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Course Description

W8P The Modern Data Warehouse: Data Science Platforms & Application DeliveryNEW!

February 12, 2020

2:15 pm - 5:30 pm

Duration: Half Day Course

Prerequisite: Knowledge of Traditional Data Warehouse Applications

Krish Krishnan


Sixth Sense Advisors Inc.

Analytics are key enterprise insights that are delivered from the data warehouse by deploying applications and algorithms. Advances in algorithmic processing have been driven by a combination of statistics, artificial intelligence, neural networks, and mathematics. Collectively, these techniques are called data science. How do we leverage this in the enterprise? There are success stories in every use case, but are they generally applicable or are they specific to that enterprise?

Attend this course to discuss the internals and specifics of using a modern data warehouse for applications, analytics, and insights. This course deals with the front-end data science platforms and applications that consume data from the modern data warehouse. (A companion course deals with back-end data management platforms and infrastructure.)

You Will Learn

  • The foundations of the applications, analytics, and visualizations of the modern data warehouse
  • What a data science platform is and which user roles are required to build AI solutions
  • The basics of what you need to build; how to deliver enterprise-grade data integration, wrangling, and quality with Nifi and Spark
  • Delivering interactive, code-free, batch and streaming data discovery and analysis with ElasticSearch, Kibana, Timelion, and Spark SQL
  • How to deliver experimentation, modeling tools, and cutting-edge algorithm libraries for data scientists with Jupyter and JupyterHub, including how to enable collaboration, versioning, and reproducibility of data science experiments
  • How to publish predictive models to production as robust, scalable, secure, versioned APIs
  • How to support a heterogonous collection of cutting-edge machine learning and deep learning frameworks on one platform
  • How to deploy, scale, protect, and monitor an enterprise-scale platform using Kubernetes, Ansible, Calico, Prometheus, and Grafana

Geared To

  • All

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