SPARK + AI SUMMIT | SAN FRANCISCO, CA
The Virtual Event for
Data Teams
NOW ON-DEMAND
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Migrate your on-premises big data workloads to Azure Databricks

Webinar

Streaming from: San Francisco, CA

In this webinar you’ll learn why successful organizations are switching to modern, cloud-based platforms like Azure Databricks to drive innovation, productivity, and business outcomes. Leave with a best practice framework for safely and securely migrating data and workloads to Azure.

Fine Grained and Scalable Demand Forecasting

Webinar

Virtual Event

Learn best practices for forecasting demand not only at scale but also at a granular level by data, by SKU, by store.

Migrating Big Data Systems to the Cloud

Webinar

Virtual Event

Join our virtual conference to learn why companies are switching to transformative, cloud-based platforms like Databricks to drive productivity, exceed business goals and reduce TCO. You’ll also learn a best-practice framework for safely and securely migrating data and workloads to the cloud.

How Apache Spark 3.0 and Delta Lake Enhances Data Lake Reliability

Webinar

Webinar

Apache Spark has become the de facto open source standard for big data processing for its ease of use and performance. The open source Delta Lake project improves Spark’s data reliability, with new capabilities like ACID transactions, Schema Enforcement, and Time Travel. This helps to ensure that data lakes and data pipelines can deliver high quality and reliable data to downstream data teams for successful data analytics and machine learning projects. Join us in this webinar to learn how Apache Spark 3.0 and Delta Lake enhances Data Lake reliability. We will also walk through updates in the Apache Spark 3.0.release as part of our new Databricks Runtime 7.0 Beta.