Dataiku brings together everything a data team needs — from raw data preparation to advanced machine learning — all in one collaborative environment. At i-spark, we use Dataiku to help teams move faster, experiment smarter, and turn ideas into working AI solutions that scale.
Our role goes beyond implementation. We structure Dataiku environments that fit your existing data stack, automate repetitive processes, and give both analysts and engineers the freedom to focus on insights instead of manual work.
From Experiment to Impact
AI projects often get stuck between proof of concept and production. With Dataiku, we help bridge that gap. Our team sets up reproducible pipelines, reliable connections to your data sources, and governance practices that make your models robust and ready for real-world use.
Whether you’re working on churn prediction, marketing optimisation, or anomaly detection, we ensure your workflows are efficient, traceable, and built to deliver measurable business outcomes.
Collaboration That Scales
Dataiku shines when teams collaborate — and that’s exactly how we use it. We create shared spaces where data scientists, engineers, and business users can explore, build, and evaluate models together.
By designing clear project structures and automating version control, we help teams avoid silos and focus on driving value. The result: AI projects that are transparent, repeatable, and easier to maintain over time.
Designed for Your Ecosystem
Every organisation’s data landscape is unique. That’s why we configure Dataiku to integrate seamlessly with tools you already use — from Snowflake and Redshift to Databricks, dbt, or Looker.
We build automation and orchestration logic that connects everything smoothly, ensuring data flows predictably and performance stays consistent.
Work With i-spark
At i-spark, we believe AI should be understandable, not mysterious. With Dataiku, we help teams make advanced analytics part of their daily workflow — without adding layers of complexity.