Discover how Smile and Dremio modernize your Data Platforms thanks to the Open Lakehouse architecture. Unify your silos and accelerate your AI projects right now.
Facing the explosion of AI, mastering data assets has become the #1 challenge for CIOs. At Smile, we have selected Dremio as a strategic partner for its ability to unify silos via a high-performance Open Lakehouse architecture.
Why is data the pillar of your AI strategy?
Only a few years ago, talking about corporate data management often felt like talking to a brick wall. Today, the narrative has changed. Business departments understand the stakes, budgets exist, and projects are frequently launched driven by AI use cases. Except that on the ground, reality often remains disappointing.
Data scattered across dozens of silos. Teams spending more time searching for the right source than analyzing it. A Shadow IT/AI that has taken root because official tools were too slow, too rigid, or too opaque. And a reliability of reports that no one can truly guarantee, limiting trust and undermining governance.
We encounter these situations regularly with our clients, regardless of their size or sector. These are not isolated cases: it is the reality for most organizations that have accumulated systems without ever truly thinking about the global architecture, and whose data heritage has become sedimented.
What is needed to break through? A modern data platform, designed to unify without creating rigidity, to open up without losing control, and to govern and make data actionable as "Data Product" assets through "as-a-service" tools.
Smile's expertise: transforming a technical project into a business lever
At Smile, we rarely intervene just to install technology and leave. What interests us (and what really works) is building something that lasts, strengthening engagement and adoption by client teams. Concretely, this involves three levels of intervention:
- Strategy: Before opening a terminal or configuring anything, we take the time to understand the real stakes: who needs what, where is the data today, what are the priority use cases, and how are data teams organized and working together with business/IT units. This phase often makes the difference between a project that takes off and one that stalls.
- Implementation: We design robust and scalable Open Lakehouse architectures, intended to integrate into already crowded environments: Snowflake, dbt, Talend, Tableau, Power BI… The challenge is not to start from scratch, but to intelligently orchestrate what exists, capitalize on it, and unlock the potential of the data heritage.
- Support: A data platform, no matter how well-designed, only produces value if teams embrace it. We train, structure roles, and implement concrete practices (data governance / data quality "as code" and "by design"), using product-mode approaches to develop ownership. Because data culture cannot be decreed; it is built and maintained over time.
Dremio : the open architecture, without compromising on performance
It is with this logic that we chose to work with Dremio. And honestly, what convinced us wasn't the marketing promise, but what we saw working in the field while implementing the Open Lakehouse standard based on Apache Iceberg and Arrow open formats, eliminating vendor lock-in.
Dremio is a platform that truly embodies the principle of the Open Lakehouse: querying data where it resides, without duplicating or moving it, with a high-performance SQL engine that holds up even on large volumes.
What concretely changes the game:
- Open source logic first. No lock-in, no dependency on a closed vendor. The architecture integrates into the existing setup rather than replacing it and relies on Apache standards (Parquet, Arrow, Iceberg, Polaris).
- Data virtualization next. This is one of Dremio's strengths via the reflection mechanism: allowing teams to access cross-referenced data from heterogeneous sources without going through costly and fragile copy pipelines.
- Fine-grained access control and traceability. Who is accessing what, since when, and with what permissions? These questions find clear answers in Dremio, which makes life much easier for both data teams and business departments in applying rigorous governance.
- Fast onboarding. This is perhaps the most underestimated detail: if a tool is too complex, teams avoid it. Dremio was designed to be usable by various profiles through an ecosystem of tools already in place (Data Governance, BI and Data Visualization, AI/ML, and AI Agents); it is more than a traditional data platform—it is an Agentic Lakehouse.
What this partnership changes for our clients
As a Dremio partner, our value-add is not limited to installation and configuration. We intervene across the entire spectrum: from architecture design to team upskilling, including integration into sometimes very heterogeneous ecosystems and the construction of data products and high-impact data/AI use cases.
What we build together is a modern data environment where business teams can access reliable data quickly, where technical teams maintain control over quality and security, and where the organization can evolve its infrastructure without tearing everything down at every change of course.
In conclusion
At Smile, we believe that data must be a catalyst for performance, not a brake. By partnering with Dremio, we provide our clients with a powerful, open platform perfectly aligned with today’s data transformation challenges.
Technology alone is never enough. But when it is well-chosen, well-integrated, and well-supported, it can truly transform how an organization creates value from its data. This partnership serves a clear ambition: to make data a strategic, reliable, and accessible lever for everyone.
Key questions for your Data project
What is an Agentic Lakehouse? It is an evolution of the Lakehouse architecture optimized for AI agents, allowing seamless interaction between language models and the company's structured/unstructured data.
How does Dremio reduce storage costs? By using Data Virtualization, Dremio avoids unnecessary data duplication and reduces dependence on complex and expensive ETL processes.
Ready to modernize your platform? Contact our Smile experts for an audit of your data architecture and discover how the Open Lakehouse can accelerate your AI projects.
