Learn how to design and implement triggers in SQL Server using real-world examples.

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data.

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms.

Azure Data Engineers design and implement data solutions in the Microsoft Azure cloud. This course will teach you how to use Azure products to perform batch data processing operations.

Kafka can do more than just storing streaming data. This course will teach you to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams.

In this learning path, the learner is introduced to HDInsight and how to apply this technology to solve a range of real world challenges.

Cloud Composer is a fully managed workflow orchestration service that allows creation, scheduling, and monitoring of pipelines. This course covers the architecture of Composer and creation of pipelines to run arbitrary shell scripts and Python code.

This course brings any Big Data newbie up to speed on one of the most widely used open-source platform to build data pipelines - Apache Kafka.

Do you need to process live data streams from sensors, custom apps, IoT devices, and logs? Do you need to immediately respond to anomalies and patterns in live data streams? Are you familiar with T-SQL? If so, Azure Stream Analytics is for you.

Import data from different sources, build relationships, and enhance a model's usability so it finds widespread adoption in your organization. At the end of this course, you'll know how to build a semantic tabular model.

Data Engineering is one of the hottest topics on IT right now, as the velocity, volume, and variety of data nowadays require skills beyond just traditional ETL. In this course, you'll learn the basic concepts needed to work with Azure Data Factory.

In this course, you will learn about the Spark based Azure Databricks platform, see how to setup the environment, quickly build extract, transform, and load steps of your data pipelines, orchestrate it end-to-end, and run it automatically and reliably.