About the Client

Our client, a leading global insurance provider, offers diverse insurance products for individuals and businesses. Seeking improved data management and reduced operational costs, they embarked on strategic enhancements.

Problem Statement

The client wanted to manage its data efficiently and effectively. Operational expenditure was high due to the process of acquiring data with a single version of truth from data coming from a vast number of sources.

Their old solution posed several problems:

  • Scaling and modification in the existing system was a complex process
  • Difficult to manage multiple tools and technologies
  • All the above problems lead to high cost

The Challenge

The challenges involved were:

  • Lack of expertise in Data Vault methodology
  • Lack of documentation of their old solution
  • Handling GDPR data was another challenge
  • Standardization and verification of the address data
  • Time pressure, as the client did not want to extend the contract of the tools used in their old solution
  • Adaptation of the customer dashboards to the new Master Data Hub layer, based on best Data Vault practices

The Solution

Scalefree presented the client with the following:

  • Implemented the best practices of Data Vault 2.0
  • All the processes are well documented
  • GDPR issue was resolved using the Data Vault approach
  • Provided SQL dynamic script based on belmap solved the problem of address standardization
  • Agile approach led to quick integration of different sources
  • New solution was tested and implemented in the Dashboards
From Problem to Solution

Tangible Results for the Client

The following issues were successfully resolved:

  • The migration was completed successfully within 4 months
  • It led to a major cost saving
  • All the dashboards were rewired to the new solution
  • A single version of truth is available on a cloud based Snowflake data platform

Technologies involved

  • Snowflake
  • Wherescape
  • Informatica
  • DB2
  • Collibra

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JÜRGEN DACKWEILER

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