ANOW! Automate integrates with Azure Data Factory (ADF) to provide unified orchestration and control over your data pipelines within hybrid environments. This integration allows ANOW! Automate to trigger and execute both Azure Data Factory Triggers and Pipelines, consolidating fragmented data operations into a single operational dashboard for faster incident detection and consistent status views.
The ANOW! Automate integration with Azure Data Factory (ADF) serves as a robust solution for centralizing the management and orchestration of data workflows across complex hybrid IT landscapes. It enables ANOW! Automate to seamlessly interact with ADF, supporting both the triggering of existing ADF Triggers and the direct execution of ADF Pipelines. This bidirectional control enables sophisticated automation of data ingestion, transformation, and processing, ensuring data readiness for downstream consumers.
The integration leverages an Azure Server Node for executing cloud automation tasks, with an Azure Endpoint providing secure access to specific Azure services. Azure Data Factory Triggers, configured for time-based or event-based automation, are scheduled and managed directly within ANOW! Automate. This ensures that data pipelines always process the most current data, eliminating delays and idle resources often associated with traditional time-based scheduling. ANOW! Automate also manages Azure Data Factory Pipelines, facilitating the creation, transformation, and processing of data within the Azure cloud with precision and reliability.
This powerful integration is designed for enterprise IT decision-makers and data engineering teams in large organizations, particularly in financial services, manufacturing, and retail. It addresses the challenges of fragmented data operations, compliance requirements, and the need for demonstrable ROI in hybrid IT environments. By unifying control over ADF and other enterprise systems, ANOW! Automate helps mitigate business risk, optimize operational efficiency, and future-proof IT infrastructure against skills gaps.
Consolidate all data operations—pipelines, jobs, transfers, and refreshes—into a single operational dashboard. This unified view, regardless of platform, enables immediate failure identification and consistent status for business stakeholders, reducing Mean Time to Resolution (MTTR) and providing a single source of truth for audit and compliance.
Replace rigid time-based schedules for ADF pipelines with dynamic, event-driven triggers. Ensure pipelines run only when complete data is available, triggered by events such as file arrivals or upstream job completions, resulting in more responsive data processing and fewer missed SLAs due to incomplete or stale data.
Orchestrate entire data pipelines as a single, governed flow across diverse cloud and on-premise platforms, including AWS, Azure, SAP, and Snowflake. This gives you consistent governance and clear lineage, turns cross-cloud data delivery into a single business process, and improves reliability and control.
Implement a dynamic SLA model that continuously analyzes run statistics and recalculates critical paths in real-time. Automatically execute predefined remediation actions upon risk detection, such as targeted retries or resource scaling, significantly improving SLA attainment and reducing manual operational firefighting.
Use Cases
DATA ENGINEERING
Automate data transfer from SAP to Azure Data Factory, ensuring timely processing and reporting for critical business insights.
IT OPERATIONS
Gain a single pane of glass to monitor all ADF and on-premises data operations, improving incident response.
COMPLIANCE
Apply CI/CD practices to ADF artifacts to ensure version control, automated validation, and auditable releases for compliance.
BUSINESS USERS
Empower business users to securely trigger ADF pipeline refreshes with controlled parameters, reducing the engineering team's workload.
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In the 2025 Gartner Magic Quadrant for Service Orchestration and Automation Platforms (SOAP), Beta Systems Software was recognized as a Leader. Discover key market trends, vendor strengths and cautions, and how ANOW! Suite has been evaluated.
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Our architecture ensures that data processing and storage strictly comply with EU regulations such as the GDPR. Beta Systems is a trusted European software provider, and our solutions, including the ADF integration, are designed to support data sovereignty through local support and implementation partners, providing complete peace of mind on compliance.
Yes, ANOW! Automate offers over 600 out-of-the-box integrations, supporting a wide range of cloud services, including AWS and Google Cloud, alongside databases, ERP, ETL, and mainframe systems. This enables true cross-cloud data pipeline orchestration, providing a single point of control for your entire hybrid IT landscape.
We show you a clear path to measurable ROI within 12 months. This is achieved through quantifiable metrics such as reducing manual tasks by 40-60%, cutting batch runtimes by 20-30%, and drastically shortening audit preparation time from weeks to hours, which directly translates into significant cost savings and reduced risk.
ANOW! Automate meets the highest industry security standards, including GDPR, ISO27001, SOX, SOC 2, and PCI DSS. Our integration with ADF provides secure access via Azure Endpoints, with centralized configuration, role-based access control, encrypted data transfers, and comprehensive audit logging, ensuring strong data and process protection.
ANOW! Automate orchestrates critical workloads across Google Cloud services like Compute Engine and BigQuery, unifying operations with your hybrid IT landscape. We enable granular control over VM lifecycles and data pipelines, ensuring cost discipline and auditable compliance across your Google Cloud estate without custom scripting.
ANOW! Automate on Amazon Web Services (AWS) provides enterprise-grade workload automation and orchestration, consolidating diverse AWS jobs, container services, and data pipelines into a single operational dashboard. This gives you unified visibility and control across hybrid and multi-cloud environments, helping you meet up to 99.95% SLA for critical business processes.
ANOW! Automate extends Kubernetes' native scheduling, providing an essential orchestration and control plane that transcends cluster boundaries. It enables event-driven responses, creates and manages containers on demand, and executes critical business applications within pods, optimizing resource utilization across hybrid environments.
ANOW! Automate provides deep, native integration with Microsoft Azure, offering a single, governed control plane that orchestrates mission-critical workloads across Azure services and the broader enterprise IT estate, ensuring unified monitoring and control with event-driven precision.
ANOW! Automate integrates natively with Microsoft Teams, establishing bidirectional communication between orchestrated workflows and the collaboration platform. This allows real-time notifications, approvals, and operational commands to flow directly within Teams, significantly reducing mean time to detection and improving collaborative response without switching tools.
ANOW! Automate integrates with Amazon EMR to orchestrate big data processing workloads, automatically provisioning and scaling clusters for data pipelines. This integration ensures that complex data transformations execute efficiently, optimizing resource utilization and accelerating time-to-insight for data-driven enterprises.
ANOW! Automate orchestrates Azure Databricks workloads, enabling unified monitoring, event-driven job execution, and cost governance across hybrid cloud environments. We provide tasks for managing clusters, running jobs, and monitoring activity, ensuring predictable Azure spend and enterprise-grade SLA protection for critical data pipelines.
ANOW! Automate integrates with dbt (Data Build Tool) to orchestrate and monitor data transformation workflows, supporting both dbt Core and dbt Cloud instances. This enables unified control over dbt runs, models, and tests, providing native access to run status and execution logs, ensuring data freshness and audit readiness.
