Azure Data Factory Experts
Pipelines That Run. Every Time.
Poorly designed ADF pipelines fail silently, waste DIU costs, and block your analytics team. We design, optimize, and maintain ADF workflows that are reliable, observable, and cost-efficient — from first pipeline to production scale.
Everything Your ADF Environment Needs
Whether you're building from scratch, rescuing a broken pipeline, or scaling an existing ADF environment — we've done it before and we do it right.
Pipeline Design & Architecture
Parameterized, reusable pipeline patterns — avoiding the "copy-paste factory" anti-pattern. We design ADF solutions that are maintainable as your data sources multiply.
Pipeline Debugging & Rescue
Inherited broken ADF pipelines? We diagnose root causes — from wrong linked service configs to inefficient data flows — and fix them without rebuilding everything.
Performance & Cost Optimization
DIU right-sizing, parallel copy tuning, partition configuration, and data flow optimization to reduce pipeline runtime and Azure consumption costs.
Source & Sink Integration
Connectors for Azure SQL, Synapse, Data Lake Gen2, Blob Storage, REST APIs, SAP, Salesforce, on-premises SQL Server via Self-Hosted IR, and 90+ other sources.
Monitoring & Alerting
Azure Monitor integration, custom failure alerting, run history dashboards, and SLA tracking so you know about pipeline failures before your business does.
CI/CD & DevOps for ADF
ADF Git integration, ARM template export, Azure DevOps pipelines for automated deployment across dev/staging/production environments with proper environment isolation.
We Know Where ADF Gets Hard
Azure Data Factory is powerful — and complex. These are the areas where most teams struggle, and where our experience makes the biggest difference.
Self-Hosted Integration Runtime
Configuration, HA setup, troubleshooting connectivity to on-premises SQL Server, file shares, and internal APIs behind corporate firewalls.
Mapping Data Flows
Complex transformation logic in ADF Mapping Data Flows — including Spark cluster sizing, debug mode usage, and production performance tuning.
Incremental Load Patterns
Watermark-based, CDC, and partition-based incremental loading — avoiding full table scans on large source systems while keeping latency acceptable.
Error Handling & Retry Logic
Robust failure handling with custom error logging, conditional branching, retry policies, and dead-letter patterns to prevent silent data loss.
Metadata-Driven Pipelines
Single generic pipeline driven by a control table — eliminating the need to create individual pipelines for each source table, massively reducing maintenance overhead.
ADF + Azure Synapse Analytics
Synapse Pipeline vs ADF decision guidance, workspace integration, and migration between the two when your requirements evolve.
Fast Engagement, Lasting Results
ADF Environment Review
We audit your existing ADF workspace: linked services, datasets, pipeline structure, trigger configuration, and monitoring setup — identifying what's working and what's not.
Priority Fix List
We deliver a ranked list of issues and improvements with estimated effort and business impact. You decide what to fix and in what order.
Implementation & Testing
We build or refactor pipelines in a development workspace, test against real source data, and promote to production with your sign-off.
Handoff & Documentation
Every pipeline we build or modify is documented — design rationale, parameter descriptions, error scenarios, and operational runbooks for your team.
Azure Data Factory Questions
Our ADF pipelines keep failing and we don't know why. Can you help?
Yes — pipeline rescue is one of our most common engagements. We typically identify the root cause within 1–2 days of access and have a remediation plan ready shortly after.
Should we use ADF or Synapse Pipelines?
It depends on your broader architecture. If you're using Azure Synapse Analytics as your analytics platform, Synapse Pipelines is the natural choice. For standalone integration scenarios without Synapse, ADF is usually more cost-effective.
Can you connect ADF to our on-premises SQL Server?
Yes. We configure Self-Hosted Integration Runtime for secure, reliable connectivity between ADF and on-premises sources — including SQL Server, Oracle, file systems, and SAP.