Azure Data Factory (ADF)

Overview

We design and build Azure Data Factory pipelines for the databases, file shares, SFTP drops, and SaaS APIs you already use. Each pipeline is parameterised so the same definition runs in development, test, and production.

We configure integration runtimes, triggers, and failure alerts, then migrate SSIS packages or hand-written scripts where those are what you run today. Cutover includes row-count checks against the source, not a hope that the first schedule will be right.

What we deliver

• Parameterised ADF pipelines with retry and alerting
• Linked services, datasets, and integration runtimes for dev and production
• Mapping data flows or stored-procedure steps where a transform needs them
• Runbook covering triggers, failure codes, and how to reprocess a day

Business benefits

• Failed loads are visible the same morning, with a defined retry path
• One pipeline definition is promoted between environments instead of copied by hand
• Source changes are handled in parameters and mappings, not in new scripts