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Engel & Völkers Enhances Real-Time Operational Insights with Fivetran
Technology Category
- Analytics & Modeling - Real Time Analytics
- Functional Applications - Warehouse Management Systems (WMS)
Applicable Industries
- Equipment & Machinery
Applicable Functions
- Sales & Marketing
- Warehouse & Inventory Management
Use Cases
- Picking, Sorting & Positioning
- Real-Time Location System (RTLS)
Services
- Data Science Services
- System Integration
The Challenge
Engel & Völkers, a prestigious broker of premium residential property and commercial real estate, was facing a significant challenge in integrating various data sources. The company's data engineering team was inundated with requests from different departments for data integration. The process of creating custom solutions to respond to these requests was resource-intensive, leading to prioritization of tasks and inability to cater to the growing number of requests. The company was in dire need of a tool that could reduce the effort required to integrate new data sources and enable faster data integration, thereby promoting wider adoption of self-service analytics within the organization.
About The Customer
Engel & Völkers is a renowned broker of premium residential property, commercial real estate, yachts, and aircrafts. With over 40 years of experience, the company has more than 16,000 employees in over 30 countries. Engel & Völkers specializes in sales and leaseholds of luxurious properties and offers consultancy services. The company values competence, exclusivity, and passion, and these values are increasingly fueled by data analytics. Engel & Völkers' most valuable asset is data-based insights, which are used to drive decision-making and optimize operations across the organization.
The Solution
Engel & Völkers turned to Fivetran to streamline their data integration process. The first Fivetran connectors were set up within a few days, a task that would have taken the data team at least four times as long. The company now relies on over 15 Fivetran connectors for data integration. Fivetran is primarily used for three use cases: IT Operations Insights, Self-service analytics, and Marketing optimization. For IT Operations Insights, data from the project management ticketing system Jira is used to measure the performance of all teams and projects, optimize resource allocation, and improve productivity. For Self-service analytics, local teams manage data ingestion themselves by adding csv-files to a Google Drive folder, which automatically synchronizes with the data warehouse, making all data available for analytics in Tableau. For Marketing optimization, data from at least six different marketing channels are integrated into the data warehouse, enabling the marketing team to perform elaborate real-time analytics.
Operational Impact
Quantitative Benefit
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