Dataiku > Case Studies > Streamlining Data Efforts and Saving Time: U.S. Venture's Success with Dataiku

Streamlining Data Efforts and Saving Time: U.S. Venture's Success with Dataiku

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 Streamlining Data Efforts and Saving Time: U.S. Venture's Success with Dataiku - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Machine Learning
Applicable Industries
  • Automotive
  • Transportation
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Time Sensitive Networking
  • Transportation Simulation
Services
  • Data Science Services
The Challenge
The Data and Analytics team at U.S. Venture faced challenges in managing and analyzing customer data due to the complexity of operating in multiple industries. They also had difficulties in creating enterprise tools and processes that foster collaboration and remove silos.
The Customer
About The Customer
U.S. Venture is an innovative leader in the energy and transportation industries, operating in market segments such as industrial lubricants, tires and parts, alternative fuel applications, transportation strategy optimization, and fueling infrastructure. They have over 2,500 employees and a family of brands.
The Solution
The team implemented Dataiku to streamline their data efforts and create a culture of reuse. They consolidated processes that were coded differently into reusable recipes in Dataiku, enabling collaboration and project visibility. They also automated manual steps, saving time for analysts and data scientists. Excelion Partners provided training and support to help the team get up to speed quickly.
Quantitative Benefit
  • The use of Dataiku saved the Data and Analytics team at U.S. Venture thousands of hours by reducing the time required for market analysis from 60-100 hours to just three hours. This represents a time savings of 95% to 97%. The team also achieved hard cost savings by avoiding the need for expensive point software solutions. Furthermore, the upskilling of data analysts allowed for a larger and more capable analytics organization.

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