MyDataWork is the workspace around the analytical work you already do. Keep using Excel, SQL, BI, notebooks, workflows and your data platforms; MyDataWork connects that work to its use cases, stakeholders, dependencies, outcomes and value — across the tools your team already uses. Metadata only.
Bring dashboards, spreadsheets, SQL, notebooks, workflows, and cloud assets into one searchable view — so the team sees what exists without opening sensitive data.
Link assets to use cases, owners, stakeholders, objectives, and the notes that lived only in people's heads.
Track estimated and realized value across teams, projects, and initiatives — and report what drives outcomes.
Expose trusted context over MCP and scope agentic use cases in Agent Studio before you build.
See health, value, ownership, and the latest Workspace Agent findings.
Catalog the files, queries, workflows, dashboards, and cloud objects that drive decisions.
Index on-prem files and cloud data sources by metadata — via the Windows Connector and cloud connections.
Capture objectives, stakeholders, progress, notes, and value.
Trace dependencies with evidence and confidence levels.
Export leadership-ready summaries as PDF or PowerPoint.
A leadership rollup of your estate — value, utilization, dependencies, and change impact. Team & Enterprise.
Propose use cases, assess the estate, and prioritize next actions.
Scope agentic use cases before implementation.
Find stale, risky, or under-connected work.
Start from ready-made use cases for common scenarios instead of a blank workspace — free on every plan.
Turn AI recommendations into tracked next steps — and push them to Jira.
A 10-second read on your analytics estate: what's stale, what it's worth, who owns it, which tools are involved, and what the Workspace Agent recommended last.


MyDataWork builds lineage from metadata and labels each connection by confidence — confirmed, likely, or possible — with the evidence behind the link. External systems you depend on appear as ghost nodes, so hidden infrastructure becomes visible.
Because MyDataWork reads metadata and work context, never your data values or file contents, adopting it does not mean handing over your data. The security review that stalls so many tools becomes a much shorter conversation.
A column called order_date, and the fact that it is a DATE. Never the dates inside it. Not one row.
Names, types, structure, relationships, when it changed, and what people wrote about it.
Values, rows, query results, file contents, and anything a person typed into a cell.
Every one of them describes itself in its own dialect, and none of them agree. A catalog that simply stores what each tool hands it ends up with a separate pile per source and nothing that can be compared across them. Making them comparable is the work, and it is the part nobody explains. Here is the same column, as six of our sources describe it.
| Databricks | name: "order_date" | type_text: "date" |
| Power BI | name: "Order Date" | dataType: "dateTime" |
| ThoughtSpot | name: "Order Date" | data_type: "DATE" |
| Sigma | label: "Order Date" | type: { "kind": "date" } |
| Looker | name: "orders.created_date" | type: "date" |
| A spreadsheet | { "Orders": ["order_date", "region"] } | |
Six sources, six shapes, one result. The name may come through as
name, label, columnName or fieldName. The
type as type, dataType, data_type, or buried in a nested
object. Each one maps to the same two fields, attached to a named asset. That is the whole
trick, and everything downstream depends on it.
Six of the sixteen we support: Snowflake, BigQuery, Redshift, Databricks, Power BI, Tableau, Looker, Sigma, ThoughtSpot, dbt, Dataiku, Excel, CSV, Parquet, Avro and ORC. Every one speaks a different dialect. We normalize all sixteen into a single shape, which is what the rest of the product is built on.
Every source, however it phrases itself, becomes the same thing: a named column with a type, attached to a named asset.
MyDataWork holds this for every connected source: where each piece came from, how fresh it is, and, honestly, what a given source cannot publish. A CSV declares column names but no types, because the format has none. That is a fact about CSVs, not a gap in your catalog, and the page says so.
Use cases connect the work to the business reason it exists — and make its value explicit and reportable.

A deterministic, credit-free rollup that turns the work your team already tracks into a portfolio a leader can act on — built from metadata only, shown as aggregates, never cost data. It’s the view for the team lead (your workspace admin); analysts don’t touch it — their work shows up because they already organize it in MyDataWork.

MyDataWork uses the context you build — assets, use cases, lineage, value, and notes — to answer questions, propose use cases, plan modernizations, discover external data, and scope agentic workflows before anything is built. Metadata only.
An always-available assistant on every screen — ask questions, get recommendations, and act on your workspace.
Surfaces stale work, hidden infrastructure, and work losing momentum — with next best actions.
Plan and de-risk moving legacy workflows and spreadsheets — with lineage and business value attached to every step.
Find free public datasets — FRED, Census, BLS, NOAA, EIA, SEC EDGAR, World Bank — that could improve the work you already track, plus marketplace listings from your cloud providers. A free readiness check runs first, then a connection recipe you run in your own environment. Accepted sources are catalogued in lineage like any other dependency.
Define the trigger, inputs, agent role, actions, outcomes, guardrails, and handoff — then export a shareable spec.
Give agents metadata-only context over MCP — never data values or file contents.

Solution Packs load ready-made use cases for common scenarios — a structured plan you adapt to your work. Free on every plan.
Explore Solution Packs →Snowflake, BigQuery, Redshift, Databricks.
Power BI, Tableau, Looker, Sigma, ThoughtSpot.
dbt, Alteryx, Dataiku.
Python, SQL, GitHub.
Excel, CSV, and the workbooks where real work happens.
Shared folders and exports across the org.
A persistent home for the work around your analysis: what it is for, what belongs to it, who depends on it, what changed and what it delivered.
Share assets and use cases when ready, with admin controls and seat-based access.
Portfolio visibility across value, risk, ownership, and AI opportunity.
A 10-second read on the estate.
Scope an agentic use case — no code.
Start from a plan, not a blank workspace.
An AI read on what to fix first.
Data catalogs describe your data. MyDataWork organizes the work around it — the Modern catalogs govern the data estate. MyDataWork gives practitioners a workspace around the analytical work that consumes it. Use them side by side: governed data context from the catalog, active work context from MyDataWork.
Explorer is the whole product, free for 90 days. Start with demo data, then connect your own files, tools, and cloud assets when you're ready — metadata only. No credit card.