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Learn moresavings per use case
faster queries
EMEA
Financial Services & Insurance
Hadoop
Enterprise
1000+
Not only has Starburst effectively solved our legacy data architecture problem, but Starburst is one of the very few professional organizations that offers both the people and technology that can lead us to success.
Anonymous, Chief Data Science Architect
savings per use case
faster queries
The financial institution is one of the world’s largest banking and financial services organizations. The bank serves approximately 39 million customers worldwide in 62 countries and territories. The bank embarked on a data transformation project with Starburst and Google Cloud to tackle complex data landscapes, suboptimal Hadoop estates, stringent data lineage requirements, and multi-cloud data silos.
The result is a future-proofed data infrastructure that accelerates data processing and analysis, enhances compliance, reduces cost, and fosters innovation through self-service analytics, giving the bank a competitive edge.
The financial institution was heavily relying on-premise Hive and Spark workloads which were great for ETL but not for analytics. Analytics teams relied on the Hadoop data lake for every use case that they were tasked to deliver – from product recommendations, risk profiles, pricing profiles, customer touch points, through bonding.
It took hours to perform analytics queries and there were high volumes of inconsistencies in the data copying which meant that data could not be read fast enough. Data engineers were duplicating and moving data unnecessarily, wasting storage space and licensing. Every time production requests were made to move the data, this resulted in wasted man hours and delayed insights (up to 6 weeks).
In addition to optimizing data processing for analysis, the bank also wanted to meet data sovereignty requirements, improve data lineage, and future proof their data infrastructure to fuel future innovation.
To remove the data bottleneck in Hadoop, the bank embarked on a modernization journey with Google Cloud Platform. It also needed a solution to facilitate federated queries between siloed systems and speed up ad-hoc analytics on the Hadoop data lakes. The institution ultimately chose Starburst Enterprise over Denodo and other vendors due to stronger performance with Starburst’s data lake analytics platform.
The project incorporated several innovative solutions to tackle existing data management problems, including:
End-to-end data lineage: The project has successfully integrated Starburst’s capabilities to complete the last mile of data lineage, from data assets to the consumption layer. This integration provides an end-to-end usage tracking solution at the user and use case level, enhancing the overall data governance and management process.
The project successfully delivered on the desired business value – to enable better informed decision-making, meet data sovereignty compliance, and reduce the costs of their on-premise data infrastructure. By partnering with Starburst and GCP, the bank has substantially improved the ability to achieve their core goals in several ways:
*Cost savings estimated from eliminating 6 weeks of work from each workload by no longer requiring data movement and data pipelines.
The success of the data modernization project has laid the groundwork for continuous innovation in data management and analytics, ensuring that the organization remains at the forefront of technological advancements and is well-equipped to embrace future opportunities and challenges.
EMEA
Financial Services & Insurance
Hadoop
Enterprise
1000+
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Up to $500 in usage credits included