<<Back to events page 

Data analytics and machine learning have enormous potential to drive disruptive innovation particularly for organizations involved in the Financial Sector. Apache Spark™ is the top unified analytics engine that performs 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 for all your financial data.

In this workshop we’ll discuss the challenges of big data and share best practices for using Apache Spark in the cloud to simplify and scale data analytics. Additionally, we’ll cover how organizations leverage the Databricks Unified Analytics Platform, Spark and the cloud to power their enterprise data warehouse and machine learning use cases.

Join this ½ day workshop to learn how a unified approach to analytics in the cloud brings together data science and engineering to accelerate your data processing (ETL, schema validation, data reliability, large joins, streaming) and ML efforts (MLlib, TensorFlow, scikit-learn etc.). We will focus on financial data and analytics throughout the session including a use case on fraud detection. 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
  
• Obtain 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- 9:30 Opening Remarks - Unified Analytics and Roadmap
9:30-10:00 Customer Story - FINRA
10:00-10:30 Networking with Peers and Hands-on Set Up
10:30-11:00 Platform Demo and 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 

11:00-12:15 Hands on w/ Databricks Notebooks
12:15-12:30 Q&A