Analytical data models which were previously managed in an on-premises Hadoop environment.
Steel materials, products, systems and technologies, BlueScope plans to undergo a major data and analytics transformation, leveraging the Cloud based Azure Synapse Analytics to ensure limitless analysis capability.
About 800 BlueScope analytical data models which were previously managed in an on-premises Hadoop environment are being transitioned to Azure Synapse Analytics and Azure Databricks.
The current on premises solution, whilst delivering significant value to BlueScope over the past four years, was reaching its limits based on the growing requirements and usage demand of the data platform.
Rather than performing a lift and shift to the cloud, BlueScope has undertaken a root and branch transformation of its data and analytics services that promises unprecedented insights and longevity, with Azure Synapse Analytics’ able to meet the company’s current and future needs, said Julianne Tancevski, data platform product owner at BlueScope Australia.
“We are moving to an infinitely scalable, high performance cloud analytics platform that is able to not only meet our current needs but grow dynamically with the business as we proceed in our data-driven digital transformation,” she said.
Working closely with Microsoft’s global team of data and analytics engineers and specialist data and AI partner, Versor, BlueScope will be able to complete the “in-flight” transformation over a period of eight months – all the more impressive given the workplace limitations imposed by COVID-19.
An array of Azure tools and services will be used to facilitate the transformation including Azure Data Factory, ADLS Gen2, Azure Databricks, Synapse Analytics, and Azure Analysis Services.
The on-premises Hadoop environment has more than 800 custom models that will be migrated to Azure Databricks, vastly simplifying BlueScope’s analytical operations.
Looking ahead, BlueScope has begun using Azure Machine Learning to improve critical steel manufacturing processes and tackle cash positions predictions. Extending this scalable ML platform will mean delivering critical business insight across the entire operation.
