BI,Case Study
NEW, MODERN BUSINESS INTELLIGENCE AND ANALYTICS TO SIMPLIFY DATA MANAGEMENT
INTRODUCTION One of Germany’s largest insurers needed a partner to implement a new,
modern business intelligence and analytics landscape based on the AWS Cloud. Consulting services were required in the area of strategic and conceptual consulting and conceptual consulting as well as in the concrete implementation. CASE DESCRIPTION The insurance company planned to establish a new BI and analytics landscape based on Amazon Web Services (AWS) and needed to create this based on a cloud strategy with a common database to cover requirements from analytical use cases and big data. The existing technology stack was to be questioned and, if necessary, replaced.
Suggested architecture:
Overall, the architecture aimed to transform raw data delivered by source systems into information useful to end users. This supported rational decisions by users in a data-driven organization.
The source systems on the left provided the necessary raw data. These can be operational systems such as PARIS and SAP but also user-generated files in structured or unstructured file formats (Excel, CSV files, forms). External parties can also supply or provide this data (e.g. telematics data). The delivered data is then recorded in the data lake. In the architecture, the data lake is fully inte- grated and is used to record data deliveries that are independent of itself. These are initially ingested in the data lake in raw form without further transformation or preparation. However, the data is organized so that it can be efficiently accessed later. The proposed architecture implements this reusability efficiently and consistently; thus, not only can data be reused but also the results of the business logic can be as well. This harmonized the data-driven solutions of the clients and made them comparable.
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The architecture was implemented in the BI@AWS project in the AWS Cloud. Various AWS-native tools were used in the process. ● Loading data from the source into the data lake: Python. In particular, the implementation of the GDPR and the dynamic loading of the raw data could be performed well with this. ● The Snowflake DB was used for the implementation of the EDW. This is a database developed for data warehousing that runs natively in the AWS Cloud. ● Snowpipe was used to transfer the data from the data lake to the EDW layer.
Project procedure illustration :
The concrete solution for the customer was that the access to the data overview was simplified. Ad- ditionally, the Scalefree Consultants developed a GDPR-compliant data infrastructure for the client. For the multi-temporal analysis of data, the access was simplified. Further, network resources have been significantly secured to prevent unauthorized access. Adding to the result, knowledge transfer through knowledge management systems and workshops with users was achieved. Finally, a clean documentation and guideline was created by Scalefree regarding the integrated system.
Scalefree International GmbH Schützenallee 3, 30519 Hannover, Germany
P: +49 (511) 879 893 41 M:+49 (175) 811 0336 F: +49 (511) 879 893 49
info@scalefree.com www.scalefree.com
CEOs: Michael Olschimke & Christof Wenzeritt
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New Business Intelligence and Analytics Landscape for a Insurance Company © Scalefree International GmbH 202 3
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