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DATAVERSES CONNECT

From raw data to business intelligence in minutes

Visual and AI-powered pipelines — build with Agent support or drag-and-drop, configure every node, and trace lineage end to end.

Build pipeline onboarding in Dataverses Connect

How it works today

From connected sources to trusted reports — with visibility at every step.

  1. 1

    Connect sources

    Pull from channels already linked in Connect — orders, payments, and catalog in one model.

  2. 2

    Build with Agent or canvas

    Prompt the agent to assemble the DAG, or drag Filter, Join, Aggregate, and SQL nodes yourself.

  3. 3

    Configure, preview, and trace

    Edit node logic, inspect Table/Chart/SQL output, and toggle lineage when you need provenance.

  4. 4

    Publish outputs

    Export trusted tables wherever they are needed — including Report and Design Canvas, so every view stays on the same numbers.

Built for how pipelines actually get shipped

Author, inspect, and govern analytical pipelines without switching tools.

01

Build pipelines at the speed of thought — code, drag, or prompt

Whether you prefer precise visual controls or natural language generation, build multi-step analytical pipelines without context switching.

  • Agent-assisted creation — describe transformations in plain English and let the AI Agent assemble DAG nodes on the canvas.
  • Rich operator palette — Source, Filter, Combine/Join, Aggregate, SQL, and Output ready to drag onto the flow.
  • Hybrid execution — drag operators manually or prompt the agent to insert and connect new nodes inline.
Pipeline canvas with connected DAG nodes and Agent prompt bar

02

Full control over every node — configure, inspect, and execute

Inspect input schemas, customize transformation logic, and preview output data at any point along your workflow.

  • Deep node inspector — click any node to see metadata, SQL, row counts, and transformation rules.
  • Multi-format preview — validate results across Table, Chart, SQL Query, and Raw tabs without leaving the canvas.
  • Iterative debugging — run individual nodes to catch data quality issues before a full pipeline run.
Node inspector with SQL configuration and chart preview

03

Trace data provenance with built-in data lineage

Understand exact upstream dependencies and downstream impacts with automated graph visualization.

  • One-click view toggle — switch between Data Pipeline View and Data Lineage View.
  • Column-level traceability — track how fields flow through joins, aggregations, and CASE statements.
  • Audit-ready logs — review execution history, row counts, and run timestamps on every step.
Data Pipeline execution canvas layered with the Data Lineage view showing column-level flow into the RFM table

Frequently Asked Questions

How Connect pipelines keep ecommerce data trustworthy.

  • No. Connect pipelines are built for ecommerce teams. You compose the canvas, prompt the agent, edit node configuration, and run — Dataverses handles ingest, transform, and refresh.

  • Yes. Open any node to update filters, joins, fields, or SQL — or ask the agent in plain language — then re-run. You do not need a separate config file or redeploy.

  • Yes. Switch from Data Pipeline View to Data Lineage View to see upstream dependencies, downstream impact, and how fields flow through each transform.

  • Yes. Reports and Design Canvas read from the same pipeline outputs, so every view stays aligned.

Ready to Build Data and AI Applications?

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