Customer Story

A smart BI@AWS solution for better decisions

The ever-increasing volume of data presented DEVK Insurance with the challenge of replacing its very complex data warehouse with a central, analytical and flexible platform – which should enable better use of all data sources.

In Short


Existing data warehouse is too complex and confusing.


A business intelligence and analytics platform in AWS.


Faster integration of data sources while increasing flexibility.

Our solution

In the future, only insurance companies that use their data intelligently will prevail. One of the results of the "Creating value with data" study, which KPMG conducted in collaboration with Bitkom Research, was that this is exactly what an increasing number of companies are doing. Data has always formed the basis for analyses, evaluations and product development at insurance companies. Today, this data is available in huge quantities. The trend is clear: Insurance company and insured party now know a lot more about each other than before.

Existing platform was far too complex

Over the past years, DEVK Versicherungen set up a data warehouse (DWH) based on Oracle, Informatica and MicroStrategy, and launched it at the end of 2017. It mainly contains data on claims from property insurance, partner information, collection data and data from the document management system. This DWH was not widely accepted and used within DEVK, as the implemented structures were very complex.

Design of a BI and analytics platform

The DEVK therefore had a clear goal: A central, analytical and flexible data platform was to enable better use of all data sources while at the same time providing a comprehensive 360-degree view of DEVK customers. In line with DEVK’s cloud strategy, the project was implemented in the Amazon Web Service Cloud (AWS) and given the project name BI@AWS. The AWS cloud had already been connected to the DEVK infrastructure by the IT department, but BI@AWS was the first major project in this setup.

During the course of the project, detailed coordination as well as compliance and security-relevant adjustments were repeatedly necessary. The field of application of BI@AWS is very extensive. It ranges from marketing, sales and customer support to product development, where the focus is on new, data-based insurance products in particular. A prominent example of such a product is the DEVK telematics tariff*, which takes driving behaviour into account when setting the price, and for which very large data volumes must be analysed.

The new BI platform in the Cloud is of great strategic importance to DEVK. We knew straight away that it would not work without competent support.The new solution enables all aspects of a modern analytics platform to be used on a uniform technical basis for the first time, thus enabling DEVK to take a major step forward on the path to digitalization.

Günter Döge, Head of IT, DEVK

From design to go-live

After a big data orientation workshop, we were commissioned to design the target architecture and implement the Business Intelligence and Analytics (BIA) platform in AWS. The data from the old DWH as well as numerous source systems were transferred to the data lake. The enterprise DWH architecture was jointly designed and the first use cases of exploratory analytics, such as telematics, went live in labs.

With the new solution and system architecture, the integration of data sources works much faster than in the classic setup, while at the same time providing significantly greater flexibility. In addition, BI@AWS has made new forms of data analysis possible in the first place: The integration of large amounts of data in the area of telematics provided the basis for analysing the corresponding insurance product. The BI@AWS solution offers business departments and data scientists a comprehensive system environment that will be successively expanded to include additional data sources and thus flexibly map additional use cases. These capabilities form the basis for achieving decisive added value for DEVK in the long term.

Technologies used

  • Amazon Web Service (AWS) as cloud provider
  • S3 as data store for data lake and analytic lab
  • Redshift for the enterprise data warehouse
  • Glue, Athena for data access of the BI tools
  • biGENIUS for EDW automation
  • EMR for data lake management
  • Terraform as IAC solution

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