Microsoft Azure Data Orchestration Framework

Building complex Airflow DAGs can be a time-consuming and error-prone process. Conventional approaches typically necessitate the writing of substantial Python scripts, demanding specializedexpertise and continuous upkeep. This could result in:

• Development Delays
• Code Susceptible to Errors
• Maintenance Burden
• Manual Intervention

Our Microsoft Azure Data Orchestration solution addresses these challenges by providing a flexible and intuitive method for DAG generation. Users can establish intricate workflows just by modifying the configuration JSON files, eliminating the need to write any Python code.

Benefits:

• Accelerated Insights: Achieve a 90% quicker path to valuable data insights through the automation of DAG creation.
• Boosted Productivity: Liberate your team from monotonous tasks, enabling them to concentrate on strategic data projects.
• Effortless Integration: Achieve smooth connectivity with a broad spectrum of connection types.
• Enhanced Data Accuracy: Reduce human errors by leveraging auto-generated DAGs.
• Cost Efficiency: opt for the optional local airflow setup to avoid costly managed Airflow alternatives.

Business Value:

Our Microsoft Azure Data Orchestration Framework streamlines the entire DAG creation process using Jinja templates, removing the tedious complexity of manual DAG creation and enabling customers to concentrate on their top priority - strategic data initiatives and innovation.

It offers a command line interface for its developer/data engineer users. Users select from a list of connectors and set up their preferred pipelines using a corresponding user-friendly configuration file, and the framework handles the rest. In addition to automation, our Microsoft Azure Data Orchestration Framework is a holistic solution. We provide additional consultation and in-depth Understanding how to pinpoint the ideal data orchestration tool that aligns with various use cases eliminates the need for extensive initial research and evaluation.

Features:

• Comprehensive DAG Creation: Manage individual ingestion and curation tasks or combine them into complex, multi-step workflows.
• Parameters Overriding: Ensure granular control within your pipelines by easily overriding specific parameters for individual tasks.
• No More Manual Coding: Utilize our intuitive CLI or user-friendly config files to define your pipeline needs.
• User-Friendly Interfaces: Navigate the CLI and config files easily, regardless of your technical expertise.
• Local Airflow Setup: Reduce costs and maintain complete control with an optional local Airflow setup.
• Automated DAG Placement: The generated DAG is automatically placed in your preferred target location, eliminating the need for manual transfer.
• Rigorous Data Orchestration Tool Shortlisting: Use the systematic approach provided to identify the optimal orchestration, saving time and resources.
• Customized Execution: The user can customize complex task sequences for a DAG in any fashion.
• Pre-Configured DevOps Pipeline: Kickstart your DAG generation process with a handy and pre-configured Microsoft Azure DevOps pipeline