Upload a spreadsheet, get an answer
The fastest way into DataLens. Drag in a CSV or Excel file and it is parsed, typed and profiled before you have finished reading the confirmation.
How it works
Types inferred from values
Not from the header row, and not from the first ten rows — from the column, with the values that would not cast listed for you.
Immediate quality findings
Duplicates, null concentrations, outliers and mixed-type columns reported the moment the file lands.
The original is never touched
Transforms run against a working copy, so the file you uploaded is recoverable no matter what you apply.
Multiple sheets
Excel workbooks with several sheets land as several datasets rather than forcing you to split the file first.
What happens after it lands
Once rows are in the catalogue, the connector that produced them stops mattering. The dataset is profiled, can be cleaned, modelled, put in a flow, governed and published exactly like every other dataset — which means switching how data arrives never means rebuilding what happens to it afterwards.
Questions about this connector
How large a file can I upload?
Files well beyond what a spreadsheet application will open comfortably. Profiling runs over the whole file, not a sample, so the findings describe your data rather than its first thousand rows.
Does it handle messy headers?
Yes. Duplicate, blank and inconsistently cased headers are normalised and reported, and the assistant proposes better names where a column name says nothing about its contents.
Is my file stored permanently?
It is held for the session you are working in, and can be routed to object storage you own if you would rather it live in your account.
Other ways in
Database
Read from your existing relational database and pull tables in as datasets.
REST API
Point at an endpoint, map the response shape, and land it as rows.
FTP & SFTP
Collect the drops that still arrive as files on a server.
CDC sync
Change data capture, so the dataset follows the source instead of ageing.
CRM
Bring customer records across without exporting them to a spreadsheet first.
Data lake
Read from — and write back to — object storage you already own.
Documents
PDFs and documents stored whole, for retrieval and generation rather than rows.
AI model providers
Your own model credentials, held as a connection like any other source.
See it on your own data
DataLens is in private beta. Bring a file, a database or an API and work through the whole lifecycle in one sitting.
Request beta access