Reducing the time from data collection to analysis can be crucial in certain industry scenarios. Databricks’ Delta Live Tables enables efficient data streaming to reduce this analysis latency while also assuring data quality.

Getting data from its source to a quality-assured state is fundamental for application usage. The processes to go between these states are often fixed in step-by-step solutions, which can be inflexible and often inefficient, adding to the time between data collection and analysis. Delta Live Tables (DLT) innovates by following a declarative approach, in which users define rules between data states, and the ETL takes care of the rest, determining the most efficient path to stream data from collection to consumption.

In this recorded webinar Thorogood data and analytics consultants Melissa Horan and Fernando Takeshi explore the DLT functionality and consider its value via a data streaming use case in which we collect, process, and predict flight delays based on real air traffic data.

What to expect

This webcast includes a presentation and demo, focusing on the following topics:

• Introduction to the Delta Live Tables ETL and its capabilities for data streaming
• Hands-on use case presentation and deep dive
• Data streaming applications discussion and how to get started based on different organizational needs

Is it for you?

Here are a few questions to help you decide:

• Would you like a better understanding of data streaming and how to get started?
• Are you interested in machine learning and want a hand on demonstration on how to apply it to a real-world use case?
• Do you work in industries such as aviation, consumer goods or logistics and want to understand how data streaming and machine learning can be relevant to your business?