Becoming a Data-Driven Company With Looker
Customer Company Size
Mid-size Company
Region
- Europe
Country
- Germany
Product
- Looker
Tech Stack
- LookML
- Slack
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Digital Expertise
Technology Category
- Analytics & Modeling - Data-as-a-Service
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Services
- Data Science Services
About The Customer
Raisin is a successful Fintech start-up based in Germany. Founded in 2013, it operates several deposit marketplaces across Europe under the brands WeltSparen and Raisin. By the end of 2019, Raisin had scaled to over 225,000 customers, with a brokered volume of roughly 18 billion euros. The company has grown from a mere 30 employees to more than 200, each with a Looker account. The business intelligence platform has been the linchpin of Raisin’s data-driven culture ever since. Raisin's vision is to make data accessible to every employee, enabling them to make as many decisions as possible with data support.
The Challenge
Raisin, a successful Fintech start-up in Germany, was facing challenges with data management. Much of the company's data was stored in Excel spreadsheets, making it difficult to access and utilize effectively. The rapid growth of the company and management’s vision of a strong data culture necessitated a streamlined approach to data handling. The company's vision was to make data accessible to every employee, enabling them to make as many decisions as possible with data support. However, they lacked the necessary infrastructure to achieve this. They needed a self-service platform that would provide a unified view of all data sources and allow each employee to obtain easy access to the relevant insights.
The Solution
Raisin decided to implement Looker, a business intelligence platform, to democratize data within the company. Looker met Raisin's three key requirements: it was intuitive, enabling every employee to access data, even those without previous technical knowledge; it helped the BI team to be efficient, processing requests for new metrics and dashboards quickly; and it had self-service capabilities, allowing employees to configure and visualize ad-hoc analyses, easing the pressure on the data team. Looker’s data modeling language, LookML, impressed Raisin the most. With LookML, all you need to do is define the data model once, and then it is available to every user. Looker also offers enormous flexibility when it comes to updating key metrics, such as price models and performance indicators.
Operational Impact
Quantitative Benefit
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