High quality data management for titanium manufacturer

The organization is a key strategic partner for leading companies in high-tech sectors like aerospace, aero-engines, energy, chemical engineering, shipbuilding, and medicine. They export 70% of their titanium production and serve over 300 businesses across 48 countries worldwide.

In 2012, their Lausanne-based IT team started their first data warehouse project. Though the team lacked experience in analytics, they partnered with external experts to generate their initial BI reports. As company-wide adoption of these reports grew, so did their business requirements, and with shorter timeframes.

To meet these demands, in 2017 they decided to upgrade their existing BI platform by implementing the biGENIUS Desktop App for data warehouse automation.

Within a few months after introducing biGENIUS in January 2017, the company successfully completed the IT team training and a proof of concept (POC). They then developed a new operational data store (ODS) and an enterprise data warehouse (EDW) using the biGENIUS Desktop App.

The biGENIUS Desktop App included architecture blueprints, allowing the BI team to focus on implementing business logic and delivering timely reports to users, rather than getting bogged down in technical details. The solution fully managed their data mappings and incremental loads, eliminating the need for manual development after code generation. Additionally, the biGENIUS Desktop App offered high levels of customization, making it easier to tailor the solution to the organization's specific needs.

• The biGENIUS Desktop App's automation benefits were clear throughout the process, from development to deployment. It significantly reduced both development and maintenance costs while shortening time-to-market.
• The biGENIUS Desktop App offers the team ready-to-use and customizable blueprints for data warehousing and a semantic layer for data modeling. This allowed BI developers to implement advanced data management solutions, even without extensive data analytics experience.