Utilizing Big Data Analytics Hadoop

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How important are data and analytics to a banker’s bottom-line objectives – growing deposits, loans and the customer base? In the latest Digital Banking Report, AI for Improved Customer Experience, almost 90 percent of respondents indicated that advanced analytics is extremely or very important to capabilities like cross-channel contextual communications, proactive advice and audience targeting.

Attend this webinar to find out how Portworx and Red Hat are working together to help you run your Kubernetes applications. In this talk, learn how Portworx Kubernetes Data Platform delivers the enterprise-grade features you need to manage and automate the data in your Red Hat OpenShift on AWS (ROSA) environment while reducing the AWS infrastructure bill by up to 60%.

With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.