Big Data Labs

Hands-on Labs are the fastest way to gain real experience with Big Data. Labs guide you step by step in a secure, sandboxed environment. No new accounts, no additional costs, and no test instances to clean up.

Lab playgrounds

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Using Azure Synapse Analytics to Query Data Lake

Stefano Cascavilla

Handling S3 Objects Events With Lifecycle Policies and Server Access Logging

Using Azure Data Factory Pipelines to Copy Data

Andrew Burchill

Getting Started with Amazon Redshift

Andrew Burchill

Working with Special Characters and Anchors in Regular Expressions

Andrew Burchill

Efficiently Storing Data in S3 for Data Analytics Solutions

Andrew Burchill

Sessionizing Clickstream Data with Amazon Kinesis and Managed Apache Flink

Stefano Cascavilla

Structure and Analyze Data with Google BigQuery

Analyzing IoT Data Using Azure Stream Analytics

Query Encrypted Amazon S3 Data with Amazon Athena

Andrew Burchill

Aggregating Data with Amazon Managed Streaming for Apache Kafka (MSK)

Andrew Burchill

Using Regular Expressions Effectively in the Real World

Andrew Burchill

Constructing Regular Expression Character Classes

Andrew Burchill

Collecting Log Data with Kinesis Agent and Querying with Amazon Athena

Stefano Cascavilla

Run SQL Queries and Analyze Data with Google Cloud SQL

Stefano Cascavilla

Starting a Highly Available Graph Database With Amazon Neptune

Submitting a U-SQL Job to Azure Data Lake Analytics

Stefano Cascavilla

Deploy a MongoDB Solution With Amazon DocumentDB

Stefano Cascavilla

Deploy a Fully Managed and Scalable SQL Database With Google Cloud Spanner

Andrew Burchill

Configuring Distribution Styles and Table Access in Amazon Redshift

Stefano Cascavilla

Working With Incremental dbt Models

Stefano Cascavilla

Create and Execute Your First dbt Models

Stefano Cascavilla

Configure a dbt Profile and Define Sources

Stefano Cascavilla

Create Your First dbt (Data Build Tool) Project

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