Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.

In this virtual workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your data engineering and ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources. You’ll learn how to use a scalable compute engine for analytics and ML workloads, and how Databricks provides a common interface and tooling for all stakeholders (data engineers and data scientists), regardless of skill set, to foster strong collaboration.

Join this virtual workshop to learn how unified data analytics can bring data science, business analytics, and engineering together to accelerate your data and ML efforts. This workshop will give you the opportunity to:

• Learn how to build highly scalable and reliable pipelines for analytics.
• Deeper insight into Apache Spark and Azure Databricks, including the latest updates with Delta Lake. 
• Use a popular programming language (Python, R, Scala, Java, SQL) to run your data and ML workloads at scale.

AGENDA AT A GLANCE

• 2:00pm SGT / 11:30am IST - Azure Databricks Opening Remarks
• 2:05pm SGT / 11:35am IST - Unifying Data Science, Business Analytics and Data Engineering
• 2:20pm SGT / 11:50am IST - Customer Use Case
• 2:40pm SGT / 12:10pm IST - Data Analytics Interactive Demo
• 3:00pm SGT / 12:30pm IST - Q&A
• 3:15pm SGT / 12:45pm IST - End

Sign up today to reserve your spot!