Heetch + Dataiku: Developing an Elastic AI Strategy
Company Size
200-1,000
Region
- Europe
Country
- France
Product
- Dataiku
- Kubernetes
- AWS EKS
Tech Stack
- Python
- R
- Spark
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Digital Expertise
- Productivity Improvements
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Transportation
Applicable Functions
- Business Operation
Use Cases
- Fleet Management
- Predictive Maintenance
- Supply Chain Visibility
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Heetch is a French company founded in 2013 with the goal of making mobility more accessible by offering a smooth user experience. The company has grown quickly to 250 employees and has gathered troves of data from drivers, passengers, global operations, and more since its launch. However, as the amount of data grew, the company struggled to scale their ability to leverage that data. Five years in, data warehouse costs were spiraling out of control, and performance was suffering. The company needed to find a solution that would allow anyone across the organization to work with large amounts of data while also ensuring optimized resource allocation.
The Challenge
Heetch, a French company founded in 2013, has grown quickly to 250 employees united around one goal: making mobility more accessible by offering a smooth user experience. The company has gathered troves of data from drivers, passengers, global operations, and more since its launch, yet they struggled to scale their ability to actually leverage that data. Five years in, data warehouse costs were spiraling out of control, and performance was suffering as the amount of data grew. The company needed to find a solution that would allow anyone across the organization to work with large amounts of data while also ensuring optimized resource allocation.
The Solution
In 2019, Heetch chose Dataiku as their single platform for building data pipelines and processing raw data, paired with Looker for the seamless visualization and exploration of those flows. In addition to serving as a platform where Heetch could centralize knowledge and best practices, the team also leveraged Dataiku and Kubernetes to address their primary paint point: leveraging data while maintaining good performance and reasonable costs. Thanks to Dataiku’s native integration with major cloud vendors’ managed Kubernetes services, Heetch was able to integrate their AWS EKS cluster very quickly and saw a drastic increase in value from their data. Teams can now easily offload resource-intensive workloads, like big Python and R jobs, as well as leverage the EKS cluster to distribute compute and run Spark jobs. Using Dataiku means this functionality is available and accessible to any Heetch employee, no matter his or her knowledge in distributed computing — Dataiku abstracts away the complexity.
Operational Impact
Quantitative Benefit
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