SKOPOS Delivers Deep Market Insight via Automated Analytics with Alteryx
Region
- Europe
Product
- Alteryx
- Tableau
Tech Stack
- Data Visualization
- Automated Analytics
Impact Metrics
- Productivity Improvements
- Digital Expertise
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Big Data Analytics
Use Cases
- Real-Time Location System (RTLS)
Services
- Data Science Services
About The Customer
SKOPOS is a technology company based in Europe. The company specializes in providing market insights and has a dedicated Business Intelligence department. The company collects and analyzes a large volume of survey data, over 2 million responses, to provide deep market insights. The company was looking for a solution to prepare, enrich, and model this data for visualization in Tableau. The goal was to help its team visualize the survey data in a more efficient and effective manner.
The Challenge
SKOPOS, a technology company based in Europe, was seeking a solution to prepare, enrich, and model data for visualization in Tableau. The goal was to help its team visualize survey data in a more efficient and effective manner. The company was dealing with a large volume of data, over 2 million survey responses, and needed a way to analyze this data in near-real-time. The challenge was to find a solution that could handle the complexity and volume of the data, and deliver the desired results.
The Solution
SKOPOS decided to use Alteryx, a data science and analytics solution, to handle their data preparation, enrichment, and modeling needs. They started with just transforming a single data set and gradually expanded to combining different data sets, running automated model predictions, and using multiple dashboards. All these processes are populated through Alteryx workflows. The solution allowed SKOPOS to handle the complexity and volume of their data and deliver near-real-time results. The use of Alteryx made it easy for SKOPOS to work with such a large volume of data, something that would have been impossible using traditional SPSS methods.
Operational Impact
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