![]() This combination should enable Slingshot to accelerate feature development in response to customer feedback, underpinned with governance-enabled data quality and usability. “The most promising features we see are the focus on and deep partnership with Snowflake, the modular building blocks for customization and the governance workflow,” Kramer said. He argues that Capital One’s experience in ensuring governance combined with high data volumes, velocity and privacy, presents a compelling data management value proposition, particularly for medium-sized businesses without the resources to build comparable capabilities. Nick Kramer, leader of applied solutions at SSA & Company, a global consulting firm advising companies on strategic execution, told VentureBeat, “Any Snowflake customer would have to be intrigued by Capital One’s application, particularly for governance.”Īll banks face stringent regulatory requirements and comprehensive, measurable governance is a cost of doing business. ![]() Capital One’s success suggests that even some of the largest and most regulated businesses can succeed in going all in on the cloud. In the early days of the cloud, many regulated industries were concerned with some governance challenges of moving their processes off their internal servers. For example, they found that development and testing teams often previously provisioned much larger instances than required. It also helps ensure that teams don’t over provision data warehouses. For example, it can alert analysts when a query is inefficient so they can turn it off and create a more efficient one. It also helped reduce Snowflake costs by 27%, improve the cost per query by 45% and save over 50,000 hours of work. This allowed them to onboard almost 450 new use cases since migrating from the on-premise data infrastructure. So, they developed self-service tools that empowered business units, with data management, cost controls, and automated governance baked in. They found that the old model of trying to centralize analytics was not feasible, since central teams don’t have the expertise and domain knowledge to process data across business units. So, his team worked on a new management tier that helped create and enforce best practices across Capital One. “The challenge was how to make sure you are using Snowflake as efficiently as possible,” Syed said. But they soon discovered that many of these queries were inefficient and often resulted in provisioning excess cloud infrastructure, which increased costs. The platform’s simplicity allowed analysts to develop new analytics as fast as they could combine datasets. However, this introduced new data management challenges. In 2017 Capital One began migrating all its data to Snowflake, which helped automate many aspects of data management and sharing. “We were betting on the fact that the cloud would become this place where apps could be developed quickly,” Syed explained. The cloud also suggested a way to scale and change directions quickly when needed. ![]() This had been a big challenge with their on-premise database, particularly at busy times of the month. ![]() In addition, the cloud promised a way to enable workload isolation so queries from one team of analysts did not impact others. Salim Syed, head of engineering at Capital One Software, told VentureBeat they believed the cloud could help scale the number of queries its 6,000 business analysts could run concurrently and make it easier to share data across the business. Capital One was one of the first banks to go all in on the AWS cloud in 2015.
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