Skip to content
dt-badge

This Codespace leverages the Dynatrace Enablement Framework, providing a robust and flexible development environment. Key features include:

  • Seamless operation within GitHub Codespaces, as a remote container, or locally via Docker.
  • Cross-compilation support for both AMD and ARM architectures, ensuring broad compatibility.
  • Adherence to industry standards and best practices to optimize the developer experience.

To learn more about the Dynatrace Enablement Framework and how it can enhance your development workflow, please refer to the official documentation

Enablement DQL 301#

Support Policy

This is an enablement project created by the Center of Excellence - Enablement Team at Dynatrace.

Support is provided via GitHub issues only. The materials provided in this repository are offered "as-is" without any warranties, express or implied. Use them at your own risk.

Lab Overview#

During this hands-on training, we will use the Dynatrace playground with Notebooks and Dashboards to explore the following:

  1. DQL 301 - Data Transformation: Learn how to effectively use the join, lookup, append, and data commands to combine data from multiple sources, enhancing the depth and breadth of your queries.

Future sessions

  1. Data Optimization: Optimize your DQL queries with sampling, entity usage, and timeseries data, enabling better performance monitoring and analysis.
  2. Aggregate Complex Queries: Explore techniques for aggregating complex queries using workflows and business events, allowing for more comprehensive data analysis and reporting.

By the end of this session, students will have a deeper understanding of advanced DQL features, empowering them to leverage Dynatrace for more sophisticated and efficient data analysis.

Lab tasks:

  1. Import Notebook into Dynatrace Playground

  2. Including Raw Data with data

  3. Appending Additional Data with append

  4. Connecting Data With lookup

  5. Exploring the Entity Model and Semantic Dictionary with describe

  6. Flexible Data Connectivity With join

Technical Specification#

Technologies Used#

Reference Architecture#

N/A

Continue#

In the next section, we'll cover the prerequisites for this lab.