Snowflake
Many organizations pay for data infrastructure they only partly use, wait on IT for every change, and often see AI analysis as reserved for data scientists with Python knowledge. Heavy analyses also slow down other users, further squeezing productivity. Snowflake solves this with a data platform that scales automatically, manages itself, and makes AI analysis accessible to anyone who knows SQL.
What is Snowflake?
Snowflake is a cloud-based data platform that fully decouples storage and compute. Teams get their own compute power and pay only for actual usage, down to the second. No cluster management, no manual tuning. You also don't need Python knowledge or external tooling: SQL is enough to get started independently.
The benefits of Snowflake
Automatic scaling
No unnecessary infrastructure costs, because your platform automatically scales up and down with demand.
Independent analysts
Analysts work independently, without depending on IT for every change or extension.
No mutual slowdown
Teams no longer slow each other down, even during peak load such as a month-end close.
AI without Python
You don't need Python knowledge or external tooling to work with AI on your data.
Components of Snowflake
Snowflake consists of a number of components that together create a platform that scales along with you, doesn't get in teams' way, and makes AI accessible.
Components of Snowflake
Snowflake consists of a number of components that together create a platform that scales along with you, doesn't get in teams' way, and makes AI accessible.
Snowflake fully separates storage and compute. Virtual warehouses (Snowflake's compute units) start within seconds, scale automatically under high load, and pause when idle. Costs are always tied to actual usage, never to reserved capacity sitting idle.
Multiple teams each run on their own virtual warehouse, without affecting each other. A heavy month-end close therefore doesn't slow down the daily queries of other teams.
Snowflake Cortex brings AI functions directly into SQL, from sentiment analysis to text summarization and classification. Business users ask questions of their own data in plain language, without a technical layer in between.
Our approach with Snowflake
A data platform only delivers value when it fits what's already in place. With more than 25 years of experience in data management, analytics, and application development, we start with an inventory of your current data environment and determine which workloads benefit most from a switch.
After that, we first build a Proof of Concept, to concretely demonstrate what Snowflake delivers for your situation before you invest further. Only then do we migrate step by step, set up access management from day one, and make sure your team can continue independently. Costs remain transparent and predictable throughout. We implement Snowflake GDPR-proof and hosted in Europe, and are certified to ISO 27001, ISO 9001, and NEN 4400-1.
Our success stories
Get started with Snowflake
FAQ
What makes Snowflake different from a traditional data platform?
Snowflake fully decouples storage and compute. As a result, you only pay for the compute power you actually use, down to the second, and your platform scales automatically without you having to manage or tune clusters yourself.
Do we need technical knowledge to work with Snowflake?
No, not necessarily. SQL is enough to analyze independently and work with AI functions via Snowflake Cortex. You don't need Python knowledge or external tooling, so analysts without a data science background can get started right away too.
Do heavy analyses, such as a month-end close, slow down other teams?
No. Thanks to the multi-cluster architecture, each team runs on its own virtual warehouse. A heavy load on one team's side has no effect on the speed of another team's queries.