Wednesday, September 5/ Grand Hyatt Washington D.C.
Data analytics and machine learning have enormous promise - it has the potential to drive disruptive innovations affecting most enterprises on the planet. Apache Spark™ is the top unified analytics engine that introduces big data processing at massive scale and combines that with a platform for machine learning. Couple the power of Spark with the cloud and you can realize the benefits of the fastest analytics engine with the operational simplicity of the cloud.
In this workshop we’ll uncover the challenges of big data and ML, best practices for enterprises to use Apache Spark and the cloud to simplify and scale your data analytics efforts. We’ll dive into the components of Apache Spark, how Spark is used for common use cases such as ETL, SQL analytics, and machine learning, and how taking the power of Apache Spark to the cloud with the Databricks Unified Analytics Platform can simplify data engineering operations and accelerate data science innovation.
Join this ½ day workshop to learn how a unified approach to analytics in the cloud can bring data science and engineering together to accelerate your data processing and ML efforts. This free workshop will give you the opportunity to:
- Get under the hood with Apache Spark to learn key components and use cases
- Learn to build highly scalable and reliable pipelines for analytics
- Best practices for building, training, and deploying ML models into production
- Network and learn from your ML and Apache Spark peers
AGENDA AT A GLANCE
8:30-9:00 Registration, Breakfast & Networking
9:00-9:15 Opening Remarks - Unified Analytics
9:15-9:30 Introduction to Apache Spark, Unified Analytics Engine
9:30-10:15 Apache Spark Use Cases
- ETL - Learn how to easily build a robust and scalable ETL pipeline with Spark
- SQL Analytics - Learn how Spark accelerates SQL queries by 100x over Hadoop
- Machine Learning - Learn how to simplify ML with Spark’s seamless integrations with ML frameworks and libraries such as TensorFlow, PyTorch, R and SciKit-Learn
10:15-10:45 Networking with Peers
10:45-11:45 Interactive Demo & Apache Spark Best Practices on Databricks Unified Analytics Platform
11:45-12:30 Customer Story - Moving Analytics and ML to the Cloud
12:30-1:00 Q&A