Give every Alteryx workflow a front end
AI analytics on the clean, curated data your Alteryx workflows already produce.
Put your Alteryx-prepared data to work
Pick up where Alteryx leaves off
Golden connects to the destination your workflow writes to and reads it live. Your prepared data does the work, and every answer comes from the result your workflow just produced — not an extract that may be out of date.
Workflows stay in Alteryx
The connecting, cleansing, blending, and enrichment stay where they belong: in your Alteryx workflow, saved as a repeatable recipe. Golden consumes the curated result. It does not fork your logic or ask your team to rebuild it. Need something unique to your analysis? You can make those updates right in Golden so you can stay in the flow.
Governance stays with the destination
Where the output lands in a governed warehouse, each person sees exactly what their role allows. Golden reads under those existing controls and does not ask your team to maintain a second permission model.
Alteryx gives us a governed foundation for how data and business logic are built and trusted, while Golden creates a much more fluid way for people to explore that intelligence. By putting those two things together, analytics start to become less of a destination and more of an operating layer for businesses.
Bill UrciuoliChief Technology Officer, McGarrah Jessee
How Golden talks to Alteryx
| Step | What happens |
|---|---|
| 1 · Prepare | Alteryx connects, cleans, blends, and enriches — in Designer, Server, or Analytics Cloud. |
| 2 · Land | The workflow writes its output where you want it: to files (CSV, Parquet, JSON) or Google Sheets, or pushed down into a warehouse (Snowflake, Databricks, BigQuery, Redshift) when you run one. |
| 3 · Connect | Golden connects live to that destination — the same tables or files your workflow just wrote. No extract, no duplicate store. |
| 4 · Analyze and communicate | Golden profiles the data, surfaces where to start, and turns it into dashboards and stories that stay live. |
Why Golden on Alteryx is different
| Criterion | Traditional BI | Golden on Alteryx |
|---|---|---|
| Relationship to Alteryx | Competes with it; aims to pull prep and reporting into its own stack | Completes it; keeps insight in the Alteryx ecosystem |
| Prepared-data handoff | Re-extracts the output into a separate engine before anyone can use it | Connects live to where the workflow landed the data — no re-extract |
| Freshness | Bound to its own extract and refresh cycles | Live — no refresh layer of its own on top of the workflow |
| Who can use the output | Trained report builders and licensed analysts | Analysts and business users alike — no ticket queue |
| Prepared data to insight | Hours to days of modeling and dashboard building | Minutes, starting from a question |
| AI | A copilot bolted onto a pre-AI tool | AI-native from the first connection |
Golden connects to the rest of your stack too
Snowflake
AI analytics on the Snowflake data, roles, and metrics you already run the business on. Reads your Semantic Views; OAuth means Snowflake roles decide access.
Databricks
AI analytics on the lakehouse data, Unity Catalog grants, and metrics you already run the business on. Every statement lands in your Query History.
Golden × Alteryx
How do Golden and Alteryx work together?
Golden and Alteryx form a handoff, not an overlap. Alteryx prepares, cleans, and curates data — often from sources that are hard to reach — and writes the finished output to a destination. Golden connects to that output and turns it into live analysis, dashboards, and stories. Alteryx prepares the data; Golden makes it sing.
How does Golden connect to Alteryx data?
Golden connects to wherever Alteryx writes its prepared output, not to the Alteryx engine itself. Alteryx workflows land curated data in a cloud warehouse such as Snowflake or Databricks, a database, or a file such as CSV or Parquet, and Golden connects to that destination — querying the warehouse or database live, or reading the file directly. Clean, Alteryx-prepared data is ready for analysis in Golden as soon as the workflow runs.
Which Alteryx product does Golden work with?
Golden works with any Alteryx product, because it does not connect to Alteryx directly — it connects to the destination your Alteryx workflow writes to. From Golden's perspective there is no difference between one Alteryx product and another; what matters is that the workflow can output to a cloud data warehouse such as Snowflake or to a flat file such as Parquet or CSV. There is no "publish to Golden" step, because Golden has no proprietary extract engine and does not need one. The better the data feeding your warehouse, the better the output in Golden.
Does Golden overlap with or replace Alteryx?
Golden and Alteryx are complementary, and Golden is not a replacement for what Alteryx does. The two shine in different places: Alteryx excels at the heavy preparation work — normalizing, blending, and cleaning disparate data from many sources into something trustworthy — while Golden works best once that data is clean, structured, and ready to analyze. Most complex preparation stays in Alteryx by design, though analysts also have the option to do additional, lighter data prep within Golden when it is convenient. Golden completes the Alteryx workflow rather than competing with it, and the shared goal is to make joint customers more successful.
What does Golden add to an Alteryx workflow?
Golden brings Alteryx-curated data into the AI era. Data that took hours to prepare is profiled, explored, and turned into dashboards and narratives in minutes, across 40+ chart types and an AI Storyteller. Golden also makes that curated data reachable by the business users who never had the tools to use it before, not only the analysts who built the workflow.
Why does Alteryx-prepared data work especially well in Golden?
Golden delivers the most value when it starts with clean, curated data, and that is exactly what Alteryx customers bring. Alteryx unlocks sources Golden cannot reach on its own and improves quality and context along the way. More sources, better quality, and richer context translate directly into more analysis, more insight, and more value inside Golden.
Do I need to copy or duplicate data for Golden to use Alteryx output?
No additional copy is required. Golden connects to the output Alteryx already writes, and when that output lands in a warehouse or database, queries run in place so the compute stays there and no duplicate data layer is created. Golden reads the curated result where it lives rather than standing up a second copy of it.
How is Golden different from putting a traditional BI tool on Alteryx output?
Traditional BI tools tend to pull Alteryx output into their own proprietary stacks, which puts them at odds with Alteryx. Golden takes the opposite approach: it connects to the curated output, keeps insights inside the Alteryx ecosystem, and completes the workflow as an AI-native front end rather than a replacement.
Who is Golden + Alteryx for?
Golden + Alteryx is for the joint customer. Analysts who prepare data in Alteryx get faster, AI-native analysis on top of their work, and business users who could never reach that curated data get access to it for the first time. The partnership brings both groups forward and makes Alteryx-prepared data more valuable to more people.
Bring Golden to your Alteryx workflows
Connect to where your Alteryx output lands, keep your governance in place, and put live analysis in front of everyone who needs it.