytic

04/09/2026

PSA: just because Microsoft is investing in Fabric doesn't mean you 𝘩𝘢𝘷𝘦 to migrate right now.

For instance, if:
- PowerBI is enough for your use cases
- You're already on Databricks or Snowflake
- Someone else is pushing the migration...
you might want to hold your horses.

On the other hand, there are 5 cases in which a migration might be the right move.

Find out in our latest blog post:

Should you migrate from Power BI to Microsoft Fabric? An honest decision guide for Belgian leaders: when migration pays off, when it does not, and what it actually involves.

01/09/2026

September 1st is the real new year.
Try and change our minds.

January is for good intentions, but September is for action: a time to reset, start fresh and dive in with all that "back-to-it" energy.

For us at Agilytic, it means new client challenges, and of course new perspectives with our recent move to join Artefact.

Welcome back, everyone! Let's make it count 🫡

26/08/2026

A demolition and deconstruction company wanted to improve its prospecting by identifying commercial opportunities as early as possible.

They were already using AI, but through a broad, all-in-one prompt run manually across several tools.

We set out to:
- Deliver prompt engineering and technical workshops
- Build an automated market watch agent

Discover how we did it and what came out of it on our website: https://eu1.hubs.ly/H0xLmfW0

24/08/2026

You want conversational analytics?
In other words, you want to translate natural language questions into SQL queries against your data, then get a result in plain language or a visualization?
Great.

Now, which tool do you want to use?
Because Databricks, Snowflake AND Fabric have a conversational analytics product.

Fear not: we've asked our best data engineers to conduct a comprehensive benchmark of the three tools.

Here it is:

Databricks, Snowflake, and Microsoft Fabric each deliver conversational analytics. Which one suits your organization best?

19/08/2026

You can have data in Fabric... and still not be able to use it.

A raw data layer is only a starting point: without the curated layers on top, the data isn't structured for reporting, decision-making, or anything else that actually matters to the business.

In Fabric implementations, we often encounter this gap. The platform is in place, something was built during the initial phase, but the work needed to make it reliable and usable was never completed.

On a recent project, we took an incomplete CRM data pipeline (running across an ERP, an SSIS layer, a SQL Server warehouse, and Fabric) and built it out properly with a medallion architecture.

The full case study is on our website:

How we helped a company running its analytics on Microsoft Fabric to secure and mature its CRM data foundation

17/08/2026

𝗗𝗮𝘁𝗮 𝗷𝗼𝗯𝘀 | #2: 𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁

After the data engineer, here's the second entry in our data jobs series!

Data analysts transform raw numbers into insights that help teams make better decisions. They use SQL, BI tools, dashboards, KPIs... but also storytelling and stakeholder management.

Disclaimer: you don't always need a specific degree to get there! Career switchers from marketing, finance, or operations make it all the time. What matters is the ability to work hands-on with data and communicate what it means 😌

This article covers what the role actually involves, the skills it requires, and how to get started 👉

We're hiring data analysts in Belgium!

12/08/2026

In (too) many organizations, business users remain heavily dependent on data teams for simple and recurring questions.

Agilytic partnered with a leading self-storage provider to reduce this dependency by developing an analytics chatbot on Databricks.

Business users now have natural-language access to their data warehouse: decisions are faster, and the data team is free to focus on higher-value work!

Read the full story here:

How Agilytic developed an analytics chatbot on Databricks for a self-storage provider

10/08/2026

Fabric looks reasonably priced on paper. But its pricing model tends to catch people off guard.

To help you see clearly, our latest blog post is a full breakdown of the Fabric pricing model (with actual numbers):

- How the F-SKU model works
- What you need to know about capacity & tiers
- Why predictable does not mean cheap
- The sweet spot for Fabric pricing

Read it on our blog:

How much does Microsoft Fabric actually cost? How does the F-SKU model actually work?

06/08/2026

Last week was the first game to officially launch the integration between Agilytic and Artefact teams.

Good vibes (and legendary goals) were on the agenda 😎

03/08/2026

After 10 years, we're starting a new chapter 📖

Agilytic is joining Artefact, a global data and AI consultancy with 2,500+ people across 27 countries!

We know it will make us (even) better at the thing we've always cared about: helping Belgian organisations get real value from data and AI.

For our clients, the day-to-day doesn't change. Same team, same people, same approach.
What grows is the ceiling of what we can take on:
- Deeper expertise
- More specialized talent
- The ability to go further on ambitious projects without hitting the limits of a 30-person shop.

Julien wrote about why we made this choice, what changes, and what doesn't:

Agilytic is joining Artefact. Co-founder Julien Theys on why the move is deliberate: what changes for clients, what stays the same, and why the same team, proximity and problem-first approach to data and AI remain at the core.