IntegrateDataSquares Pipelines

Orchestrate data movement without the glue code

Design, schedule, and monitor ELT and ETL pipelines visually — from extraction through transformation to your warehouse — with durable runs, retries, alerting, and end-to-end lineage into your dashboards.

  • Visual designer — build pipelines through the UI, no glue code
  • Incremental loads and change data capture
  • Durable runs resume after failure — with lineage into your BI
Read the Pipelines documentation
daily_revenue_loadRunning
Extract
Transform
Load
crm_opportunities124K rows
billing_invoices86K rows
product_events2.1M rows
Next run: tomorrow 02:00 · Retries: 3 · Alerts: on

See it run

One canvas, source to dashboard

Extract, transform, quality-check, and load — orchestrated as one durable run, with lineage that reaches all the way to the dashboard.

Sources
salesforce124K
postgres84K
Transform
join · dedupe · cast
14 checks passed
Warehouse
live
orders82K
partition swap
Dashboard
revenue by region
lineage traced
Run #1284every 15 min resumed after restart42s0 errors running

Always in view

Every run, logged and recoverable

Row counts, durations, and errors on every run — retry from the failed step, backfill a date range, and watch volumes trend over time.

Run history · daily_revenue_loadlast 24h
#1284now82K rows
#128315m ago119K rows41s
#128230m ago118K rows2m 04s
#128145m ago117K rows39s
Retry from failed step Backfill

Rows loaded · per run

avg 118K / run 41s median

A closer look

Inside Pipelines

01

Build pipelines, not glue code

Compose extract → transform → load as a visual graph through the UI or API — versioned and run for you. No orchestration servers to operate, no Python files to babysit.

  • Visual DAG with copy, transform, branch, and loop steps
  • Cron, file-arrival, API, and dependency triggers
  • Backfill any date range as parameterized runs
02

Durable runs that resume

A crashed run picks up mid-pipeline without repeating completed work. Durable execution, per-step retries with backoff, and checkpoint restarts keep long loads resilient.

  • Resume mid-pipeline after a worker restart
  • Per-step retry policy with exponential backoff
  • Atomic partition swap — dashboards never see a half-load
03

Lineage into your dashboards

Column-level lineage flows automatically from source through every transform into the dashboards built on top — so impact analysis and trust come for free, inside one platform.

  • Source → dataset → transform → dashboard card
  • One login and audit trail across ingest to insight
  • Incremental and change data capture keep syncs cheap

What you can do with Pipelines

01

Visual designer

Compose pipelines as a graph of activities — copy, transform, branch, and loop — built through the UI or API, versioned, and run for you.

02

Flexible triggers

Run on a cron schedule, on file arrival, or on demand via API. Chain pipelines with dependency triggers and backfill any date range.

03

Incremental & CDC

Move only what changed. Watermark-based incremental loads and change data capture keep syncs fast and cheap.

04

Transforms you control

Transform with SQL models that run right in your warehouse, or visual dataflow steps — joins, filters, aggregations, and type casting.

05

Durable, resumable runs

A crashed run resumes mid-pipeline without re-doing completed work. Per-step retries with backoff and checkpoint restarts keep long loads resilient.

06

Monitoring & lineage

Every run logs rows, durations, and errors, with alerts on failures. Column-level lineage flows from source through transforms into every dashboard.

Durable

Runs resume after failure

Batch · CDC

Incremental change capture

End-to-end

Source-to-dashboard lineage

How it works

1

Pick source & destination

Any connector to your warehouse or lake

2

Design the flow

Add transform, branch, and validation steps

3

Set the trigger

Schedule, event, or API-driven runs

4

Monitor runs

Track history, alerts, and data volumes

Frequently asked questions

Pipelines covers the core ADF workloads — copy activities, transforms, triggers, and monitoring — inside the same platform as your BI. Lineage flows end to end and metering is in plain execution-hours, with no separate tools to stitch together.

See DataSquares Pipelines in action

Get a demo