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Dataiku > Case Studies > Heetch + Dataiku: Developing an Elastic AI Strategy
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Heetch + Dataiku: Developing an Elastic AI Strategy

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
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.
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 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
  • Since moving to Dataiku, Heetch saw both a decrease in frustration from the previous bottleneck caused by the data warehouse as well as a notably faster time to market for Heetch data projects coupled with a greater ROI thanks to cost control.
  • The team has launched hundreds of data projects with Dataiku, ranging from features stores and ETL projects to real-time fraud detection, churn prediction, route optimization, passenger/driver segmentation, pricing models, marketing attribution tracking, and more.
  • Dataiku has allowed Heetch not only to transform its ability to leverage elastic resources, but to uplevel its overall AI maturity.
Quantitative Benefit
  • Decrease in frustration from the previous bottleneck caused by the data warehouse.
  • Notably faster time to market for Heetch data projects.
  • Greater ROI thanks to cost control.

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