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Scaling Up Data Efforts

 Scaling Up Data Efforts - IoT ONE Case Study
The Challenge

In 2017, LINK Mobility decided that they wanted to scale up their data efforts both when it came to handling internal requests as well as externally with customers. 

LINK Mobility produces a lot of data and saw an opportunity to expand its 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 send additional offers based on that data.

LINK Mobility needed to find a tool that would allow them to scale up data requests coming from inside the company as well as be flexible enough to provide data insights to customers without having to use two different tools or platforms to cover their various needs.

The Customer

LINK Mobility Group

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 offer a wide range of scalable services and solutions across industries and sectors due to the growing demand for digital convergence between businesses and customers, platforms, and users.

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. The LINK Mobility’s team completed their first data project in just seven months which is half the time it would have taken without Dataiku.

  1. By using Dataiku, LINK Mobility is able to:
  2. Easily work with large amounts and diverse types of data.
  3. Facilitate collaboration and internal communication between business teams and technical staff by providing a single platform in which both are comfortable working.
  4. Easily reuse their previous 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.
  5. Combine coding in notebooks with visual recipes to speed up analysis.
  6. Use the go-to tool for any data needs.

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