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- Cloud
- Data
Stream Processing with Apache Spark Structured Streaming and Azure Databricks
Streaming data is used to make decisions and take actions in real time. The processing of streaming data must support these virtually immediate results, by the stateful analysis of multiple events over a period within one or multiple data streams. It must also support the joining of streaming data with data at rest in databases. The purpose of this skill is to teach you how to process streaming data using Apache Spark with Azure Databricks.
Content in this path
Beginner
Understand the processing model for streaming data, as implemented in Apache Spark Structured Streaming.
Intermediate
Build a streaming data processing pipeline using Apache Spark Structured Streaming.
Advanced
Apply your streaming data knowledge inside of Azure Databricks.
- The fundamentals of modeling streaming data
- Governance and quality concerns around streaming data
- Streaming data processing using Apache Spark Structured Streaming
- Streaming data processing in Azure Databricks
- Java
- Distributed Systems Literacy
- Basic SQL
- Relational Database Design Literacy
- DevOps for Streaming Data
- Data Governance
- Data Analysis
- Machine Learning