Cloud-based
data analysis

After-sales data such as information on complaints, customer satisfaction surveys or customer loyalty measures is often stored in different locations, different formats and for different purposes. Insular information management systems like these are known as data silos, and make evaluation of the data very time-consuming if not impossible.

Cloud-based data analysis and visualisation using an automated data pipeline can be the perfect solution when it comes to optimising after-sales activities and strengthening customer loyalty. And machine learning methods provide useful support.

• The goal is efficient data analysis with an integrated analytics platform

• Integration of heterogeneous data sources

• Structuring of the data

• Creation of an automated end-to-end data pipeline

• User-friendly implementation of dashboards to visualize the data

• Our data-driven technologies at a glance

In order to structure after sales data correctly, an automated cloud solution is being developed on AWS. This enables the connection of different, distributed data sources. The data is read in automatically at regular intervals. A central data repository is set up to back up all data in one place (to avoid data silos).

• By implementing an end-to-end data pipeline, data can be prepared, transformed, aggregated, cleansed and analyzed.
• The clear visualization of the data is ultimately done with Tableau.

• Fast, efficient decisions

• Available data is relevant and meaningful

• Data can be evaluated and displayed quickly and easily

• Data is readily accessible to a wide range of users on custom dashboards