Datasets
What is a Dataset?
A Dataset represents the *data itself* flowing through your network — not a specific file, table, or system. Think of it as a label for "this particular piece of business data," independent of where it physically lives or how it's technically stored at any given point.
A Dataset can be as specific as a single file (e.g. "Country File.xlsx") or as broad as a logical grouping of related data (e.g. "Vendor Assessment Data" or "Regulatory & Governance Data") — whatever level makes sense for how your organization actually thinks about and manages that information. There's no requirement that a Dataset map 1:1 to a physical file, table, or view; it's an abstraction that sits *above* those technical details.
Why this matters:
The same Dataset can pass through many different technical forms as it moves through your systems — starting as an Excel export, landing as a table in the Data Lake, appearing in a view, and finally surfacing in a Power BI report. Tagging each of those hops with the same Dataset is what lets the tool trace a straight line from the original source all the way to every report or system that ultimately depends on it — even though the underlying file, table, and view are all technically different objects.
In short:
A Dataset answers "what data is this?" — while Assets and Components answer "where does it live?" and "how does it get there?"
A Dataset represents the *data itself* flowing through your network — not a specific file, table, or system. Think of it as a label for "this particular piece of business data," independent of where it physically lives or how it's technically stored at any given point.
A Dataset can be as specific as a single file (e.g. "Country File.xlsx") or as broad as a logical grouping of related data (e.g. "Vendor Assessment Data" or "Regulatory & Governance Data") — whatever level makes sense for how your organization actually thinks about and manages that information. There's no requirement that a Dataset map 1:1 to a physical file, table, or view; it's an abstraction that sits *above* those technical details.
Why this matters:
The same Dataset can pass through many different technical forms as it moves through your systems — starting as an Excel export, landing as a table in the Data Lake, appearing in a view, and finally surfacing in a Power BI report. Tagging each of those hops with the same Dataset is what lets the tool trace a straight line from the original source all the way to every report or system that ultimately depends on it — even though the underlying file, table, and view are all technically different objects.
In short:
A Dataset answers "what data is this?" — while Assets and Components answer "where does it live?" and "how does it get there?"