Alteryx workflows have a way of becoming infrastructure.
A workflow starts as a practical solution: blend the Excel assumptions file, clean up the partner CSV, join it to staged SQL, produce the forecast, push the output downstream. Then people begin to depend on it. Finance builds a dashboard from the output. Supply chain uses it in planning. A manager starts asking for the number every Monday. Months later, the workflow is no longer just an analyst’s canvas. It is part of how the business runs.
Alteryx is excellent at building that workflow. Designer gives practitioners a powerful canvas for data prep, blending, modeling, automation, and repeatable analytical logic. And Alteryx has gotten serious about lineage: Alteryx Connect has provided technical lineage by loading metadata from source and target systems and interpreting Alteryx workflows, while newer Alteryx One catalog integrations push lineage metadata from Server runs into external catalogs such as Atlan and Collibra.
The harder question is what happens around the workflow. The hand-maintained inputs. The downstream dashboards. The duplicate efforts in Python or Power BI. The stakeholders who depend on the output. The business value the workflow is expected to produce. That surrounding context is what determines whether a workflow should stay in Alteryx, move to Python or dbt, be rebuilt in the warehouse, or be retired altogether.
That’s the gap MyDataWork is built to fill.
A scenario most Alteryx teams will recognize
Ray Delgado is the senior demand-planning analyst at a mid-market manufacturer. His team owns ManufacturingDemandForecast_v3.yxmd — the Alteryx workflow that blends an Excel assumptions file, a weekly partner CSV, and staged SQL into the demand forecast the supply-chain and finance teams plan against.
Ray knows the workflow cold. He knows every tool on the canvas, every input connection, every join. If his organization runs Alteryx Connect or pushes to an enterprise catalog, he can trace the technical lineage too.
What none of that tells him:
- That the partner CSV feeding the workflow is manually refreshed by one person every Monday — and when that person is out, the forecast can still run, but against stale input
- That the executive Power BI dashboard finance reviews every Monday and the Tableau scorecard his VP opens every morning are both built on his workflow’s output — sitting outside the canvas, in tools Ray has no single inventory for today. MyDataWork catalogs them alongside the workflow, so the connection he otherwise tracks only in his head becomes something he can see and document
- That a teammate has been building a parallel forecast in a Python notebook, unaware Ray’s workflow already produces the number
- That the VP of Supply Chain is the real stakeholder for this work — and that the CFO will ask “what is the forecasting work actually saving us” in next quarter’s planning, with no portfolio-level answer ready
These are not failures of the workflow. They are context gaps around it. And for most practitioners, that context lives one layer above any single tool.
What the canvas doesn’t tell you
Alteryx builds the workflow. MyDataWork shows the work around the workflow — and the business purpose above it. In practice that’s three things.
Cross-tool inventory. The Windows Connector catalogs Ray’s .yxmd workflows alongside the assets around them: the Excel reference file his business partner maintains, the partner CSV, the staging SQL, the Power BI and Tableau dashboards built on the forecast output (cataloged alongside the workflow, with the dependency one you confirm rather than one inferred from a shared warehouse table), the Snowflake tables in the pipeline, and the Python notebooks a teammate used to validate the approach. MyDataWork does not need to read the underlying business data to make that work visible.
The asset catalog brings every tool into one inventory — ManufacturingDemandForecast_v3.yxmd (badged “Alteryx”) sitting alongside the Excel, CSV, SQL, Power BI, Tableau, Snowflake, and Python work around it.
Cross-tool lineage. For the assets around the workflow, MyDataWork infers dependency edges from the structural references in each file. The Alteryx workflow takes its place on that map: MyDataWork reads the inputs it depends on — the Excel and data files it reads — and connects the workflow to them, matched by filename and shown as Likely connections you can confirm. Inputs it touches that aren’t yet cataloged are flagged Not in catalog. Every inferred edge carries a confidence level, so you can see at a glance how solid each connection is — from confirmed shared-table lineage to likely file matches.
MyDataWork reads the workflow’s metadata and maps what it depends on: the Excel inputs it reads (matched by filename — shown as Likely connections you can confirm) and the uncataloged sources it touches (flagged Not in catalog). Connection confidence is shown on every edge, so you can see how solid each link is at a glance.
Business context. This is the layer technical tools often don’t capture consistently across the full practitioner workflow — and where much of the day-to-day value becomes visible.
Use case documentation. Ray links the forecast workflow to a documented use case: Improve mid-market demand forecast accuracy. He sets the baseline (forecast error at 18%), the current state (12%), and the target (8%). He records the estimated value ($240K/year in avoided overstock and expedite costs) and updates the realized value as the work delivers.
Ray’s forecast-accuracy use case documents the baseline, current state, and target, with realized value tracking the work as it delivers. The VP of Supply Chain is linked as the stakeholder.
Stakeholder linking. The VP of Supply Chain is added as the use case stakeholder, visible on the use case and on the lineage view, so anyone touching the underlying assets knows who depends on them. The Workspace Agent’s missing-stakeholder check flags any active use case that doesn’t have someone assigned.
On-demand workspace review. Ray runs the Workspace Agent when he wants a structured read of his workspace. It surfaces patterns across six categories — duplicate parallel work, missing stakeholders, stale use cases, high-value work tracking below estimate, dependency breaks, and assets that have quietly become hidden infrastructure. With the forecast workflow now linked to four separate use cases, the agent flags it as exactly that kind of load-bearing asset — the one worth coordinating around before anyone changes it.
The Workspace Agent surfaces findings across categories. The highlighted one flags ManufacturingDemandForecast_v3.yxmd as referenced across four active use cases — the kind of load-bearing asset worth governing carefully before any change.
Portfolio reporting. When the CFO asks what the forecasting work is worth, Ray generates a portfolio export — linked assets, documented use case, baseline-to-current improvement, value realized to date. The conversation moves from “we run a workflow” to “here’s what it produces.”
Not a replacement for Alteryx — a context layer around it
MyDataWork is not an enterprise data catalog, and it’s not a replacement for Alteryx Connect or the Alteryx One catalog path. Tools like Atlan, Alation, and Collibra — and the lineage Alteryx pushes into them — serve top-down governance for teams rolling out catalog discipline at scale. Those investments work, at enterprise scale.
MyDataWork is built for the practitioner: the demand-planning analyst, the analytics engineer, the workflow builder developing a working practice from the bottom up. Your Designer workflows keep doing what they do. Your Connect or enterprise-catalog setup, if you have one, stays in place. MyDataWork adds the work-context layer above both — the documentation of why each workflow matters and what it produces — without an enterprise catalog implementation.
Try it on the work that matters most
MyDataWork’s Explorer plan is 90 days, free, no credit card. For an Alteryx-centric practitioner, it’s enough room to start with a handful of workflows that matter most and the assets around them: the inputs they depend on, the dashboards built on their output, and the outcome metrics leadership cares about.
Build the documentation practice around those, link the people who care, set the outcome metrics that matter, and let the agent surface what you’d miss. When you outgrow it, the paid plans lift the asset caps and your work carries forward — the workspace you built becomes the foundation you expand from.
Why this matters for Alteryx modernization
The Alteryx community is in a moment of decision. Many teams are being asked to rationalize their workflow estate: what should stay in Alteryx, what should move into Python, dbt, or the warehouse, and what should simply be retired. The hardest part of that decision is not always the rebuild. It is knowing what each workflow feeds, who depends on it, what business outcome it supports, and what is worth carrying forward versus leaving behind.
That is a work-context question, and it is the one MyDataWork answers before modernization starts. Migration Assist goes further by rating workflows and related assets for modernization fit — effort, risk, recommended path, and confidence — so scope decisions are grounded in analysis rather than guesswork.
The same context matters for AI. Whether the agents your leadership deploys come from your BI platform, your cloud provider, or an internal build, they will need more than workflow metadata. They will need to know which analytical products serve which business outcomes, who depends on what, and which work is worth protecting, migrating, or retiring. Your canvas holds the logic. MyDataWork holds the context any agent — or any migration — needs to reason well about it.
Start here. Email only, no credit card. Connect your folder of .yxmd workflows and the files around them, and you’ll start seeing the surrounding surface area mapped in minutes.