Datangle
Simplify DataOps with no-code automation and collaboration
What is Datangle? Complete Overview
Datangle is a DataOps platform designed to simplify and automate data processes for modern data teams. It enables users to create no-code CI/CD workflows, manage environments, and collaborate seamlessly. The platform integrates with popular data tools like Databricks, Snowflake, Big Query, and Amazon Redshift, eliminating the need for manual scripting. Datangle is ideal for data engineers, scientists, analysts, and even non-technical users who want to streamline their data operations. By automating workflows and providing version control, Datangle helps teams reduce errors, improve productivity, and accelerate insights.
Datangle Interface & Screenshots
Datangle Official screenshot of the tool interface
What Can Datangle Do? Key Features
No-code Workflow Builder
Datangle's visual canvas allows users to create complex CI/CD workflows without writing any code. This feature simplifies pipeline automation, making it accessible to both technical and non-technical users. The intuitive interface enables drag-and-drop functionality for designing workflows, reducing the reliance on YAML scripts and other manual coding methods.
Event-based Triggers
Automate tasks based on schedules, data updates, or custom events. This feature ensures workflows are triggered precisely when needed, whether it's a timed event or a change in your data environment. It eliminates manual intervention and ensures timely execution of data processes.
Version Control
Track changes and revert to previous versions of workflows, environments, and pipelines. This feature provides a safety net for teams, allowing them to roll back to stable versions if issues arise. It enhances collaboration by maintaining a clear history of changes and updates.
Environment Management
Automate testing, deployment, and pipeline promotion across multiple environments or data warehouses. This feature ensures consistency and reliability by managing environments systematically. Teams can deploy changes confidently, knowing that their environments are properly configured and tested.
Real-time Collaboration
Work together on workflows with real-time updates, pull requests, and comments. This feature fosters teamwork by enabling seamless communication and coordination among team members. It ensures everyone stays aligned and can contribute effectively to the data pipeline process.
Best Datangle Use Cases & Applications
Pipeline Promotion
Datangle automates the promotion of data pipelines across different environments, ensuring smooth transitions from development to production. This use case reduces manual errors and accelerates the deployment process.
Data Quality Management
Teams can implement automated quality checks and testing within their workflows to ensure data accuracy and reliability. This use case helps maintain high data standards without manual intervention.
Environment Provisioning
Datangle simplifies the creation and management of multiple environments, enabling teams to test and deploy changes confidently. This use case ensures consistency and reduces configuration errors.
How to Use Datangle: Step-by-Step Guide
Sign up for early access or request a demo on the Datangle website to get started with the platform.
Connect your existing data tools such as Databricks, Snowflake, or GitHub to integrate them with Datangle.
Use the no-code workflow builder to design your CI/CD workflows on the visual canvas. Drag and drop components to create automated pipelines.
Set up event-based triggers or schedules to automate the execution of your workflows based on specific conditions or timings.
Collaborate with your team in real-time, track changes, and manage environments to ensure smooth deployment and rollback if needed.
Datangle Pros and Cons: Honest Review
Pros
Considerations
Is Datangle Worth It? FAQ & Reviews
DataOps is a collaborative data management practice that improves communication, integration, and automation of data flows. It enhances data quality and reduces cycle time by adopting DevOps methodologies, making data processes more efficient and reliable.
Datangle is designed for data engineers, scientists, analysts, and non-technical users. Its no-code interface makes it accessible for anyone looking to automate and manage data workflows without writing scripts.
Datangle integrates with tools like Databricks, Snowflake, Amazon Redshift, and GitHub. These connections allow seamless data flow and automation within your existing stack.
You can trigger workflows based on events, schedules, or data updates. Datangle supports both manual initiation and automated triggers for flexible workflow management.
Datangle accelerates data pipeline deployments, reduces errors, and improves collaboration. This leads to faster insights, better data quality, and cost savings by streamlining operations.