Brought to you by DataStax & IBM

WEBINAR: Modernize Your Data Architecture to Scale AI in the Cloud

Wednesday, June 30, 9 AM PT

Many enterprises are struggling to run modern workloads using legacy databases that can’t keep up with real-time, highly active, and unstructured data.

Success in 2021 relies on modern data applications and databases that are always on, highly scalable, secure, and able to utilize real-time data.

In this fireside chat-style webinar on Wednesday, June 30, 9 AM PT, Patrick Callaghan, VP of Partner CTO at DataStax, and Alan Villalobos, VP of Development, Partnerships, Data and AI at IBM, dive into how together, IBM Cloud Pak for Data and DataStax Enterprise (DSE) enable a Cassandra-based distributed datastore, coupled with best-in-class data science, governance, and privacy.

You'll Walk Away With

• The know-how to run a Kubernetes-native database, with the benefits of IBM’s ecosystem and DSE’s cloud-native API’s
• How to enable a  lightning-fast data layer that seamlessly supports and can keep pace with AI/ML
• Use cases for realtime, massive amounts of data

Meet The Speakers

VP, Partner CTO at DataStax

Patrick Callaghan has been a Technology and Business Strategist at DataStax for over 7 years. He works with companies implementing and supporting mission-critical applications across hybrid and multi-cloud environments. Prior to DataStax, Patrick held roles in the banking and finance architecting and developing real-time applications.

VP of Development, Partnerships, Data and AI at IBM

Alan joined IBM in 2018 to build a Data Visualization practice as part of the Data Science and AI Elite team. He has a background in Computer Engineering and spent 13 years in the Life Sciences industry leading software teams and building ML models for Gene Engineering. Alan's other expertise is in Data Visualization and building visual tools, fulfilling business and scientific needs through the development of Rich Interactive Applications and effective visualization.

Join us Wednesday, June 30, 9 AM PT

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