foodpanda: Democratizing Data with Sisense for Strategic Business Analysis
Customer Company Size
Large Corporate
Region
- Europe
Country
- Germany
Product
- Sisense
Tech Stack
- PostgreSQL
- Salesforce
- Google BigQuery
- Zendesk
- Jenkins
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Industries
- E-Commerce
- Food & Beverage
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- System Integration
- Training
About The Customer
foodpanda, founded in 2012, is a market leader in global online food delivery, particularly in emerging markets. The company has experienced rapid growth, raising $300M in recent funding rounds. Operating in over 500 cities across five continents, foodpanda has partnered with more than 38,000 restaurants globally. The company employs over 3,700 people worldwide and is headquartered in Berlin, Germany. foodpanda's primary data sources include a data warehouse running on PostgreSQL servers, with data from Salesforce, SQL, Google Docs, Google BigQuery, Zendesk, and Jenkins drop scheduling.
The Challenge
foodpanda faced significant challenges with their existing data warehouse, which was unable to efficiently handle terabytes of complex data from multiple sources. The limitations included a lack of data mining functions and the inability to affordably process large volumes of data. Additionally, foodpanda aimed to centralize data to promote transparency and democratization, reducing employee reliance on the BI department. They needed an intuitive, self-service BI solution to shift the focus from data collection to insights and strategy.
The Solution
foodpanda implemented Sisense to address their data challenges. Sisense's Single-Stack™ solution allowed foodpanda to rely on one system for data preparation, querying, and visualization. The In-Chip technology enabled agile and affordable analysis of big data. Sisense's self-service platform democratized data access, transforming employees into active business analysts. The platform's versatile security features allowed for customizable user permissions and easy segmentation of dashboards. Sisense's unparalleled customer care and support further facilitated the implementation process.
Operational Impact
Quantitative Benefit
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