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DataStax Accelerate 2019 Building a Feature Store and Experiments Platform with DataStax Enterprise at Condé Nast

The Feature Store is a centralized, curated repository for machine learning features of our content and users. The Experiments Platform provides multivariate testing capabilities…

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DataStax Accelerate 2019 Creating a Python Microservice Tier in Four Sprints with Cassandra, Kafka, and DSE Graph

Join Jeff Carpenter, DataStax Director of Developer Advocacy, as he retraces his journey to create a Python implementation of the KillrVideo microservice tier in four sprints.  In…

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DataStax Accelerate 2019 Rapid Cloud Development with Spring Boot and Cassandra

Development today is all about getting your apps into the hands of your customers as quick as possible. It is also about keeping your data close to the customer so that the…

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DataStax Accelerate 2019 Data as a Service: Transforming Enterprise Data into Modern Applications

Keith develops strong lasting relationships at CTO Boost. He makes every client his priority, whether it is a start-up, non profit or multinational corporation, Keith treats his…

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DataStax Accelerate 2019 Developing Fault-Tolerant Applications in the Cloud with Kubernetes and Cassandra

Learn how to build and scale applications leveraging Kubernetes Engine and Cassandra. Kubernetes Engine enables rapid application development and iteration by making it easy to…

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Real-Time Insurance Product Recommendations and Customer 360 Across Multiple Clouds? We Can and You Can Too

Boggess Advisory Group helped a leading insurance giant create a streaming data platform that constructs a 360-degree view of the customer in real time. The platform powers the…

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DataStax Accelerate 2019 The Hybrid Cloud Journey: Lessons Learned

The majority of DataStax customers are running DataStax in a hybrid cloud architecture. Learn the patterns that emerge as we help our customers plan their data management strategies…

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Datastax Accelerate 2019 Predicting Restaurant Inspection Failures with DataStax Enterprise Analytics

How does a data scientist go about understanding the data and determining how to build a model? What are the problems, and how can a model be misleading? What are the tools…

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Datastax Accelerate 2019 Lighting a Spark with Machine Learning and DataStax Enterprise Analytics

Machine learning glitters as the latest skill in tech for developers. This session will combine lecture and live code that will utilize DSE Analytics and review five different…

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Datastax Accelerate 2019 Extending Gremlin with Foundational Steps

Gremlin provides the most technology agnostic way to develop graph applications. Gremlin is the graph query language of Apache TinkerPop, which is the open source graph computing…

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DataStax Accelerate 2019 The Managed Platform Driving Cassandra Adoption at Bloomberg

In this talk, we will discuss the history of Cassandra at Bloomberg and why it is uniquely positioned to address a wide variety of our workloads. We will look at the ways we've…

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DataStax Accelerate 2019 Persistent Memory Support for Cassandra

What does a database look like when we have persistent memory as fast as RAM? In this talk, we'll describe how we built an open source persistent memory toolkit for Java and how we…

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