Dataiku > Case Studies > Revenue-Generating Data Projects from the Ground Up

Revenue-Generating Data Projects from the Ground Up

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Region
  • Europe
Product
  • Dataiku
Tech Stack
  • Hadoop
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Revenue Growth
  • Productivity Improvements
Technology Category
  • Platform as a Service (PaaS) - Data Management Platforms
  • Analytics & Modeling - Big Data Analytics
Applicable Industries
  • Telecommunications
Applicable Functions
  • Product Research & Development
  • Business Operation
Services
  • Data Science Services
About The Customer
LINK Mobility Group is Europe’s leading provider of mobile communications, specializing in mobile messaging services, mobile solutions, and mobile data intelligence. They facilitate the sending of more than 6 billion messages every year. They offer a wide range of scalable services and solutions across industries and sectors due to the growing demand of digital convergence between businesses and customers, platforms, and users. In 2017, they decided to scale up their data efforts both when it came to handling internal requests as well as externally with customers. They produce a lot of data and saw an opportunity to expand their offerings to provide more data-driven insight to customers surrounding the delivery and performance of their messages and services.
The Challenge
In 2017, LINK Mobility, Europe’s leading provider of mobile communications, decided to scale up their data efforts for handling internal requests and externally with customers. Their primary offering is mobile messaging services, sending more than 6 billion messages a year worldwide carrying invoices, payments, and vouchers, associated with various services. They produce a lot of data and saw an opportunity to expand their offerings to provide more data-driven insight to customers surrounding the delivery and performance of their messages and services. They were looking to expand to customer dashboards as well as the ability to take action based on that data. However, with just a one-man data science team at the beginning of the project, they needed to be able to get up and running quickly and easily. They also needed to find a tool that would allow them to scale up data requests coming from inside the company as well as to be flexible enough to provide data insights to customers without having to use two different tools or platforms to cover their various needs, use cases, and data types.
The Solution
LINK Mobility turned to Dataiku because of its ability to quickly facilitate the deployment of revenue-generating monitoring services to customers with a small staff. By using Dataiku on top of Hadoop, LINK Mobility is now able to easily work with large amounts and diverse types of data. The team went from data lake setup to first completed data project in just seven months, which is half the time it would have taken without Dataiku. In addition to successfully deploying an entirely new product and business area to enhance the company’s existing offerings, LINK Mobility also leverages Dataiku for facilitating collaboration and internal communication between business teams and technical staff by providing a single platform in which both are comfortable working, self-documentation and easy reuse of work, combining coding in notebooks with visual recipes to speed up analysis, and as the go-to tool for any data needs.
Operational Impact
  • The team went from data lake setup to first completed data project in just seven months, which is half the time it would have taken without Dataiku.
  • Successfully deployed an entirely new product and business area to enhance the company’s existing offerings.
  • Facilitated collaboration and internal communication between business teams and technical staff by providing a single platform in which both are comfortable working.
  • Self-documentation and easy reuse of work; in other words, showing how data is transformed in an intuitive way so that other team members can be onboarded easily and all data processes can be quickly explained.
  • Combined coding in notebooks with visual recipes to speed up analysis.
Quantitative Benefit
  • Time to produce data projects was reduced by half.
  • Expected to add substantial additional revenue and cut costs from preventing customer churn and increasing the overall stickiness of the company and its services.

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