Michelin: Democratizing AI for Improved Industrial Performance
Michelin uses Dataiku to democratize AI, improving quality, maintenance, machine availability, supply chain, energy consumption, and more.
Learn MoreDashboards are a common deliverable for teams across an enterprise, especially in customer-facing roles where having a complete understanding of consumer behavior is critical to operations. However, they can be challenging to produce scalably or keep updated regularly, and often they prove to be more of a burden than an agile tool used reliably for insights.
Challenges: Lack of Transparency & Siloed Data
The primary point of contact between OVH and its users is through their website, where customers can place an order and receive technical advice or support. Therefore, analyzing users’ interactions and deriving insights from their behavior to inform the product and operations teams’ decisions is paramount. But the business analysts responsible for disseminating data and insights to inform on the commercialization and optimization of the website were facing issues; namely, they had built a dashboard with basic, high-level metrics (like user behaviors and site traffic), but its utility was limited.
The main problem was that the dashboard didn’t combine different data sources for a complete view, so it necessitated ad-hoc analysis, for which the analysts had little time. Additionally, ETL (extract, transform, load) for the dashboard presented concerns for the data architects around data and insights quality, as there was a lack of transparency around exactly what data was being transformed and how.
How Analysts at OVH Used Dataiku to Help
OVH turned to Dataiku to power their dashboards, leveraging its features to slash data preparation time and ensure visibility into the data life cycle. Thanks to Dataiku, OVH business analysts were able to:
- Quickly connect directly to any number of data sources (weblogs, CRM, etc.).
- Combine data sources for more complete customer insights.
- Do data preparation work efficiently thanks to an intuitive visual interface and the automation of much of the process.
- Have a culture of experimentation and rapid prototyping.
In addition, on the IT side, Dataiku gives data architects peace of mind that analysts are working with quality data thanks to the clear visualization of data flows. Those data architects can also clearly see and correct any issues in data quality directly.
OVH increased the efficiency of its analysts by 40%, and as a consequence, they are now better able to contribute to projects and work together with the rest of the team. They attribute the significant time optimization to Dataiku’s more efficient solutions for data preparation and data workflow monitoring. All of these gains amount to a faster time-to-market overall, accelerating OVH’s ability to go from data warehouse to meaningful business insights.