Importing data

The import wizard turns CSV files and Excel workbooks into connected tables — field types, cross-file relations, and rollups are detected for you, and you review everything before a single record is created. Start an import Open Import data from Manage workspace at the foot of the rail, or choose Import workspace from the New menu. The wizard walks you through four steps: add files, analyze, review the plan, import. Nothing is created until the final step. Analysis only reads your data, so you can back out at any point without leaving anything behind. Add your files Drop files onto the upload area, or click browse to pick them. CSV files and Excel workbooks (.xlsx and .xls) both work, and you can add several files in one go. • Each CSV file becomes one table. Each sheet in an Excel workbook becomes its own table, so a whole workbook imports as a connected set. • The first row of each file or sheet is read as column headers. A file or sheet needs at least one data row under the header to be included. • Every sheet appears as a card showing its column and row counts — click ✕ to remove one before analyzing. Choose where the data goes The import lands in your account, adding its tables alongside the ones already there so the new data can relate to them. Your account has one home for its data — see Folders, not separate workspaces — so there is no step here that splits it in two. If you opened the wizard from a workspace where you are an Admin, a Destination picker names that workspace explicitly and is selected for you. Editors and Viewers never see it, because adding tables changes the workspace's structure and that is reserved for Admins. A workspace is created for you only if you do not have one yet — an account that was invited into somebody else's workspace and has none of its own. In that case the Workspace name field prefills from your first file's name, and you become that workspace's Admin when the import finishes. Analyze the files Click Analyze files and RowFold reads a sample of each sheet — up to the first 300 rows — to propose a plan. Every column gets a suggested field type (numbers, currency, percentages, dates, emails, URLs, phone numbers, checkboxes, select lists, and more), and select columns get their options collected from your actual values. Relations are found by matching values across files: when most of a column's values match the row names in another sheet — say an Orders file whose Customer column is full of names from your Customers file — that column is proposed as a relation between the two tables. Detected relations also produce suggested rollups, such as a count of linked rows or a total of an amount column. Let AI refine the plan When an AI model is configured, it reviews the detected plan and refines it: cleaner table and field names, better type calls, an emoji for each table, and rollups where the data makes them meaningful. It also writes a one-line summary and a short list of suggestions — things it noticed and ideas for later — shown above the plan. Without a model configured, the built-in detection still produces the full plan on its own. AI runs only during analysis; the import step itself never calls the model. Review and adjust the plan Each proposed table appears as a card you can edit before anything is created: • Rename the table or any field by typing directly into its name. • Pick which column names each row with the Row name selector. • Untick a column's checkbox to leave it out of the import — columns that look like noise, such as empty ones, come pre-unticked. • Change any column's type from its dropdown. A relation column shows the table it points to; switch it to Text if you would rather import the raw values. • Suggested rollups sit in the Σ Rollups strip — click ✕ on any you don't want. Turning a relation into text also removes rollups that depended on it. Use Back to files to add or remove files, then analyze again. Finish the import The Import button shows the total number of rows in your files. Clicking it builds every table and field, adds the records, then links relation columns: each value is matched against the row names in the related table, and matches become real record links, so rollups calculate immediately. The confirmation screen shows how many tables, records, and relation links were created — and, if any relation values had no match, how many were left blank. Click any table pill to jump straight to its records, or See the schema map to view the imported structure as a diagram. Values are tidied on the way in: currency symbols, commas, and percent signs are stripped from numbers, yes/no becomes a checkbox value, and dates are normalized to a standard format. Several files with the same columns become one table Exports are often split up — one file per year, per region, per batch — with the same columns in each. Drop them all in together and RowFold treats them as what they are: more rows of the same thing. Files whose column headers match exactly are combined into a single sheet before anything is analysed, so you get one table rather than one per file. The upload list says so — “3 files combined — identical columns, so they become one table” — and the row count is the total across all of them, so you can check it before going any further. A file whose columns differ, even slightly, stays separate and becomes its own table. Matching is on the full set of headers, ignoring case and surrounding spaces. If you genuinely want identically-shaped files kept apart, import them one at a time. Import into a table you already have Importing into an existing workspace doesn't have to mean new tables. When the destination already has tables, each sheet gets an Into: picker — create a new table, or add these rows to one that's already there. Choose an existing table and two more things appear: • Column mapping. Every column gets a picker: fill an existing field, or add it as a new field on that table. Columns are matched up by name automatically, so you normally only fix the odd one. • Match on. The column that identifies a row already in the table — a SKU, an email, an order number. Rows whose value is already there are updated; the rest are added. Leave Match on empty and every row is simply added — which is what you want for a log or a list of new records, and what you very much don't want when re-importing a corrected export. The wizard spells out which of the two will happen before you commit, and the summary at the end reports how many records were updated as well as how many were added. What an update does and doesn't touch Updating merges the incoming row into the record that's already there. Only columns with a value are written, so a blank cell never wipes what you already had — handy when your export only carries the fields that changed. Columns you left as “＋ New field” are added to the table as part of the import. Untick a column to leave it out entirely. Relation, Lookup and Rollup fields can't be mapping targets. Lookups and rollups are calculated, and text dropped into a relation would sit there looking linked while pointing at nothing — so those fields aren't offered, and a column aimed at one is skipped rather than filled with something misleading. Tips • Name a column "Name" or "Title" and it's picked as the row name automatically. • Relation columns link by matching text against the other table's row names — keep spellings identical across files for clean links. • Bringing in a Word, Markdown or text document rather than a sheet of rows? That goes into a record's doc: open the doc and choose Import. See <a href="/Help#help-docs">Docs</a>. • Untick columns you don't need instead of editing the source file — your original file is never changed. • The Workspace name prefills from your first file — you can change it any time before you press Import. • On the done screen, See the schema map shows every imported table and relation in one diagram. • Dropping in a folder of same-shaped exports is the fastest way to load a big table — they're combined automatically and the upload list shows the combined row count. • Re-importing a corrected export? Pick a Match on column so it updates the existing rows instead of doubling them. • Check the combined row count in the upload list before you analyse — it's the quickest way to spot a file that didn't parse. Good to know • Analysis samples only the first 300 rows of each sheet, so a type call can miss patterns that appear later in a large file — check the types on the review step. The full file still imports. • Relation values that don't match a row name in the related table are left blank, not kept as text; matching ignores case and surrounding spaces but the text must otherwise be identical. The confirmation screen shows a count whenever values go unmatched. • A CSV file or Excel sheet needs a header row plus at least one data row — otherwise it is skipped without warning. • A select column with more than 40 distinct values is imported as plain text instead. • Rows that are entirely blank are skipped. • Nothing is saved until you press Import — leaving the page mid-review discards the plan, and you'd need to re-add the files. • Files are combined only when their headers match exactly (case and spacing aside). One renamed column and that file becomes its own table. • With no Match on column, re-importing the same file adds every row again. There is no duplicate detection beyond the column you nominate. • The match is on the raw cell value — trailing spaces or a different date format count as a different row and will insert rather than update. • Combining is automatic: identically-shaped files can't be kept as separate tables in one pass. Import them one at a time if you need that. Who can do what • Any signed-in user can import files into a brand-new workspace; the importer automatically becomes that workspace's Admin. • Importing into an existing workspace is Admin-only: the Destination option only appears when you opened the wizard from a workspace where you are an Admin, and the server enforces the same rule when the import runs. • Editors and Viewers cannot add tables to a workspace through import — creating tables counts as a schema change, which is reserved for Admins.